Is there any established database schema to store references? I wonder whether there exists any well-established database schema(s) to store references.

For example, the Perl package Bib2ML (aka. Bib2HTML) contains a bib2sql tool that generates a SQL database from a BibTeX database, with the following schema:

If there is no well-established schema, I am still interested to know about alternatives. One can assume the data it contains can be extracted from the paper or the BibTeX (i.e. no need to be able to store information coming from other sources, and the focus is on the reference, not the paper's content).

If you would consider an approach of storing bibliographic information in XML format, either directly (as XML files), or indirectly (via serialization or XML-to-RelationalDB conversion), you might find the following resources of interest (some of the resources are general and/or database-focused):

Metadata Object Description Schema (MODS) by The Library of Congress (USA);
Standards at The Library of Congress page lists a host of relevant information;
Apache OpenOffice bibliographic implementation and bibliographic database information;
development documentation for any other open source bibliography management software (JabRef, Zotero, etc.); for more information, see this list;
Dublin Core Metadata Initiative (DCMI);
List of citation standards, which might be used to store bibliographic metadata (by DCMI);
Finally, for the NoSQL way of doing things, consider using BibJSON schema and, for the linked data emphasis, consider using JSON-LD (also see this relevant article).


Professional goals in pursuing a doctoral degree - Statement of Purpose I am a prospective Ph.D. applicant in the area of Robotics Controls and Biomedical Engineering (US universities). As a part of universities' SOPs, I am supposed to talk about my professional goals in pursuing a doctoral degree (or current degree goals).

I am really confused over what to discuss about it in my SOPs. If you ask me about my goal of enrolling in a doctorate degree, I would say that I want to be able to make a contribution in my field through my research, and subsequently develop core expertise in the field so that I can join some top-level R&D organization/startup after completing Ph.D. (This answer might be a cliche and other applicants might have written the same thing.)

Is it literally that easy to talk about one's doctorate goals? Or do I need to work on it more and come up with a better answer?

Any direction/feedback/critique is welcomed.

Your SOP as a whole should cover your professional background in terms of classes, research, former professional experience, and your goals going forward. It sounds like you're asking about the last part of this.

Yes, your goals going forward are to do a good PhD and to get a job at a start-up. Those are reasonable goals, so it's reasonable to list them.

To the extent possible, you should be specific: what kind of research, which core skills, what types of jobs, etc. Obviously you want to leave yourself enough room so that your interests can evolve, but if you can articulate a well-thought-out, realistic plan for what you're going to do with this PhD after you get it, that will put you heads-and-shoulders above most applicants, who will be focusing on the PhD as an end in itself, or haven't considered jobs other than hyper-competitive faculty positions.


How long before PhD graduation should I start applying for academic jobs I hope this is not a duplicate, I saw this question:
How long before PhD graduation should I start applying for post-doc positions?

However, I didn't find any analogous question for applying for jobs (academic). Is there a certain timeline to look for jobs?

In particular, do I need to have completed the PhD or fulfill any requirement (e.g. submitted thesis) before I can look for jobs?

I am considering any kind of academic job, tenured, or non-tenured jobs like lecturer and adjunct posts.

I am looking at mid-tier universities in Asia, in applied mathematics and related fields.

For postdoc positions: apply approximately 3-6 months before graduation.

For (UK, AU)-lecturer and assistant professor positions: apply approximately a year before the graduation.

Usually, you have to be graduated by the first day you start with your job duties, though exceptions exist.


Methods for Assessing The Performance of an Exam What are some common methods for assessing how well a exam works, once you have the results back? This is something of a generalization of How to measure entropy of exam results.

I've seen professors regress scores against some potentially interesting covariates (majors vs. non-majors, gender, etc.) and look at which questions were predictive of your overall grade, but I'd be interested to see if there's a particular battery of tests one should look at to see if an exam is "well written".

The most common analyses I've seen are generated automatically by scantron grading software, and are thus only used for multiple choice questions. But a motivated person could perform the analyses themselves.

I've read a few articles on test analysis over the years, and this summary of a particular scantron software's results seems like a good overview of test analysis in general. A quick summary to improve searchability:

Item statistics:

Item difficulty - percentage of students answering correctly. Desirable = above chance.

Item discrimination - how much item correlates with test as a whole (students who did well on the exam get this right more than low-level students). Uses stat like Pearson Product Moment correlation. A "good" question has a score over 0.2.

Test statistics:

Reliability coefficient - A general measure of test length, breadth and its intercorrelations. Scores above 0.8 are considered excellent for a classroom test.

Some other interesting measurements are used more in standardized testing, rather than classroom testing. These definitions are taken from this overview.

Construct validity - does the exam actually measure the subject, or some other variable like reading skill. Generally uses a panel of "experts" or feedback by students.

Split-half reliability - measures whether different test items that purport to test the same concept produce similar results within a single exam.

Criterion-related validity - measures how well the new test correlates with a known exam, like an ETS field test or GRE subject test.

If you don't get a basic output from scantron software, is there a department on your campus that will analyze your exam for you?


How do I politely ask a professor to contact another professor he knows to accept me as PhD student? I sent an email to a professor for possible acceptance as a PhD student, but sometimes it takes too long to hear back.

I know another professor, that has a good knowledge (experience) with the first professor. Can I ask this second professor, in polite way, to contact the first one, and discuss with him whether to accept me as a student?

Is this possible? What should I say to the second professor?

If you know the second professor well, there's no harm in hinting.

By "hinting", I mean, you're having a chat with Prof. 2, and you mention that you wrote to Prof 1 but haven't heard back.  Ask for Prof 2's advice -- for example, "Do you think I should try sending him a second email?"

If you're lucky, Prof 2 will at this point offer to speak up on your behalf with Prof 1.

If not, during this conversation you will hopefully get vibes in one direction or the other, and will know whether it would be worthwhile to make the request.

The worst that could happen would be that Prof 2 says no.

By the way, I hope you have tried re-sending your original email.  People are fallible, especially when it comes to answering email.


How much information should I reveal in a postdoc interview, when I am also applying for a fellowship at a different institution? I have been invited for an interview to a post-doc position. In the same time, I am applying for a post-doc fellowship to a different organisation. If that fellowship application will be successfull, I will have to quit the postdoc position (where I am going to do interview) somewhere in the middle, because I am more interested in that position with the fellowship.

I know, I don´t have any clues whether any of the two positions will work out, but how should I address this fellowship opportunity on the intreview?

Should I let them know in advance that I am applying for a fellowship and let them decide whether they want to interview me anyway? Or should I mention only at the interview, that I am applying for a fellowship? Or shouldn´t I mention it at all?

They will probably ask you if you are applying or evaluating other positions during the interview, if they don't you don't have to bring it up.

But if they do ask, just say you currently don't have any offer in hand but that you are applying to other positions. When and if they make you an offer, at that point you should decide to accept it or not, or to ask for extra time to make your decision. But switching post-doc half way will not be good for your CV or your research, but that's another question.


Uploading under review paper to arXiv Can I upload a paper (status: Under Review) submitted to ACM CSUR to arXiv?

Across a large part of the landscape of scholarly publications, pre-prints are (confusingly) regarded as unpublished draft versions of manuscripts that happen to circulate prior to their full-fledged publication at journals (or other outlets). It follows that to many journals & publishers, it is fine to disseminate pre-prints even prior to the first submission or during the review process.
However, it seems to me that ACM follows a bit of a stricter policy. At ACM CSUR, the Author Guidelines state:

Publication, or republication, of a (perhaps revised) paper that has been widely disseminated is permitted only if the editor judges that (a) the revision contains significant amplification or clarification of the original material or (b) there is a significant additional benefit to be gained from journal publication.

With such a wording, I would be cautious, as you cannot know whether you will need to integrate major revisions or not during the review process. I would recommend you to talk to the editor directly and ask about their stance with regards to your manuscript. (Perhaps the editors are more liberal regarding pre-prints than the wording of the ACM policy on prior publications.)


What master's degree is recommended to study at a university for establishing a start-up? I studied for 3 years computer science at a relatively good university, and at the same time I have several years of experience with broad and deep knowledge in many fields on the subject. I am a creative person and I am interested in expressing my Innovative ideas by setting up a start-up from scratch which will bring a technological solution to many companies in high-tech.
I wanted to ask in general what it is recommended to study for a master's degree so that I can bring the product that I can build independently through my knowledge of computer science and experience to a successful start-up company?

Given that a start up is a business and your education is elsewhere, it would probably do you well to get some specific knowledge of business and the regulations that typically govern business. An MBA might be appropriate if it is focused on entrepreneurship. Economics is probably not what you want, being a more theoretical course of study. Marketing might be an alternative. But it would depend on the particulars.
You can hire business experience, of course, once you have some revenue or can talk people in to working for nearly nothing, but lack of knowledge yourself might mean you need to trust them more than is wise.


How to improve my capacity to follow my advisor's instructions during research? I am a Computer Science undergraduate doing a research project in Bioinformatics. I know my weaknesses, especially that I am not good at speaking, listening, and interacting with people in all social context. Until now, this wasn't a problem, I hardly paid attention in class, studied by myself directly from books, and got excellent grades. But in my current position, I have come to understand that I have to improve some social skills if I want to advance. Right now, it's plainly difficult to me to follow the rationale among two or more phrases if I don't see them on paper and this characteristic is causing problems because my advisor's instruction are mostly oral.

Although my professor praises my ability to do math and program, he complains about how I easily lose track of the instructions. This is a true problem, specially when processing biological data (one thing is that the program works, the other is that it makes biological sense and I am not yet conversant in biological background). This situation is starting to raise problems with my advisor and I have to find a solution before everything gets worst.

Note: I take notes. This is the most logical, straightforward solution, but I never developed the ability to take good notes as I didn't like attending classes. I'm working to improve this skill, but I the problem of connecting orally communicated ideas effectively remains.

As a summary, I have to figure out how to follow the incredible amount of oral information passed to me, even if I have never built this ability.

I've found that taking notes, even point form, is really helpful.

Even if you were good at understanding oral instructions, taking meeting notes would be useful.

They let you go back to things you didn't have much time to think about at the time later on.

You could also email your supervisor a summary of your understanding of the meeting and your plans until the next meeting, so that he has a chance to correct/clarify in writing any misunderstandings, or refocus your priorities.

As for the problem of connecting oral instructions, you should take every opportunity to confirm your understanding of the main points discussed so far in the meeting. Rephrase what you just heard back to your supervisor. If there is a definition you don't know, either ask right away, or jot down the word to ask about later.


How "submitted", "to appear", "accepted" papers are evaluated in a CV? Assume a search committee is reading my CV and in the publication section they notice some of my papers are only submitted or claimed to appear in a journal (or accepted for publication in a journal). Sometimes the journal which has accepted the paper for publication lists the title of accepted articles before actually publishing them, but in the rest of cases there is no evidence to prove that the referee process of the paper is over and the journal has accepted the paper for publication. Also assume preprints of my papers are available in ArXiv. So, my questions are:

How a search committee interprets and evaluates those papers which are just submitted or are claimed to appear?

Does a search committee consider these types of publications less valuable than the published ones (assuming the same quality)?

Does a search committee refer to my preprints in ArXiv to evaluate my submitted or accepted papers?

It's a tiered system:

Peer-reviewed published articles. Published means published in any form, so it includes papers in all states published online on the journal's website, including “in print”, “ASAP papers”, “just accepted papers”, etc.

That's top notch: it demonstrates your ability to perform research, write it up and publish it. Those are key requirements for the job.

1b. Peer-reviewed accepted papers. All search committees I know will assume good faith, and accepted papers not yet published (thus without proof) are considered as good as published papers. If you want to (and the application format allows for it), you can actually join a copy of the manuscript (not as proof, but for committee members who may want to read your paper to judge its quality).
Submitted papers, non peer-reviewed papers. This has some value, as an indication of your recent activity. It is especially useful to the committee if you have few papers (junior researcher) or have not published much recently (so that it is clear you are still active). Again, you may want to join manuscript(s) to your application, or give a link to arXiv if you deposited it there.
In preparation, in writing, … There is no clear standard on threshold for what is a paper “in preparation”, so these are usually worthless on a CV. The only exception is if you have very very few (or no) published papers: applying for a PhD position, or early application for post-doc position, with 1 or 2 published papers. Otherwise, my advice is simply not to mention manuscripts you have not finished writing.


First sentence of a research proposal I am writing a research proposal and I can not choose the right very first sentence to start the introduction. My research is purely theoretical.
Let's assume I want to study a mathematical model of dynamics of wolfpacks distribution in last 100 years in country C.
There is a separate section for objectives so I would not start from aims.

What would you write to start?

I have several ideas but neither of them looks totally convincing for me.

Wolves are very important
Wolfpacks distribution is very important
Wolfpacks distribution dynamics is very important
Analysis of ecological data is important
In recent years study of wolves/wolfspack distribution/wolfpacks distribution dynamics has received much attention
Many problems of something are related to wolfpacks distribution dynamics
Mathematical modelling of ecological processes has been proved to be useful in analysis of many things over years.

If I were writing a paper I would not care much about it but here people say, that the first words are of particular important and I don't want loose points.

EDIT: As question got popular and everybody wants to correct my orthographic error in "wolfs", I correct it myself.

The first paragraph of any paper or proposal is always the hardest for me to write, and the first sentence is the hardest part of that paragraph.  In my experience, no matter what I write, it sounds hackneyed; fortunately, the same is true of everybody else's first sentences, including all of the sentences you and other other answers have suggested.  I used to spend days agonizing over the precise choice of words in each opening sentence.

So a few years ago, I adopted the following strategy, which works surprisingly well:

Typeset the phrase INSERT FIRST GRAF HERE in bold red 18-point text at the top of the first page of your proposal.  Promise yourself that you will write this paragraph only at the very end, after you've written and polished everything else.
Start writing the second paragraph, which explains in broad strokes the substance of your proposed research.  Assume that the first paragraph has already explained how novel/important/cool the research area is.
Make sure your introduction includes a few paragraphs describing specific prior work and its impact, as well as the specific work you are proposing and its potential impact.  Keep it high-level; this is just the elevator pitch.  You'll include a more detailed description of both of these points later.
When you are completely finished writing and polishing the rest of the proposal, delete the phrase INSERT FIRST GRAF HERE from the top of the first page and submit the proposal.

Yes, I really have done this, multiple times; and yes, the resulting proposals were funded.

To put it more bluntly: Just get to the point.


Are you supposed to disclose all stimuli that your participants have been exposed to? I am a master student in psychology in the US.
I performed a study in which the participants had to read a story and should recall it afterwards.

Now I am writing a manuscript where I only analyze parts of the participants’ responses to answer my research questions.
This puts me in a dilemma: Should I explain the whole story stimulus in my paper or just focus on the parts that I analyzed?

My supervisor suggested that I should not mention the unanalyzed parts of the story at all because that will distract readers and take away the focus of the paper. However, I'm thinking what if this paper is published and someone ask for the stimuli to replicate the study, and then find out that the stimuli is different from the way I presented in the paper. It’s like I’m hiding something from them. I worry this may lead to a retraction of the my publication. I’m very new to academia and my supervisor sometimes is not very on top of things, I don't think he cares much about what I do. So I want to make sure I do the right thing and ask for your advice.

Psychology is not my field, but your concerns seem valid to me. As a reader of your work I'd want a fairly complete picture of the experiment that was done.

However, you don't need to discuss everything at the same level of detail. A synopsis of the parts you don't focus on is likely enough to satisfy your concerns without distracting readers from what may be more important to your purpose.

In other words, the overall description can be broad, but not deep. Then focus on what you want to say. Arguably, the fuller description could come in an appendix/annex to the paper. Or if a fuller description of the experiment has been published you could just cite that.

If I think that the "unexplained" parts are more important to the outcome then I, at least, have a basis for discussion, rather than having just been misled.

But, again, this is advice from an outsider.


How to address a class about cheating An undergraduate course that I teach has roughly 50 first-year students, and without trying I noticed several egregious examples of cheating, both on assignments and on a recent midterm exam.  Given that the students have only very recently entered university -- they occasionally behave as if they were still in high school -- I'd like to have a discussion with them about academic integrity and cheating.

Has anyone else here had such a conversation with a class of theirs, and would be willing to share some advice?  If the above-referenced incidents had been referred to a university committee on the matter, the students would almost certainly fail the course, or perhaps suspended.  The department, however, gives the faculty some flexibility in deciding whether to refer particular cases to this committee.

Please carefully read your school’s policies concerning academic dishonesty before you do anything.  Follow those rules carefully so that the students won’t be able to get away with their cheating on appeal.  For example, at my school you’re expected to talk directly with the student to give them a chance to defend themself before you decide on a punishment, and you’re required to submit an official report which allows the school to decide on any larger sanctions.

I’d also recommend having a third party (e.g. course coordinator, director of undergrad studies, or TA) present for the conversation.  This makes it clear that it’s serious, makes me feel safer, and prevents the student from lying about the meeting.


Revision letter and grammatical errors I got a major revision and I will prepare a revision letter. The editor asked me to review my manuscript for grammatical errors, in addition to the scientific comments he made. Should I present all the grammatical changes I made on the manuscript one by one? There are lots of minor changes (i.e addition/insertion of commas, "the", "a/an").

Since they haven't pointed out what mistakes you have, it is unlikely they have a list of errors they have found; therefore, enumerating your changes is pointless. Also, since you got "major revision", a good chunk of your text should be changed anyway.

Just make sure you double check the language before resubmitting, preferably by someone else (native speaker would be ideal).


Can more than one person share PhD thesis? I have a PhD research proposal and I came up with this proposal idea while discussing machine learning with my brother who is in the same field as me and has same degrees as me.

my question is can we (my brother and I) submit this proposal for the university so we both share the research?

do we have to provide 2 seperate research thesis?

my question is can we (my brother and I) submit this proposal for the university so we both share the research?

Yes, assuming the university and supervisors don't object.

  do we have to provide 2 seperate research thesis?

Yes (in general). You can work together throughout, but, ultimately, both of you need to uniquely identify your individual contributions. I'd suggest that one of you takes the lead on each work package and that work package is considered their individual contribution, whilst the other provides support. Resulting publications will list both of you, but such publications will only appear in one thesis. (There's some flexibility here, since you might both include material from some publication. Your supervisors can help you work that out.)


Changing field from Computer Science to Philosophy I am a Computer Science graduate and I have been realising that my true passion lies in Philosophy, as for the past 5 or 6 years (I am 26) I have been constantly asking questions about life, conciousness, the universe and the relationship between them. I am also in the process of writing a book which can be considered as Philosophical, although I am not yet quite sure whether it will be Philosophical Fiction or Non Fiction.

My question is, is it possible to continue as a graduate and start a Masters or Doctorate in Philosophy? Since I would like to become a professor so I can help others pursuing answers to such questions. As already mentioned, I would also like to start writing unfortunately, in our current era, it is very difficult to be taken seriously if you do not have academic background on that field.

From what I am reading, this might not be possible since Philosophy is an ancient field and hence there is the usual sequence of degree, masters and PhD. For instance, some new fields, such as neuroscience do not have any directly related degrees and hence you can transition to them from other fields.

If this is not possible, will I be taken seriously if I transform my book into a paper (assuming it is actually a good book) and be allowed to start a PhD without any previous academic philosophical background? My current targets are either Oxford University or UCL.

Looking forward for your response.

Since you're interested in life and consciousness, you might want to explore cognitive science (including artificial life), which draws from philosophy, artificial intelligence, neurology, and other fields. Your computer science background could help you enter a program like this, and once in, you could take philosophy courses to strengthen your background in that area. Perhaps you could do an MSc in cognitive science, and then you might have the background to enter a PhD program in philosophy.


How to select which conferences I should attend? I am in my first semester of a computer engineering PhD in the USA. At my University during your first year they will pay for your expenses to attend, up to $1000.00, for a conference. Every year after that they will pay your expenses if you get a paper accepted.

I am wondering how others look at/find conferences that they feel are worth the monetary and time commitment for what they provide. My areas of interest are embedded systems, computer architecture, and security. I have found many conferences but am unsure of how I should vet the quality of these.

What criteria do others use when looking at conferences and judging their relevance to the area they address?
What opinion or otherwise do people have of academic conferences vs industry type conferences vs enthusiast type conferences?

There are many different types of conferences and many different reasons to go to a particular conference.  The most relevant that I would say for your situation are:

Flagship conferences that everybody in a field goes to because that's where everybody goes, and where research presented will get the greatest audience.
Niche conferences and workshops that serve some particular smaller interest group.  They are less prestigious, but are where the communities they serve have a lot of key interactions and get a lot of actual intellectual work done.
Crap conferences that would like to fool you into believing that they are one of the first two.

Some good tactics for judging the quality of a conference:

Where do the people whose work you respect (particularly your advisor) publish and attend?
Where are the organizers and program committee members from?  Are many of them from high-profile research institutions?
Google Scholar metrics

Given your early stage and breadth of interests, I would recommend going to one of the broad flagship conferences, where you can hear about lots of things from lots of different types of researchers and organizations.  Those conferences often have a lot of industry attendance as well.  I don't know your specific field too well, but even from outside I know that USENIX is a large conference with a strong reputation.  Still, use the heuristics I suggest and see if it's really the one you want...


How to automatically extract submitted/accepted dates of many journal papers? I am doing a research of the processing times of papers published in journals in my field. I have noticed that the metrics that the journals advertise (e.g. the Elsevier journal insights) do not correspond to my experience, nor to the recently published papers, so I wanted to make my own survey. (My guess is that they take into account papers which are immediately rejected by the editor without being sent to a review, so the average looks quite favourable. I am more interested in the average time of the papers which are actually accepted.)

I plan to cover all recently (last 12 months) published papers in 10-20 journals of different publishers (e.g. Elsevier, T&F, Wiley), which will result in hundreds of papers. Basically, I will take the date when the paper was submitted, accepted, and published online, and calculate the average per journal.

Is there a way to automatically extract this information?

Have you checked this data is actually made available for your preferred journals? IME not all make their accepted/submitted/first-online dates very easily accessible, though it has improved a bit recently.

If it's there, your best bet is probably to screenscrape the HTML. Some journals provide nice clean XML to play with, but this is usually new online-only titles rather than legacy ones from traditional publishers.

Elsevier use a simple HTML tag (class="articleDates") which contains the core dates -

Received 23 March 2015, Revised 15 May 2015, Accepted 18 May 2015, Available online 9 June 2015

Taylor & Francis have similar information to Elsevier: the element you'd need is again "articleDates", but it unfortunately has a lot of linebreaks in it for no good reason!

Finally, Wiley don't seem to expose submitted/accepted dates (at least not for all journals); "publicationHistoryDetails" just gives first-online, which isn't much help.


Variation in drop dates, and effect on student outcomes (This question may be specific to US university systems.  Also, sorry it is long.)

US universities usually have some provision for students to drop a course.  Within the first N weeks of the term, if they decide they don't want to continue with a course they are taking, they can drop out of it.  Their official transcript will show no record that they ever took it, and it will have no effect on their GPA.  If they are paying tuition per course or per credit, they may get a refund.  Usually they have to stay enrolled in some minimum number of courses, so this can probably only be done for one or two courses per term.

Students may have many reasons for dropping a course, but obviously one common reason is that they are not doing well in the course and are afraid they may fail it.

(There may be another option to withdraw from the course up to N+K weeks, but with a note on the transcript saying that they enrolled in the course and later withdrew, maybe listing the pseudo-grade of "W".  This usually doesn't affect their GPA but may look bad to prospective employers, graduate schools, etc.)

I realized the other day that there is very wide variation between institutions in the value of N.  At Institution A, the medium-sized public university where I currently work, we have N=2.  At Institution B, the small private college where I got my bachelor's degree, we had N=11!  (I had vaguely remembered that N seemed to be larger at B, but I was still startled when I looked back at an old B calendar to check.)

(One significant difference: at A, students very often pay by the credit, and get a refund if they drop, so the university has a financial disincentive to let them go.  At B, most students paid a flat tuition fee per semester, and didn't get any refund if they dropped a course.)

Anyway, it seems like this could have a rather profound effect on student outcomes.  When N is small, students have only a short time to commit to their schedule, and can more easily get in over their heads.  By the time they've had a midterm exam and realized they are in trouble, N weeks have already passed and they are stuck in a course.  Most likely, they end up with an F (or several, if the time they spent trying to pass the hard course hurts their work in their other classes).  Their GPA drops, hurting their eventual job prospects.  It may drop below the institution's minimum for continued enrollment, in which case they may quit college altogether.  I'd expect an overall negative effect on retention and graduation rates, job placement, and other common measures.

On the other hand, if N is large, then by the time the drop date approaches, students may be more than halfway through the course, and may have taken several exams.  If they are likely to fail the course, they probably know it by now, and the obvious course of action is to drop it.  In an extreme case, the result may be that students hardly ever get D's and F's (because they drop those courses), and grades may inflate.

So I have two questions:

What factors do universities actually consider in choosing or changing their value of N?
Is there any research studying the effect of N on student outcomes?

I'm not personally aware of formal studies on the subject, but at my undergraduate institution there was a carefully thought policy that seemed to work fairly well.  They had not one, but two different drop dates for classes, with different intentions:

The first drop date, ~5 weeks in, left no record at all, and was intended to allow "class shopping" and academic risk taking. This made registration a low-stakes decision. A student unsure whether they could handle a hard class or undecided between two classes could simply sign up, try things out, and then make a decision after a couple of weeks, before investing too much.
The second drop date, ~12 weeks in, left a record on the internal transcript, and was intended to allow a failing student to triage and focus on their remaining classes.  It still didn't show up on external transcripts (except as a light-load semester).

With these two dates as long-standing and well-accepted policies, professors tended to include them in their planning.  Most of the early "shopping" drops happened in the first week, so professors tended to wait until the second week before doing things like arranging tutorial sections or setting presentation schedules.

Similarly, grading policies mostly tended to assume that D, F, and late drops were synonymous.  Thus, many classes set their first quiz before the first drop date, to let students have their first serious assessment of their progress before that decision deadline.  Likewise, curves were often set to assume the worst grades would have gone to the students who dropped, meaning that students who stuck out the class were not unfairly penalized (though they could still fail if they did that badly).

These policies I'm sure do create some statistical GPA inflation, but I doubt it has much significance because 1) it would not generally affect the stronger students, and 2) significant failures are still visible as gaps on a transcript.


Should I be concerned when an editor tells me that I have the final say about the paper he sent me to referee? I have been asked to referee a paper for a middle-tier physical science journal.  I have reviewed for this journal many times before, although it was several years since I had gotten a paper sent to me by this particular editor.  (I thought that this editor disliked me, since I was fairly critical of one of his own research papers.)  However, some weeks ago, he sent me a paper to referee, and I sent promptly sent back a report.

The peculiarity came the second time that I was sent a draft of this paper.  After the first round, I asked for some significant clarifications, since the work being described in the manuscript seemed to have been done properly, but the justification was very poorly explained.  The editor was not able to find another scientist to provide a second report, so the revisions were based solely on my comments.  The authors made some changes, which I have not combed through that carefully yet, but they are probably satisfactory.

However, this editor told me explicitly in the letter he sent me that he will definitely accept or reject the paper, according to whatever "verdict" I return.  This makes me a little uncomfortable.  On the one hand, I am honored that he trusts my judgement sufficiently to put the entire decision effectively in my hands.  On the other hand, I feel a nagging concern that the editor is, to some extent, shirking his own responsibilities in this case.  Not that I would ever really expect him to go against my recommendation, but I am sort of uncomfortable with the level of responsibility that he has implicitly placed on me.

As a general rule, the way this editor works is somewhat idiosyncratic.
 For example, the journal has an online system for submission and refereeing, but its use is apparently optional for the editors.  Every other editor I have worked with on this journal has used the Web-based system for assigning and collecting reviews, but this guy does everything entirely via e-mail.  His e-mails can be rambling and mix personal and professional communication, quite different from most e-mails I get from journals, which are almost all boilerplate.

So I guess my question has two aspects:  First, is it reasonable to be concerned about what the editor has said?  Second, is there anything I can (or should) do about it?

What you could do is locate a second reviewer, say a colleague, yourself. Explain the situation and the paper (in general terms) and ask if they could give a review. Then write to the editor

  I found that the authors addressed most of my concerns. However, there are still a few points I am unsure of and would like a second opinion on. I have spoken to Researcher B (without disclosing the paper) and he/she is willing to give me some input. May I share the paper with him/her?

Even for mid-tier journals, a single reviewer isn't unheard of, especially when the topic is specialized and as you have said you are an authority on the topic. What usually happens is that the editor doesn't tell you about their plans.


Is it common to contractually require that a professor works with other faculty members in their department? My adjunct contract states that I have to work with other professors and share information with them about the work. While I'd love doing that, I find it bizarre that it is part of my contract. This is particularly concerning to me since the head of the department has been pushing me to work with/learn from a certain faculty member whose teaching methods and approach are radically different from mine. I don't want to be "forced" to meet and chat with people just because the department's head thinks it would be good for me.
What would you do in a situation like this? Thank you!

You should learn from other faculty about their teaching methods.  In most cases, you should follow their advice.  Consider it an experiment.  If there is unambiguous evidence their advice is not effective, don't follow it.
Your alternative is to decline the contract.  If you are unwilling to try new teaching methods, I recommend taking that alternative.


Why are tenure-track professors hired on the basis of their research when they spend most of their time teaching? I was just looking at a different post that cites National Center for Educational Statistics about how professors of all levels spend their time. I am actually doing some research on faculty hiring practices at research universities.

How much time do professors have to do research on their own?

The thrust of the data is that most professors, whether tenure track or non-tenure track spend more than 50% of their time on teaching. I imagine this data is averaged across both research and teaching universities, but still teaching must make up the bulk of time or even professors at research universities--whether that be teaching classes, mentoring grad students, committees, etc.

But at the same time, I know that the hiring criteria for the research universities focuses on publication records with little if any concern about teaching evaluations and such. I am not trying to make a critique or political point, this is just something that I have understood from my interactions with professors and other graduate students.

Now my assumption is that most research university departments get the majority of their money from student tuition. I might be wrong about this, and if I am wrong please let me know. We also know that the ability to do research does not always correlate with teaching ability.

So I want to understand the mechanisms that allow research universities to continue to hire professors who are not necessarily the best teachers? Of course, there are many amazing professors at universities who are excellent teachers. I am not trying to make a blanket statement by any means. I just mean that you would probably get better teachers if the primary hiring criteria was teaching ability, right.

By mechanisms I mean, if student tuition is the main source of money, then why do students keep paying for classes taught by not always the best teachers? Or is there just so much money coming into research universities from grants, etc., that they can afford these large professor salaries despite the loss of undergraduate students? Like how does this actually work?

I imagine part of the answer to this question is associated with the growth in non-tenure-track faculty like adjuncts. That seems like it would solve some problems. But still why can universities who seem to get most of their money from students, get away with paying so little attention to students when it comes to hiring faculty?

Any insights are welcome. Again, if I phrased anything indelicately, please forgive me. I was not trying to cast any aspersions on anyone. Just purely thinking from an economic rationale.

Because they don't spend most of their time teaching.  For example, officially the expectation is that I spend half my time on research, a third on teaching, and a sixth on service (e.g. administrative responsibilities).


Doing a research paper / poster without much available data? I know, why would somebody choose a topic for a research paper or a poster that doesn't really have much data or literature available? But here it goes...

Without much consideration, I chose a topic for a presentation at a Geographu scientific conference that doesn't have a lot of digitised data available. When I think of it, there are no existing databases on which a digital / computer approaches and methodologies could be applied.

My question is, how do you manage this kind of situation? Do you just write a theoretical paper that just gives similar case studies from other geographic regions where this methods were applied, or?

Also, I think it is now a bit late to change topics.

The fact that there isn't much data available sounds like a fantastic opportunity to collect lots of data in that field, setting yourself apart from other folk and carving out a nice niche for yourself.

The fact that there isn't much data available in the field shouldn't hold you back from just doing it yourself. Science is the pursuit of knowledge, after all.


Conference first or paper first? I am currently figuring out what would be better to do: would it be better to select one or multiple conferences first and then write for these conferences (if their topics match your topic(s) of interest)? Or would it be better to write and once completed writing, see which conferences do match your paper? What would you do? What would be your advice?
Thanks in advance!

What field? What's typical in your area? Ask your advisor.
When I was a student, in my area, computational fluid dynamics using the finite element method, things tended to go:

talk or poster (with no paper/abstract only minisymposium)
journal paper or invited paper to conference proceedings

unless it had been a while since we'd been to a relevant conference, and then we'd take a recent paper and make a talk or poster out of it to give at an upcoming conference with some added results if we had them or could make them in time. But, that may have just been my advisor's preferred manor of working. Doing that, we wrote a few papers and did a lots of talks and posters in the time I was in my PhD program. Sometimes we'd do a paper for a conference that required a full paper (e.g., the AIAA annual meeting) and have to wait much longer on acceptance than something that was reviewed only on abstracts or extended abstracts.


What material should I bring to my first meeting/interview with my prospective advisor? During a very brief email exchange, a professor of my university (mathematician) said that he is available to take on a masters student at the moment and gave me an appointment during his office hours.

Roughly in the same spirit as the question How much detail to include in first email to potential PhD supervisor?, I'd like to ask

  What kind of "support material" should I bring to this "interview" to make sure the professor collects a sufficient (and sufficiently well-organized) amount of information?

I mean, in addition to the basics, which are

a copy of my CV;
a copy of my trascript;
a concise summary of my mathematical background that is relevant to the (possible) thesis topic with precise references to courses, workshops, conferences, summer schools, and the books or papers I've read.

It looks like you're set with respect to material things. What I would encourage you to prepare is an agenda -- which, in this case, means a set of immediately practical questions you need answers to, and one or two conversation-starters regarding your would-be advisor's research and that of his existing advisees.

Practical questions: what paperwork is involved in formalizing the arrangement, when should you report to start work, that sort of thing.

Conversation starters: "I read your recent 'Mathematical Models of Baskets' in the Journal of Underwater Basketweaving; are you still working on that?" "What are your current students working on, and is there anything you wish somebody would tackle?" and that sort of thing.


Are 'please cite my paper' emails socially accepted? I am a PhD student in physics. A few months ago, I submitted a paper (which has meanwhile been accepted, but not yet published). The preprint is on arXiv.

Now, I saw that a few days ago, another manuscript, from a different group, has appeared on the arXiv, and I think there are large parallels. It's not that my work would dramatically alter the interpretation of their conclusions, but I think it would have been appropriate to link the works.

They also have a very broad 'catchy' title on their paper to make it sound spectacular and it seems to me that this title also relates to my work.

I'm not really suspecting conscious malice from the authors or so. But I wonder if I should send one of the authors a link to my paper, or if this is frowned upon.

Emailing them could be acceptable -- and I would even say it should be encouraged! -- but you have to tread very carefully. If you write an email like

  Hey Dr. Jones,

  I saw your newest paper on arXiv and I noticed you didn't cite [Wouter et al, 2020], do you think you can post an update and cite me?

  Wouter

this would come across very poorly, and in general the above email would be socially unacceptable.

Instead, you could follow the following steps:

Read the paper carefully to find how it relates. It is likely that you, as an author of the other paper, are overestimating the overlap. There still may be some important overlaps, and reading it carefully will allow you to narrow down on the precise similarities.

For example, you mentioned that their broad and 'catchy' title overlaps with your paper, but if the actual material does not overlap, then the overlap in the title is probably superficial and doesn't require a citation here.
Once you understand the scope of the overlap, consider how many papers there are in this topic. Is this a topic with dozens of papers every year, in both high-quality venues and low-quality venues or arXiv? Or are both of your papers the only ones even addressing this topic? In the former case, I would expect that citing you is wrong (they should instead cite one of the more classic or well-known examples in the literature); in the latter case, I think they should cite you (although given that they didn't, they probably aren't aware of your paper).

At this point there are two cases: either you have determined that there is overlap and they should consider citing you, or you have determined that it's probably fine that they didn't cite you. If you still think they should cite you, then you can proceed to the next steps:

See if your advisor or a senior colleague knows this group, and can email them instead. It would be far better to get an email from someone they know about this, rather than some PhD student they haven't heard of.
Finally, as a last resort, write the email yourself. But keep the email professional and careful.

Don't say that they should cite you; do say they might be interested in your recent work.
Do assume that the work was done completely in parallel (it probably was).
Don't overstate the overlap or relevance of your work.
Don't assert that they have an obligation to be aware of your work; the literature is usually extremely vast, and it is hard to keep up with everything, especially arXiv papers with 0 citations posted a few months ago.
If there is another paper, other than yours, that is more representative of the line of work that your paper represents, which they didn't cite, suggest that work instead. And maybe in that case, don't mention your paper at all.
Above all, focus on your interest in their work; state that you saw their work and found it interesting; you can even ask questions, see if they have tried method X or considered question Y. Best case scenario, this could be an opportunity for future collaboration (or you could be a postdoc in the group later, etc.)

I think if you follow the above steps and guidelines, the email should be OK. And if they really should cite you, hopefully this diplomatic approach will cause them to do the right thing (the scientifically honest thing) by citing you.

If you decide not to write an email, then what you can do instead is cite their work in the future. Or meet them at a conference. These are more organic ways for awareness across research groups to develop.


Is it legal to add your publications to ResearchGate? I recently created a profile on ResearchGate. And to add your publications list it requires you to upload the paper. Is it legal to upload published journal articles on public servers, where everyone can download it for free?

Is it legal to upload published journal articles on public servers, where everyone can download it for free?

It depends on the publishing agreement you signed, which should specify which rights the authors and the publisher hold.  The allocation of rights depends on the journal (and the field you are working in), and sometimes there are modifications or addenda for a specific paper.

You should keep copies of the publishing agreements for your papers, precisely so you can refer to them at times like this.  If you don't have them, you can get an approximation by looking on the journal's website to see what their current policies are.  The policies could have changed over time (and in principle the publisher could still enforce a stricter policy you agreed to in the past), but it's probably safe to post a paper online if the publisher allows it as part of the current publishing agreement.  If you're feeling nervous, you could always ask the publisher whether you could follow the terms of the current publishing agreement for your paper that was published long ago.


CS graduate admissions for masters level For people applying from unknown schools where one's senior has never hit that department before, what is the evaluation metric for graduate admissions ? Probably all schools are not equal, but what if the applicant's school is unknown or a newly established one without a reputed faculty who are unknown to the researchers in the field.

How do you judge if the candidate is good enough ? What is the value of GRE Subject Test especially in these situations ? How does top 10 programs approach such candiates, do they spot reject them ?

My question is about MS level admissions, please answer considering that fact.

Most schools are unknown schools; there are just too many for the admissions committee members to have an idea of the quality of all of them.

So the standard approach is to de-emphasize the GPA and make the decision based more strongly upon the other parts of the application.  If the GPA would be troubling if it were from a good school, then it's still troubling; otherwise, it's more of a threshold ("Well, that's good enough--let's look at the rest of the application.").

(This is generic advice for all academic fields; there's nothing special about CS in this regard.)


I wrote the code based on a paper's methodology; are there any legal problems with making it open source? I coded the methodology based on the paper "Free Water Elimination and Mapping from Diffusion MRI" and I am curious if I am legally bound to take permission from the authors or the journal in making the code open source on Github?

You are not required to get permission to implement an idea you have read about in a paper, or to make it open source.

The paper is protected by copyright, but this only protects the text and images in the paper (the expression of the idea), not the idea itself. The copyright on the paper does not prevent you from creating your own realization of the idea in code and distributing it freely. You should also acknowledge the source of the idea by citing the paper in which you read about it, but this is an ethical requirement, not a legal one.

The exception to this is if the methodology in the paper is patented; in this case additional restrictions on what you can do will apply.


Change of interest right before qualifying exam I'm a first-year pure math PhD student. I'm going to take an oral qualifying exam in a few months, and for this I need to find at least one person who agrees to be my adviser and one of the examiners in the qual. I'm interested in symplectic topology, and I have already talked with a professor of this area, whom I was going to ask for being my adviser. However, my interest in machine learning got revived, and I'm now very certain that I want to change my path.

Reapplying to CS PhD isn't really a good choice for me, since I didn't take any CS course in undergrad. However, I have studied this area by myself, and the process was very easy compared with studying pure math. I've audited topics courses in ML, from which I believe I don't have any lack of prerequisite for this subject, and that I'm ready for research once I finish reading relevant papers.

I'm aware that, once passing qual, I have freedom of changing the area to pursue. For example, a pure math PhD student having done a qual on symplectic topology can get a PhD by writing a thesis on computational complexity. While qual is not difficult for me, I have no idea how to actually proceed from now on. Should I tell the professor that I want to take the qual with him as my adviser and that I will not work on symplectic topology after that? (After that, I will find a co-adviser from CS department with whom I will work on thesis.) Or should I not tell him my intention until after the qual?

Given that you're in the US, my advice to you is slow down.  You don't need to pass your oral exams in your first year, and studying for and passing an exam in a subject that you intend to drop completely is not a good use of your (or anyone's) time.  Moreover, you can stop working with (or not start working with) your advisor without jeopardizing your future in the program, so there is absolutely no reason not to be forthcoming about your concerns.

I suggest talking to your current faculty advisor and devising a program of study which allows you to explore ML while not quitting symplectic topology "cold turkey".  As a first year student you can afford to spend at least a year taking courses trying to figure out what you want to study and building up background in that area.  In fact, it is very unusual for a first year US math PhD student to know exactly what they want to study in the future: that kind of decision usually lies at least a year away.

It sounds like you thought you did and that you have some pride in your own advanced standing.  That's understandable, but the thought of going ahead with an examination in a subject that you plan to drop soon thereafter and with an advisor that you plan to drop immediately thereafter is really not a rational, wise or kind way to proceed.  I think you need to take some time to gain a better perspective.  Sharing your proclivities and your plans with your peers and mentors is a good way to do so, but again: take it slow.


Does authorship matter when applying for academic jobs? In some fields, authors have equal weight on a paper, but in my field (mechanical engineering) people care where their name appears. However, I am not sure how much the authorship is important when applying for an academic job. When reviewing the list of publications, do people check the authorship too?

Does it matter that I am first author or corresponding author? Or just they consider that I have publications in high impact journals?

Does sole authorship have a higher credit? In co-authorship, I have contributed a part of the research (maybe trivial). As a sole author, I have proven that I can handle any part of that work. Or hiring people prefer teamwork?

While obviously this can be very specific, not just in disciplines of engineering, but also perhaps to individual departments and groups of different institutions with different focuses, I'll try to give a somewhat general answer.

First authorship is definitely important - it generally shows you "did the work". An important consideration for a hiring committee is how well your research direction fits into their focus. Your first author publications show "your" own work, and that you can do research. Generally these would be impressive and in high ranking publications, to show impact and recognition from other researchers.

Your "non first author" papers are either from collaborations with other researchers, or from supervision. Having good collaborations (perhaps with other institutions) shows a good ability to interact with colleagues and others in the field, which means you can likely attract funding. An important part of an academic job is to attract funding. Collaborating with others shows that others were (presumably) prepared to work with you, and there were results.

As a supervisor though, the quality of your students' output is also important. At least in my experience of engineering, the nearer the end your name is, often the more senior you are. For the avoidance of doubt, I am not referring to the addition of senior grant holders who had no input - let's presume we have 3 or 4 authors on a paper. The first one may be a PhD student. The second might be a collaborating PhD student. The third may be a RA or more senior PhD student, who helps the fourth (the supervisor) with supervision and advising students.

To give an anecdotal example (also in engineering), I started off writing papers with only myself and advisor as authors. After a few months, I found myself helping out some new-start students, and helped them get their own first publications. I ended up as second (of a few) authors. This continued and other students would approach for help and advice, and I'd be happy to assist them. As this happened more, I obviously have less active input in the specifics of the work, more helping to plan the research, and helping to confirm findings and challenge their own interpretation of the results. This pushes you down the author list towards the supervisor position.

I suggest that you want a healthy balance of work - good, high impact first-author papers to show your skills and expertise and research ability, combined with collaboration work, showing work with colleagues at other universities, as well as in skillful supervision and mentoring of your (or someone else's) students. All these things are considered in my department, and the potential to obtain research funding (and produce good quality PhD graduates) are both seen as very important. Having no real first author publications has given people problems before, as has having no collaborations or supervisory-capacity publications.

To address sole authorship: In engineering, I find (at least in my field) that sole authorship is uncommon, and have not seen it regarded differently than first authorship on a paper with several authors. As an academic you form part of a group and it is expected you'll work individually as well as part of a team. Therefore sole author doesn't seem to be treated differently to first author.


How to cite in APA format for an author who uses only a first name? How do I cite in APA format for an author who uses only a first name?

When there is only one name, simply use that name.

The guiding principal of citation is to give a clear and unambiguous pointer for finding the work in question and related works.  Thus, when dealing with a mononym, the general APA dictum of "author's last name" (which is quite culturally narrow in any case) maps cleanly to "author's only name."

Examples can easily be found for famous ancient authors such as Plato, e.g.:

  Plato. (1961). Meno (R. S. Bluck, Trans.). Cambridge, England: Cambridge University Press. (Original work published ca. 380 B.C.)

The same principles can be applied for modern mononymous authors.


Secondary Research Questions in a Master Thesis, where to answer? My question concerns the placement of secondary research questions (SRQ) within a Master Thesis for a Software Engineering program.

Currently I describe my primary research question in a chapter on the Methodology of my Thesis. In the same chapter I describe 6 SRQs as auxiliary questions.

In the next chapter I describe my Experimental Design, and I answer 4 of the SRQs as they relate to the design and how it can properly test my hypothesis.

However, my supervisor suggested I cut the amount of SRQs to < 5 and that I answer the SRQs in my Introduction. I find that to be an odd place for SRQs since I would have to describe and answer them in the first chapter of my Thesis.

To be fair, the first 4 questions concern the Software framework to use, which dependent variables should be measured, which independent variables should be manipulated and how to guarantee reproducibility of the experiments (this is a big issue in Software Engineering and particularly for my subject). So I understand his issue with the questions. However, I feel that answering them in the chapter concerning my Experimental Design is actually quite fair and avoids a cluttered introduction.

Here is my current structure:

Introduction <- Supervisor suggests describing and answering 4 SRQs here, or to remove them
Use-case
Related Work
Methodology <- Currently describing PRQ and SRQs here
Experimental Design <- Answering 4 SRQs here
Results
Conclusion <- Answering PRQ and 2 SRQs here

I tried finding some literature on SRQs but I couldn't find anything on their placement, only what type of question they should be.

Any suggestions are appreciated.

I agree with your supervisor about the positions for the questions: Those should be in chapter 1. Answering the question about the position of the other questions is difficult because we now neither your work nor the questions.

But the answer in chapter 1 as well seems to be odd - I would assume that those could be a result of a state-of-the-art analysis (in your case chapter 3) or of the "Results".

But maybe those questions are not really research questions but sub-tasks you have to do in order to achieve your goal. Then the "Methodology"-chapter would be appropriate, but I would not list them as SRQs but as "tasks".

In the end, readability should be considered, too.

Finally, your advisor is grading you - and if (s)he strongly suggests one option, I would follow the suggestion. But I would show my "optimal" solution, first.


Unsure whether to continue maintaining research account on Facebook re Cambridge Analytica I maintain a Facebook account purely for research purposes. I have about 30 or so friends on my account. I have always disagreed with FB and its ethics, however, recently, in the light of the CA scandal I have found myself increasingly questioning my use of the site.

The benefits that FB provide to the researcher of virtual communities are undoubtedly strong. Much of my master's research focused on virtual communities in Iraq and Syria, and much of this would have been impossible without FB. However now I am considering deleting my account in the wake of these - unsurprising - revelations.

As a PhD student, the benefits of being part of an online social community are notable. As a Linux user and a supporter of Free and Open Source Software I also have to wrestle with the occasional difficulties of trying to get software to work which Windows or Macs users would breeze through with ease, but I am happy to do so because of my support for free software and the additional learning/skills I inherit.

Maintaining an ethical standard re software and software companies becomes increasingly difficult in the modern climate. Does one just put one's ethical beliefs on the back burner in the interests of research and should one be perpetually plagued with the decisions one has made to maintain a FB account in spite of disagreeing strongly with the company? Or does one delete one's account and potentially miss out on the great research opportunities it provides?

You are facing a moral dilemma that only you can answer. We all are facing a similar dilemma:

  Do my professional activities contribute to the wealth of un-ethical companies?

That company may be Facebook, a publisher, a software company, a private group, etc.
Most of the people I know will think

  If I don't have the choice, I will go with it but keep an eye open for the alternatives, and make sure the people I work with are aware of that dilemma.

I use C# and Visual Studio in my teaching, despite not really liking Microsoft: I roll with it, but make sure my students know of the alternatives, and bring up the topic regularly with my colleagues, in the hope that we will collectively chose an alternative.

Arguably you can't make that switch on your own: you can't make all the virtual communities in Iraq and Syria switch to Diaspora overnight, but you can create an account on that website as well, encourage people to switch, and keep an eye on both platforms.

As you stated, that recent "scandal" with Facebook didn't create that dilemma: you already knew that your data was used in all sorts of ways. But maybe you can use it to encourage some of your contacts to move to a different platform?

Some people have the opposite approach and put their morals before their career: Alexander Grothendieck is such an example. Quoting Wikipedia:

  Grothendieck's political views were radical and pacifist […]. He retired from scientific life around 1970, after having discovered that the IHÉS was partly funded by the military.


France national research institutes hinder work by banning foreign online services I recently started a postdoc in France. I am not French, do not speak any French yet, and I am new to the culture.

It turns out that all national research institutes in France have a rule against using any foreign online service. All research data and communication must always stay on secure government networks and on French territory.  In practice, this means that services like Skype, Dropbox, Gmail, etc. are banned, and we are sometimes reminded of this through the institute's mailing lists (in French only).  An article mentioning Skype: https://en.wikinews.org/wiki/France_banning_Skype_from_universities

I find that not being able to use such services seriously hinders my work. I cannot talk to collaborators while at work because they all use Skype, and talking from home is not always convenient (time zones, etc.) I cannot have a shared Dropbox folder with them. I cannot use my online backup service (Backblaze). I cannot forward my emails to a central mailbox (Gmail or other) that I will have access to even after I leave this institute.  The institute does not provide easy to use replacements for most of these services.  The ones that it does provide don't work well, are limited, inconvenient and unreliable.

The attitude of my colleagues spans a broad spectrum, from "I don't give a damn" to scolding me for wanting to use these services. The attitude of our PI is ambiguous (they aren't really a computer person).

Our work does not require stricter security than usual (i.e. we don't collect personal information, medical data, etc.)

How would you deal with this situation? Complying with the rules would be a hindrance for my work, and would waste time.  Not complying may be a risk for me.  I am looking for advice from other people who also work in France. I would like to have opinions form people who work in other labs, and also some "cultural advice", as "rule" doesn't mean the same thing in all countries.  Since this seems to be a national rule, others must have encountered the same problem.

First and foremost: their lab, their rules.
As long as they is not illegal, immoral, or unethical, the lab or their funders (i.e., the government) can set standards and requirements that you must follow. If you don't like the rules, you can quit. If they catch you willfully breaking their rules, they can easily fire you for cause So I would be hesitant about circumventing their regulations if you like your job.

Second, their rules might have a rationale. Their country, their courts, their laws. European data privacy regulations are notably very strict. American companies not only operate under a looser regime -- but the companies themselves often have fictitious headquarters or locate their servers in regimes that are even looser about data privacy.  Dropbox and Google have cooperated with US courts and law enforcement to give up client data. Skype used to use clients as p2p supernodes, potentially opening up backdoors (or at minimum, using resources without permission) - this caused many agencies to forbid its use. Even leaving aside court orders and malware,  EU privacy laws are such that having something even as trivial as putting the lab's telephone directory (with personal phone numbers and addresses) on a Dropbox might mean that the data might leave the EU  -- and thus violate EU data privacy restrictions. As long as the data stays in France, it's protected by French courts and French laws.

Third, the rules might be designed to support local industry. Just as I am only permitted to "Fly America" when using USA-government funds, it is perfectly reasonable for the French government to encourage the use of their own national technologies. If enough national lab scientists are pissed off enough about not being able to use an American software tool, they might very well come up with a superior French tool. Or so they hope.

Fourth, see rule #1: their lab, their rules. You are new to the country and to the lab. Ask your other lab members what they do. Try to not be the "ugly American" who assumes that their way is always the best way. See which rules are to be strictly obeyed and which everyone largely ignores. Learn the culture and language.


When should a college graduate attend a professional academic conference? When should an undergraduate attend their first professional academic conference if they have nothing to present and traveling isn't cheap? Would while enrolling for a masters degree be a better time? I'm thinking American Stat Association.

Ask one of your professors who attends the conference about this. Ask what you could gain. If the prof is actually going, maybe they could shepherd you around so that you could meet people.

I don't know about the conference, but see if they have things for students, especially such things as a doctoral symposium where you can hear about student work in progress, even if it is a bit beyond where you are.

Aside from the standard program, conferences are a good way to meet people, though for an undergraduate the first one might not be so valuable unless you have a guide.

But long term, building a circle of like minded people, especially potential collaborators, is a major benefit.


Prevent plagiarism after rejection of a paper? After reading the question What to do if a referee plagiarises the result after rejecting a paper?, I wonder what can be done to prevent this.

I also recently got a conference paper rejected with a good (but not very good) idea. Reviewers gave me 2 × weak accept and 1 × accept and only the meta-reviewer rejected the paper with bogus arguments.

The next conference where I would like to submit is in a few month such that nearly half a year is in between the two submission deadlines of the conferences. I don’t know how may people had access to my work and would like to protect my idea.

I can maybe upload it to arXiv now before submitting it to the conference. Some conferences are fine with this as for example ICML:

  Publication at http://arxiv.org explicitly does not conflict with
  ICML.

but I am afraid that this can become problematic for other conferences.

What else can I do?

I think that this has been covered on this site before.  But briefly:

Most academics (in particular those who have weighted in on the issue on this site) agree that the best way to prevent plagiarism is through more light, not more secrecy.  In other words, once you've shown your work to one other person (and in many academic fields, this will necessarily occur in the course of doing academic work), the more people who know about it -- and the more that people know that people know about it, and so forth -- the less likely it is for your work to be plagiarized.  Thus posting your paper on the arxiv would be an ideal solution (and have many other benefits as well) unless you're working in an academic field which has the practice of regarding, or potentially regarding arxiv submissions as "prior publication".  (If so: have you considered switching to math / physics / TCS instead?  In those fields we not only do not feel that way, we regard the whole notion that freely showing your work to others counts as "publication" as being infinitely lame and wrong-headed.)
Even if you can't or don't want to upload a public copy of your work, you have already done plenty to establish your priority.  Namely you submitted it to a conference and got three referee reports.  You should certainly keep these reports for your records along with the correspondence with the handling editors.  If later on someone tries to steal your work, all you have to do is produce this correspondence.  You should also be able to count on the conference editors / organizers for help: whether the paper is accepted or not, if a conference submission results in someone's work being stolen, the organizers of the conference have an ethical obligation and a professional stake to be actively involved in your pursuit for academic justice.


Giving students a complete set of study resources This is a hypothetical question, as I am not currently in a teaching position :)

I am currently making flash cards for Japanese on Quizlet, a flash card service (website & app). The flash cards are for vocabulary, grammar, and additional notes that I have made for edge cases that would be expounded upon in later courses.

Personally, if an instructor had given me the material I am currently working on at the start of the semester, I would have used it to my advantage throughout the course, and it would have saved me about 8 hours of preparing the material myself. Yet, I have a feeling that it could be detrimental to some students, especially in particular subjects. That said, I see no problem in the case of foreign language courses, where the most important thing is active application of what was learned - you have to study vocabulary and grammar before you can use it in class, thus giving students a set of flash cards for such topics would not influence their application of the language.

I am wondering: were I in the position of instructor for the course, would it be pedagogically detrimental, or even inappropriate, for me to make such resources and give them to students? Would it depend on the time of the semester when I gave them the resources (e.g. would it be best to give them what I prepared only after all the material has been covered)? Would it depend on the subject?

It sounds helpful, not detrimental. NB, whatever materials you curate and provide will never be "complete" by any objective standard. Consider a textbook: it may be written to address a particular course design, and focus on the main topics relevant to that course, but it cannot make other study resources useless.

The major factor here is how much work you want to put into creating those resources, not what their easy availability would do to impressionable students.


Do hiring committees look at a candidate's StackExchange account? On StackExchange, some people use their real names, while others hide behind a username.

I was wondering, do hiring committees look at a candidate's StackExchange account and consider the candidate's activity on these accounts?

I know committees look at my website, they openly mention this during interviews.  They also ask me about things that they would only know about after seeing my website.  I have yet to connect my real identity with my StackExchange account, because of my reservations about this.

Yes, it can happen, though I expect it is rare.

I was recently asked in a job interview whether I was the Tara B on math.SE.  The interviewer who asked the question is also on math.SE, and we have answered some of the same questions.  I have met him in real life and e-mailed him once to ask for a paper, but I had the impression that he primarily remembered me from stackexchange.  (I did get the job, but I doubt that my SE participation was a significant factor.)

(Incidentally, this also demonstrates that even if you only use part of your name on SE, your account might still be noticed.)


Is a revisiting review bad? I need to know what it means when a paper starts with: “Revisiting [topic]”

I read enough on a topic to write a survey paper, and I want to publish it in a conference to get feedback and discuss it with the relevant community. I want to publish it as soon as possible, because if I don’t, somebody else will.

However, it might be the case that in the future, I can find more relevant information and my insights will develop (as I will continue researching the same topic in the future), which might extend the survey I propose. Is it okay to publish another ‘revisiting’ paper with an extended survey? Or does this leave a bad mark on the publication and the researcher? I do not want to delay publishing because it may be hard to reach a point where I am 100% satisfied with my knowledge of the topic. But I might be wrong and I should publish only when I reach this stage.

A survey paper shouldn't just be the result of 'I did lots of reading'. There are two key types of survey I've come across. One is when some major result has been proved, and so it is time to do a 'round up' drawing together all the different ideas that go into it and with it. The second is when you've done lots of reading and have something useful to add as a result (ie the paper contains new research, on some level, as well as survey material).

I would say the issue isn't whether you 'revisit' something, but rather whether you try to publish work that doesn't add enough to the literature. No-one is going to really mind if you freely release an extended paper as an eprint for those who want to read it. On the other hand, trying to get published two separate papers that are nearly the same is not going to look so good.


Is it common for college students to drop a year or 2 between UG and graduate studies? I've heard of people taking a break for getting work experience or internships and jobs and so on ... is this the norm ?

I can't say if it's the norm, but I don't expect that working for a year or two after undergrad would be frowned upon by graduate admissions committees. So long as your job is related to your field of study, you'll be augmenting your academic studies with real-world experience, which can indeed be valuable in preparation for a graduate curriculum.

Personally, I applied for grad school straight out of undergrad, but didn't find the funding I was hoping for, so I worked for a year and then tried again. I received more and better offers the second time around.


Why is the CV needed for graduate application Why do graduate schools ask for a CV to be included in the application? Do they look for anything else besides publications and work experience?

A CV is the academic equivalent of a resume, providing all of the relevant details of your (academic) career to date.  Graduate schools ask for this information for the same reason that businesses ask for a resume when you apply for a job: it is a terse summary of your qualifications as a candidate.

In addition to publications and (research-related) positions held, a CV also should include your undergraduate and graduate degrees, service, any awards, and any other academic-relevant information about you.  A nice summary, with links to additional guide material can be found here.


Letter recommender hasn't responded to request and has conference deadline coming up. Should I remind them? The title is a bit lengthy but captures the crux of the issue. I made a bit of a hasty decision to apply to PhD programs this round rather late (last Thursday) and sent potential letter writers a request on Friday. One of them is my advisor, another is a professor who I've worked with briefly, and the last is a professor who's not in my field but has known me personally for a while.
The second professor hasn't responded, and I'm beginning to worry. It has only been 5-6 days since I sent the request, but there is also a deadline coming up for a major conference on the 16th.
I also made the mistake of not including the deadlines in the initial email. The deadline for application is December 1st, so there isn't much time.
I'm wondering if I should follow up this week with a reminder, or if I should go in person.
Any feedback or opinions are appreciated. Thanks.

You sent the request last Friday. It is now Wednesday, i.e., the third working day after the request. That is not a lot of time at all, in the calendar of a professor. Moreover, the deadline is on December 1, which is still almost four weeks away.
Give the professor at least one more week. Maybe then send a reminder, and mention the deadline in that reminder.


Publication grade concept drawings I am working on my Masters' thesis in aeronautical engineering and would like to make high-quality drawings (not technical drawings as in detail designs in CAD, but drawings of concepts and ideas, eg airplane with basic forces acting on it).

I am sure is this a common task in technical writings and would like to know if there is software available for such purposes?

Disclaimer: I am not a graphic designer and don't have the skill or time to make nice drawings from scratch. I am hoping there is software that has a library of a bunch of basic shapes and images that can be edited and freely used.

I think there is a TeX.SE question that deals with this. The details are not clear to me, but it appears that with a little work you can use TikZ with LaTeX to draw a plane:

This TeX.SE example used a variety of tools including Inkscape, Sketch, Blender, and Cinema4D (of which only Cinema4D is not FOSS) to produce:

From what I can piece together from this TeX.SE answer, details of how the above diagrams are made is available in Italian here. A Google Translate version of the abstract is:

This article shows how you can use the power of LATEX and PSTricks and TikZ packages in the production of advanced illustrations . The creation of designs that represent the three-dimensional scenes with directions of scientific content is made possible with LATEX . The author shows how it is able to manipulate and arrange three-dimensional objects in a scene with the program Sketch of Eugene Ressler edil its intuitive scripting language , getting a ' output in the form of PSTricks or TikZ commands . The proposed working method allows to overcome the limitations that users of a package as PSTricks , which also has relatively advanced three-dimensional drawing capabilities , meet whenever are going to want to draw and manipulate three-dimensional scenes containing objects simple and primitive .
The teaching of a subject such as engineering Flight Dynamics is a field in which he operates, and which they refer to the specific examples given in the article

which suggests that Cinema4D may not be critical.


Potential issues with uploading copyrighted material to TurnItIn? My university uses TurnItIn to check student's work for plagiarism and collusion. I think the underlying TurnItIn database includes both submitted work and material it has found by crawling the web, but not material behind pay walls. One major issue with TurnItIn, and presumably all plagiarism detection software, is that it can only compare submitted work to material which is in the database. This means that TurnItIn either misses when students copy from textbooks which are behind a pay wall or matches other sources which have plagiarised the textbook.

My department's academic misconduct committee is thinking about seeding the TurnItIn database with the textbook chapters that are most often used by the students by submitting a number of "assignments" that are copies of the textbook chapters. This would require an individual member(s) of staff to submit assignments that contained copied copyright material. Is it possible that this could get the staff member in trouble in the future? We were thinking about adding something like:

  The following submission is intended to seed the TurnItIn database and is an exact copy of FULL REFERENCE.

Would this work, or would TurnItIn realize that it is being given copyrighted material and purge it from its database?

This is a bit long for a comment, but I also acknowledge that only someone from TurnItIn could categorically answer this.

Since TurnItIn does not provide access to source material (other than small sections which actually match the submitted paper), I do not see how it could be a copyright issue. I get matches all the time from papers submitted to other schools, yet, TurnItIn does not allow me to see that paper.

Additionally, much of the content within TurnItIn is under copyright (blogs and others) and they do not purge it, further implying that they would not have a problem with your plan.

All that said, unless the content is quite new, or changed regularly, as soon as one student includes content, any other student including that same content will trigger a flag for you.

So, I do not believe your plan will have any problem but I am also not sure you need to worry about it unless you have a special set of texts you believe other students around the world will not have access to.


Do any legitimate conferences charge per publication? In computer science, or at least my subfield of it, most research is published in conference proceedings.  The usual procedure is to write a full article, submit it to a conference, and then if it's accepted for publication, at least one author must register for the conference and present the work at a talk or poster session there.  The flat registration fee fully covers the author's attendance at the conference, and a physical or electronic copy of the proceedings, no matter how many papers he or she may be presenting.

I recently discovered a computer science conference that employs a different model:  "Authors have to pay for each accpeted paper the registration fee." [sic]  I've never heard of this sort of arrangement before.  Is this an unusual but legitimate practice in computer science (or any other field), or is this something only a disreputable or predatory conference would do?  If it's legitimate, on what basis could the organizers justify charging the full conference registration fee (in this case up to €1797 with tax) per paper rather than per attendee?

In computer science some legit conferences charge per accepted publication. In my experience, legit but small conferences perform this practice, perhaps to better cover the organization costs. Bigger conferences are often sponsored by big partners, e.g., Google, Microsoft, Facebook, Cisco, .., so they do not need to look for money elsewhere.

Generally speaking, conference registration pages are not very clear on this issue. Let's observe the registration page of the three biggest and most respected software engineering conferences, that are ICSE, FSE, and ESEM (there might be another better example for the third place here).

ICSE 2015 registration page:

  As specified in the acceptance letter, each accepted paper must be “covered” by one registration in the name of one of the authors.

FSE 2014 registration page:

  our paper submission and acceptance implies that one of the paper's authors should register the paper using non-student registration, i.e., either as non-member or ACM/SIGSOFT (Student) member, and present the paper at FSE 2014.

ESEM 2014 registration page:

  Conference registration is compulsory for at least one author of accepted papers and posters.

In my opinion, all three pages might imply that the conferences require a per publication fee. But,

I have just asked an author who was accepted twice for ICSE, and he was not required to pay twice the registration costs. (confirmed by @Psychonaut)
@Psychonaut can confirm that FSE does also not require multiple registrations.
I have asked some ESEM authors and organizers, and ESEM does not charge twice if a single author presents two papers.

Smaller conferences tend instead to ask for a per publication fee in case of multiple accepted papers and one author is presenting them.

An example is PROFES, which is a small yet respected and established venue.

  Each paper published in the conference proceedings (full/short/poster paper) requires at least one early registration to the main conference as regular attendee.

I happened to be there with two papers (one full, one short), and I had to pay twice.

I have seen some variations, e.g., one full registration for the first accepted paper, one discounted "student" registration for subsequent accepted papers.

To further clarify, if you have two accepted articles which are co-authored by Author A and Author B, either only Author A or Author B register twice (and present both papers), or both Author A and Author B register once each and present one paper each. In the second case, it might be just a matter of speaking with the organizers to still let one author present both papers.


What is suitable format to present a Psuedo Code in academic paper? I'm going to include my algorithm as a pseudo-code in a double-column paper format.

However, since lines of my pseudo-code are long I don't know if is it suitable to use the width of both columns to demonstrate algorithm or not? I want to know are there any common rules for this?

This depends on the journal's author guidelines. If no specifics are stated, you can often add the pseudo-code like a figure in your text (just labeled with Algorithm 1 instead of Figure 1).


While showing my work to my supervisor, an adult website appeared. Am I in trouble? I will try to make this brief. I am a student at a prominent university in the UK, and while I was showing my thesis work, a website, to my supervisor, the website crashed. Then I was asked to close the browser and open it again.

When I did, it seems a tab of adult content was open from the previous day with explicit content, when that happened, I immediately (without thinking) pressed Cmd-W to close it but it was evident he saw it.

The conversation continued normally and my supervisor completely ignored it. I feel very embarrassed and I am afraid I could be reported or anything.

Am I in trouble? Will I face issues because of this? Thank you in advance.

Edit: My laptop is a personal laptop and not provided by the university. I've also used the University network to access the site from my dorm. I also don't think there are university guidelines that prevent us from accessing adult content.

It's embarrassing, but it's also understandable. I think if your supervisor has decided to ignore it, then you should take this opportunity to not ruminate. So silently thank him, and forget it.

I know advice is always easier said than done though. Rumination is defined as "to keep thinking about a problem which had already been, or can never be solved". The real problem had already been solved at the moment he decided to ignore it, so the only problem here is your rumination. To stop it, every time you feel embarrassed about this topic again, my tip is to shake the idea in your head, like it's just a toy. This will make you distract from the negative feeling.

Related:
• Why You Should Stop Caring What Other People Think (Taming the Mammoth) – Wait But Why
• Straightforwardness, Fearlessness and Improvisation: How to find the fresh perspective? – Ooker


Adding co-author for a revised manuscript Is it possible to add a new co-author when requested for a second revision?

Another co-author would help improve the quality of the manuscript, but I am not sure if this is possible.

A revision to a manuscript is a chance to correct any issues raised in the original review. If you and your co-authors feel that adding a co-author would make the manuscript better, then it is of course acceptable to do so, absent explicit instructions to the contrary from the journal (although I am unaware of any journals with such rules).

However, you will also need to clearly explain in your cover letter to the editor why you added the co-author, and exactly what her contributions to the paper were.


Progression through Computer Science Path I am currently in undergraduate studies, and currently participating in computer related studies (mainly security focused). I wish to (as an end goal) pursue a MS and PhD.

I am not sure exactly the experience in graduate level programs as far as focus. Is there a possible focus on Network Security/Infrastructure built into graduate programs or would curriculum be more of a wide range (albeit focused in the realm of computer science)?

If not is there a path which would end at a doctoral level involving information security?

This is a bit of a snarky answer to your question but... did you try Googling "PhD in Computer Science Security"? Perhaps even more useful have you looked at the offerings of your own university to see what a Masters or PhD entails?

To be a bit less snarky in PhD programs, at least, it's less about what the degree is called and more about the research and lab you become involved with. If you are interested in focusing on security, which is a broad field, in Computer Science you will often get a degree in 'Computer Science' but you will work in a lab focused on security.

With that in mind my first recommendation to you is to do some research. Find out what folks are researching at your current institution, see if you find it interesting. If you can, get involved! This is probably the best way to find out what programs exist out there for your interests.

Even beyond your local school - do some digging. I was about to do a quick Google search and find that there are a couple of schools that are considered to have the 'best'(subjectively of course) Security Information programs. You should be able to find this out as well! Start looking into other schools, see what they offer and also what their researchers are researching. See if anything seems interesting. Start reading papers. Do some research into what you want to do.

So, in short, do:

Figure out what research is happening at your school. Try to get involved.
Figure out what are the 'best' programs for the topics you are interested in. Who is the 'big name' in the field? Read those papers!
Find 1 person who you want to be when you 'grow up'. In other words find one person whose job you want to have one day. Research how they got there! See if you can build a road map to your own success based on how they got to where they are.