The trouble with modern interdisciplinary publishing

You may have heard about the recent debacle at PLOS ONE, in which the journal published [1] and then retracted [2] a paper with the following, seemingly creationist line in the abstract (boldface added):

The explicit functional link indicates that the biomechanical characteristic of tendinous connective architecture between muscles and articulations is the proper design by the Creator to perform a multitude of daily tasks in a comfortable way.

The reference to the Creator also appears in the introduction and in the discussion. Jon Wilkins has written good summaries of some of the details, both of the original publication of the paper, and of its subsequent retraction by the PLOS ONE editorial staff. An interesting point he makes is that the use of the English phrase "the Creator" can plausibly be attributed to poor translation from Chinese; an alternate translation could thus be "nature", although that doesn't ameliorate the creationist subtext that is also carried by the phrase "proper design." [3]

Anyway, I'm not interested in second guessing the editorial and authorial sequences of actions that led to the initial publication or its retraction. And, it having happened probably won't impact my own inclination for or against publishing something in PLOS ONE, since I think that the editors and papers at PLOS ONE are generally okay.

Instead, I think this event serves to illustrate a deeper and quite important issue with modern academic publishing, especially interdisciplinary journals like PLOS ONE. The core question is this: how do we scientists, as a community, ensure quality control in a system where we are drowning in the sheer volume of everything? [4]

For instance, vanity journals like Nature and Science don't let little obvious things like this through in part because they employ copy editors whose job it is to proofread and copyedit articles before they are published. But, these journals do let plenty of other, shinier crap through, for which they are properly mocked. But how does the crap get through? I think the answer is partly due to the enormous volume of submissions, which necessarily means that individual submissions often are not looked at very closely or, if they are, they are often not looked at by the right experts. PLOS ONE has, if anything, an even larger volume problem than the vanity journals. Not only did they publish something like 30,000 papers in 2015, but they also have more than 6000 academic editors. The complexity of ensuring a good matching process between papers and editors with appropriate expertise is dizzying. The fact that this enormous machine works as well as it does is pretty remarkable: PLOS ONE is probably easily the world's largest journal, both in volume of submissions, volume of published papers, number of editors, and range of topics covered. It's also a very young journal, having begun publishing only in 2006.

Here's the crux of the matter. Science publishing as we know it was invented when science was run by a pretty small community of fairly like-minded individuals. As it's grown over the past 350 years [5], science has become increasingly specialized, and the specialization trend really kicked in during the 20th century, when governments realized that funding science was politically advantageous (especially for war). Specialization is often held up as a bugaboo in modern discourse, but it's a completely natural process in science, and I think it advanced so much during the 20th century in part because it helped keep the peer review and publication systems small and manageable. That is, specialization is a way to solve the matching process of manuscripts with editors, reviewers and journals.

But, interdisciplinary journals like PLOS ONE, and its shinier brethren like Science Advances [6] and Nature Communications, are racing headlong into territory where the publication system has never functioned before. From a simple logistics point of view, it's not clear that we know how to scale up what is essentially an early 20th century evaluation process [7], which only worked because of specialization, to handle 21st century volumes for interdisciplinary science, and still feel good about the product (effectively peer reviewed papers, for any reasonable definition of peer review).

So, I think it's good that we have places like PLOS ONE who are experimenting in this area. And, I think they rightly deserve our ridicule when they screw up royally, as in the case of this "Creator" paper. But let's not shame them into stopping, e.g., by boycotting them, when they are quite a bit more brave than we are. Instead, I think we as a community need to think harder about the real problem, which is about how to run an effective scientific publishing operation in a world where we cannot rely on specialization to manage the way we collectively allocate the attention of experts.

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[1] Ming-Jin Liu, Cai-Hua Xiong, Le Xiong, and Xiao-Lin Huang. "Biomechanical Characteristics of Hand Coordination in Grasping Activities of Daily Living." PLOS ONE 11(1): e0146193 (2016).

[2] The PLOS ONE Staff. "Retraction: Biomechanical Characteristics of Hand Coordination in Grasping Activities of Daily Living." PLoS ONE 11(3): e0151685 (2016).

[3] It seems possible that the authors could have rewritten the offending parts of the paper in order to make it more clear that they mean these features evolved naturally. However, PLOS did not, apparently, give them that option.

[4] The problems that high volumes induce are pretty fundamental ubiquitous in academia. The most precious resource I have as a scientist is my attention, and it is very limited. And yet, there are an ever increasing number of things that need attending to. The number of students in undergraduate CS programs is increasing; the number of applicants to PhD programs is increasing; the number of applicants to faculty openings is increasing; the number of papers needing to be reviewed is increasing; the number of papers I would like to read in order to stay up on the literature is increasing; the number of meetings I should probably be attending or organizing is increasing; etc. etc. This is a place where technology should be helping us focus on things that are important, but instead, it's just made everything worse, by lowering barriers. Email is the perfect example of this.

[5] Arguably, science as a field was first formalized in the founding of the Royal Society in 1660.

[6] Full disclosure: I am currently an Associate Editor at Science Advances. We have our own version of the volume+diversity problem, and we have our own method for managing it. The method requires a lot of human attention in sorting things into buckets, and I have great respect for our sorters (who are also academics, like all the associate editors). But how scalable is our system? What mistakes does it tend to make? How could we lower the error rate? I don't think anyone knows the answers to these questions, and I am not sure anyone is even thinking that these are questions that need to be answered.

[7] Peer review was mainly carried out directly by the senior-most editors until the late 19th century, and it wasn't until the early 20th century that the process we recognize today, with external reviewers, took shape.

Posted on March 07, 2016 in Interdisciplinarity | permalink | Comments (1)

2015: a year in review

This is it for the year. Here's a look back at my 2015, by the numbers [1,2]:

Papers published or accepted: 8 (journals or equivalent)
Number that were "gold" open access: 2
Number coauthored with students: 4
Number that used data from sports: 2, again (this and that)
Cumulative fraction of my papers available online, for free: 0.87 (+0.21 over 2014)
Pre-prints posted on the arxiv: 7
Other publications: 1 perspective piece, and 1 popular press piece
Number of those coauthored with students: 1
Papers currently under review: 4
Manuscripts near completion: 5
Rejections: 7 (+17% over 2014)
Number of papers making up those rejections: 6
New citations to past papers: 1981 (+1.1% over 2014)
Projects in-the-works: too many to count
Half-baked projects unlikely to be completed: already forgotten
Papers read: >114 (about 2 per week)
Number of open browser tabs containing papers to read, right now: 9
Number of Dropbox folders created for research projects: 4

Research talks given: 6
Invited talks: 6
Visitors hosted: 5
Conferences, workshops organized: 3
Conferences, workshops, summer schools attended: 9
Number of those at which I delivered a research talk: 4
Number of times other people have written about my research: >42 (mostly about faculty hiring networks)
Number of interviews given about my research: 18
Coolest interview: for Double Helix, an Australian children's science magazine

Postdocs advised: 3
Students advised: 11 (5 PhD, 1 MS, 3 BS; 2 rotation students)
Students graduated: 1
Thesis/dissertation committees: 4
Number of recommendation letters written: 10
Summer school faculty positions: 1, in India (technically a "winter school")
"Short" courses taught: 2 (both on networks)
University courses taught: 1 (this one)
Students enrolled in said courses: 11 undergrads
Number of problems assigned: 23 (weekly essays, plus two essay exams)
Number of pages of lecture notes written: pleasantly few
Pages of student work graded: >390 (roughly 36 per undergrad, with 0.09 graders per student)
Number of class-related emails received: >400 (-86% over 2014)
Number of conversations with the university honor council: 0

Journals for which I am an associate editor: 2 (same as 2014)
Manuscripts handled as an associate editor: 27 (+450% over 2014)
Manuscripts refereed for various journals and journal-equivalent conferences: 15 (-44% over 2014)
Number of those mainly refereed by my students and postdocs: 8
Manuscripts or abstracts lightly refereed for workshops and non-CS conferences: 84
Conference program committees: 4
Fields covered: Network Science, Computer Science, Statistics, Physics, and some tabloids
Words written per referee report: 729 (-45% over 2014)
Referee requests declined: 77 (+4% over 2014)
Journal I declined the most: Scientific Reports (10 declines, 0 accepts; just edging out Physica A)
Program committee invitations declined: 4
Number of referee reports I owe anyone, right now: 0
Number of NSF panels I sat on: 2
Grant proposals reviewed: 15
Fraction that I thought deserved to be funded: 0.50
Fraction that were, I believe, actually funded: <0.20

Grant proposals submitted or reviewed (as PI or coPI): 7 (totaling $34,257,680)
Number on which I was PI: 2
Proposals rejected: 5
New grants funded: 2 (totaling $600,014)
Proposals pending: 1
New proposals in the works: 2

Emails sent: >9104 (-2% over 2014; about 25 per day)
Emails received (non-spam): >18,403 (-8% over 2014; about 50 per day)
Fraction about work-related topics: 0.91 (+0.01 over 2014)
Fraction that was spam from my university: 0.04 (+7% over 2014)
Fraction about research funding: 0.07
Emails received about power-law distributions: >94 (about 2 per week)
Number of emails in my inbox, right now: 21
Oldest-dated email in my inbox, right now: November 2010 (I am ashamed)

Unique visitors to my professional homepage: 30,000 (+3% over 2014)
Hits overall: 78,000 (-17% over 2014)
Fraction of visitors looking for power-law distributions: 0.38 (-0.01 over 2014)
Fraction of visitors looking for my course materials: 0.28 (+0.04 over 2014)
Unique visitors to my blog: 5,700 (-21% over 2014)
Hits overall: 9,000 (-29% over 2014)
Most popular blog post among those visitors: A "reverse" color test (from 2006)
Blog posts written: 2 (-70% over 2014)
Blog posts conceived but never written down: 3 (I think?)
Number of twitter accounts: 1
New followers on Twitter: >653 (-12% over 2014)
Tweets: 202 (-10% over 2014; including retweets of others)
Retweets of my tweets: 1108 (+10% over 2014)
Average number of retweets per original tweet: 8.9 (+31% over 2014)
Fraction of my tweets that are original: 0.62 (-0.04 over 2014)
Most popular tweet: one about NSF requiring articles to be made publicly available within one year of publication

Number of computers purchased: 1
Number of cars purchased: 0
Netflix: too many to count
Books purchased: 4 (-43% over 2014)
Books read: 3 (+0% over 2014)
Songs added to music library: 544 (+435% over 2014)
Photos added to photo library: 1654 (+70% over 2014)
Photos taken of my daughters: >1650 (about 5 per day)
Jigsaw puzzle pieces assembled: 1160
Major life / career changes / decisions: 1
Number of offspring: 2 (+100% over 2014)

Fun trips with friends / family: 7
Half-marathons completed: 0
Steps this year: 2,169,560 (about 6000 per day)
Walking distance this year: 1201 miles (about 3.3 per day, but it's very bursty)
Trips to Las Vegas, NV: 0
Trips to New York, NY: 0
Trips to Santa Fe, NM: 6
States in the US visited: 5 (TX, NM, CA, TN, AZ)
States in the US visited, ever: 49
Foreign countries visited: 2 (Spain, India)
Foreign countries visited, ever: 31 (+3% over 2014)
Other continents visited: 2
Other continents visited, ever: 5
Airplane flights: 23 (-48% over 2014)

Here's to a great year, and hoping that 2016 is even better.

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[1] I am shocked to learn that some people actually look forward to my year-by-the-numbers post.

[2] It is hard to ignore the fact that I don't post much here anymore. This is partly because of being busy with other things, some fun and some tedious, that come with being a university professor, and with having a family. I also now post many of the things that I read and find interesting on Twitter, which people seem to like. That said, I still like the idea of having a blog, where I can write things that are too long for Twitter, but too informal for an academic paper. So, as long as the CS Department at the University of New Mexico keeps the servers running the blog up, I'll keep posting, occasionally. If those servers go down, or if UNM asks me to relocate, I'll have to make a decision about whether it's worth the effort to move it. (I've already looked into it, and it seems... highly non-trivial to move 10 years worth of material to another platform.)

Posted on December 26, 2015 in Self Referential | permalink | Comments (3)

Clever crows

This is a pretty remarkable achievement, not just for the crow, but also for the researcher figuring out how to elicit such clever behavior. [1]

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[1] Perhaps the iconic "clever girl" line from Jurassic Park was not, in fact, that fanciful. If some birds are so clever, and since birds are just the branch of dinosaurs that happened to survive, it seems entirely reasonable that some dinosaurs were also quite clever.

Posted on July 21, 2015 in Obsession with birds | permalink | Comments (0)

2014: a year in review

This is it for the year, so here's a look back at 2014, by the numbers.

Papers published or accepted: 9 (journals or equivalent)
Number coauthored with students: 5
Number of papers that used data from sports: 2 (this and that)
Pre-prints posted on the arxiv: 5
Other publications: 2 workshop papers, and 1 popular press piece
Number of those coauthored with students: 1
Papers currently under review: 1
Manuscripts near completion: 9
Rejections: 6
Number of papers making up those rejections: 2
New citations to past papers: 1959 (+14% over 2013)
Projects in-the-works: too many to count
Half-baked projects unlikely to be completed: already forgotten
Papers read: >104 (about 2 per week)
Number of open browser tabs containing papers to read, right now: 22

Research talks given: 15
Invited talks: 13
Visitors hosted: 7
Presentations to high school students about science and data: 1 (at Fairview High School in Boulder)
Conferences, workshops organized: 3
Conferences, workshops, summer schools attended: 9
Number of those at which I delivered a research talk: 8
Number of times other people have written about my research: >9
Number of interviews given about my research: 4
Number of times I appeared on the BBC Radio: 1 (here)

Students advised: 11 (6 PhD, 1 MS, 2 BS; 1 rotation student and 1 high school student)
Students graduated: 1 MS
Thesis/dissertation committees: 10
Number of recommendation letters written: 12
Summer school faculty positions: 1
University courses taught: 2
Students enrolled in said courses: 113 undergrad, 32 grad
Number of problems assigned: 121 and 50
Number of pages of lecture notes written: the mind shudders to think
Pages of student work graded: >7500 (roughly 44 per undergrad and 84 per grad student, with 0.02 graders per student)
Number of class-related emails received: >2814 (+73% over 2013)
Number of conversations with the university honor council: 0

Manuscripts handled as an associate editor: 6 (+300% over 2013)
Manuscripts refereed for various journals and journal-equivalent conferences: 27 (+17% over 2013)
Number of those mainly refereed by my students and postdocs: 11
Manuscripts lightly refereed for workshops and non-CS conferences: 45
Conference program committees: 4
Fields covered: Network Science, Machine Learning, Data Science, Ecology, and some tabloids
Words written per referee report: 1333 (+45% over 2013)
Referee requests declined: 74 (+9% over 2013)
Journal I declined the most: Physica A (8 declines, 0 accepts)
Program committee invitations declined: 5
Number of referee reports I owe anyone, right now: 0

Grant proposals submitted (PI or coPI): 10 (totaling $38,227,680)
Number on which I was PI: 4
Proposals rejected: 2
New grants awarded: 2 (totaling $620,000, including my NSF CAREER proposal)
Proposals pending: 6
New proposals in the works: 2

Emails sent: >9325 (+13% over 2013, and about 25 per day)
Emails received (non-spam): >20,026 (+22% over 2013, and about 55 per day)
Fraction about work-related topics: 0.90 (+0.03 over 2013)
Fraction of work-related email about research funding: 0.13
Emails received about power-law distributions: 153 (3 per week, same as 2013)
Number of emails in my inbox, right now: 24
Oldest-dated email in my inbox, right now: November 2010 (I am ashamed)

Unique visitors to my professional homepage: 29,000 (-7% over 2013)
Hits overall: 94,000 (+8% over 2013)
Fraction of visitors looking for power-law distributions: 0.39 (-0.13 over 2013)
Fraction of visitors looking for my course materials: 0.24
Unique visitors to my blog: 7,200 (-36% over 2013)
Hits overall: 12,600 (-27% over 2013)
Most popular blog post among those visitors: The faculty market (Advice to young scholars, part 1 of 4) (from 2014)
Blog posts written: 7 (+17% over 2013)

Number of twitter accounts: 1
New followers on Twitter: >741 (+6% over 2013)
Tweets: 225 (-4% over 2013; including retweets of others)
Retweets of my tweets: 1006 (+8% over 2013)
Average number of retweets per original tweet: 6.8
Fraction of my tweets that are original: 0.66
Most popular tweet: a tweet about there being more annual job openings than graduates for CS and Math majors
K-index: 2.98 (just over half a Kardashian Scientist; whew)

Number of computers purchased: 1
Number of cars purchased: 1
Netflix: <60 dvds, 139 streaming (mostly TV episodes during lunch breaks and nap times)
Books purchased: 7 (+133% over 2013)
Books read: 3 (+0% over 2013)
Songs added to iTunes: 125 (-11% over 2013)
Photos added to iPhoto: 971 (-59% over 2013)
Photos taken of my daughter: >933 (about 3 per day)
Jigsaw puzzle pieces assembled: 0
Major life / career changes / decisions: 2

Fun trips with friends / family: 9
Half-marathons completed: 0
Trips to Las Vegas, NV: 0
Trips to New York, NY: 1
Trips to Santa Fe, NM: 7
States in the US visited: 9 (MA, NY, PA, UT, FL, NM, CA, VA, MI)
States in the US visited, ever: 49
Foreign countries visited: 3 (Germany, China, Canada)
Foreign countries visited, ever: 30
Other continents visited: 2
Other continents visited, ever: 5
Airplane flights: 44 (+13% over 2013)

Here's to a great year, and hoping that 2015 is even better.

Posted on December 21, 2014 in Self Referential | permalink | Comments (1)

Using LaTeX for a paper for Science Advances

I recently wrote a paper for the new AAAS journal Science Advances using LaTeX (as opposed to their Microsoft Word template), and have some things to share with others interested in sending their beautifully typeset work to that journal. [1]

First, Science Advances uses a bibliography style that is slightly different from that of Science, which means that the Science.bst file available from AAAS for submissions to Science is not suitable. Specifically, Science Advances wants full titles to be listed and wants full page ranges (rather than just the first page). My reading of the detailed information for authors suggests that these are the only differences. Here is a modified version of the Science.bst file, called ScienceAdvances.bst, that conforms to the required bibliographic style. [2]

Second, Science Advances uses a slightly different format for the manuscript itself than Science, and so again, the existing LaTeX template is not quite suitable. One difference is that Science Advances requires section headings. Here is a zip file containing a Science Advances LaTeX template, modified from the Science template distributed by AAAS, that you can use (note: this zip includes the bst file listed above). [2]

Finally, there are a few little things that make Science Advances different from Science. SA has a much longer (effective) length limit, being 15,000 words compared to Science's 4500 words. The Reference list in SA is comprehensive, meaning that references cited only in the Supplementary Material should be included in the main text's reference list. There is also no limit on the number of references (compared to Science's limit of 40). And, SA places the acknowledgements after the Reference section, and the acknowledgements include information about funding, contributions, and conflicts of interest. Otherwise, the overall emphasis on articles being of broad interest across the sciences and of being written in plain English [3] remains the same as Science.

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[1] Full disclosure: I am currently serving as an Associate Editor for Science Advances. Adapting Science's LaTeX files to Science Advances's requirements, and sharing them online, was not a part of my duties as an AE.

[2] The files are provided as-is, with no guarantees. They compile for me, which was good enough at the time.

[3] Of course, biology articles in Science are hardly written in "plain English", so there is definitely some degree of a double-standard at AAAS for biology vs. non-biology articles. Often, it seems that biology, and particularly molecular biology, can be written in dense jargon, while non-biology, but especially anything with mathematical concepts or quantities in it, has to be written without jargon. This is almost surely related to the fact that the majority of articles published in Science (apparently by design) are biomedical in nature. AAAS is claiming that Science Advances will be different, having a broader scope and a greater representation of non-biomedical articles (for instance, SA specifically says it wants articles from the social sciences, the computer sciences, and engineering, which I think is a really great stance). Whether they can pull that off remains to be seen, since they need to get the buy-in from the best people in these other fields to send their high-quality work to SA rather than to disciplinary venues.

Posted on December 06, 2014 in Simply Academic | permalink | Comments (0)

Grants and fundraising (Advice to young scholars, part 4 of 4)

These notes are an adapted summary of the the 4th of 4 professional development panels for young scholars, as part of the American Mathematical Society (AMS) Mathematics Research Community (MRC) on Network Science, held in June 2014. Their focus was on mathematics, computer science, and networks, but many of the comments generalize to other fields. [1,2]

Panel 4. Grants and Fundraising

Opening remarks: In general, only around 10% of grant proposals are successful. But, roughly 60% of submitted proposals are crap. Your competition for getting funded is the non-crappy 40%. Therefore, work hard to polish your proposals, and take as much time as you would a serious or flagship paper. Get feedback from colleagues on your proposals before submitting, and try as hard as possible to get that feedback at least one month before the deadline. (Many institutions have these "mock panels" available, and they are incredibly useful, especially for early career scientists.) Practice makes the master, so consider writing a grant proposal as a postdoc. Having some success as a postdoc will also make you look more attractive as a faculty candidate. Know when the annual deadlines are for the regular grant competitions, and plan ahead. Try to avoid the last-minute crush of writing proposals in two weeks or less.

  • What should be in a proposal?
    Really exciting research. But, try to propose to do more than just really exciting research. Consider organizing workshops, creating new classes, creating notes, giving public lectures, hosting undergraduates, working with underrepresented groups, running a podcast series, and even teaching in a local high school.

  • What kinds of proposals should an early-career person write?
    In your first few years as faculty, apply to all the early-career fellowships and competitions that you can comfortably manage. That includes the Sloan, McDonnell, Packard, etc., along with the NSF CAREER award, and the various "early investigator" competitions at the DoD and other places. Figure out what people do in your field and do that too. These awards are sometimes for sizable amounts of funding, but even if they are not, they are often very prestigious.

  • How many grants do I need?
    This depends on the size of your preferred research group. Many faculty try to keep 2-3 active grants at once, and write approximately 1-2 new proposals per year. As a rough calculation, a "normal sized" grant from many parts of NSF will support 1 graduate student for its duration (plus modest summer salary, travel, and computing equipment).

  • Can I propose work that I have already partially completed?
    Yes. This is common, and often even recommended. "Preliminary results" make a proposal sound less risky, and basically the reviewers are looking for proposals that are exciting, will advance the state-of-the-art, well written, and exceedingly likely to succeed. If you've already worked out many of the details of the work itself, it is much easier to write a compelling proposal.

  • Proposals are often required to be understandable by a broad audience but also include technical details, so how do you balance these requirements?
    An advanced undergraduate should be able to understand your proposal with some training. Most panels have some experts who can judge the technical details. A good strategy for learning how to balance technical material versus accessibility is to read other people's proposals, especially successful ones, even outside your field. The first pages of any proposal should be more broadly understandable, while the final pages may be decodable by experts only.

  • Can you reuse the same material for multiple grants?
    It's best not to double dip. If a grant is rejected, you can usually resubmit it, often to the same agency (although sometimes not more than once). Because you have some feedback and you have already written the first proposal, it's often less work to revise and resubmit a rejected proposal. (But, the goal posts may move with the resubmission because the review panel may be composed of different people with different opinions, e.g., at NSF.) Small amounts of overlap are usually okay, but if you don't have anything new to propose, don't submit a proposal.

Pro tips:

  • Calls For Proposals (CFPs) are often difficult to decode, so don't hesitate to ask for help to translate, either from your colleagues or from the cognizant program officer. Usually, the specific words and pitch of a program have been shaped by other researchers' interests, and knowing what those words really mean can help in deciding if your ideas are a good match for the program.
  • Proposals are reviewed differently depending on the agency. NSF proposals are reviewed by ad hoc committees of practicing scientists (drawn essentially at random from a particular broad domain). NIH proposals are reviewed by study panels whose membership is fairly stable over time. DoD proposals are reviewed internally, but sometimes with input from outside individuals (who may or may not be academics).
  • Don't write the budget yourself. Use the resources of your department. You will eventually learn many things about budgeting, but your time is better spent writing about the science. That being said, you will need to think about budgets a lot because they are what pay for the research to get done (and universities and funding agencies really love to treat them like immutable, sacred documents). Familiarize yourself with the actual expenses associated with your kind of research, and with the projects that you currently and aim to do in the future.
  • For NSF, don't budget for funding to support undergraduates during the summer; instead, assume that you will apply for (and receive) an REU Supplement to your award to cover them. The funding rate for these is well above 50%.
  • NSF (and some other agencies) have byzantine rules about the structure, format, and set of documents included in a proposal. They now routinely reject without review proposals that don't follow these rules to the letter. Don't be one of those people.
  • Ending up with leftover money is not good. Write an accurate budget and spend it. Many agencies (e.g., NSF and NIH) will allow you to do a 1-year "no cost extension" to spend the remaining money.
  • Program officers at NSF are typically professors, on leave for 2-3 years, so speak to them at conferences. Program officers at DoD agencies and private foundations are typically professionals (not academics). NSF program officers exert fairly little influence over the review and scoring process of proposals. DoD and foundation program officers exert enormous influence over their process.

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[1] Panelists were Mason Porter (Oxford), David Kempe (Southern California), and me (the MRC organizers), along with an ad hoc assortment of individuals from the MRC itself, as per their expertise. The notes were compiled by MRC participants, and I then edited and expanded upon them for clarity and completeness, and to remove identifying information. Notes made public with permission.

[2] Here is a complete copy of the notes for all four panels (PDF).

Posted on December 03, 2014 in Simply Academic | permalink | Comments (0)

Doing interdisciplinary work (Advice to young scholars, part 3 of 4)

These notes are an adapted summary of the the 3rd of 4 professional development panels for young scholars, as part of the American Mathematical Society (AMS) Mathematics Research Community (MRC) on Network Science, held in June 2014. Their focus was on mathematics, computer science, and networks, but many of the comments generalize to other fields. [1]

Panel 3. Interdisciplinary Research

Opening remarks: Sometimes, the most interesting problems come from interdisciplinary fields, and interdisciplinary researchers are becoming more and more common. As network scientists, we tend to fit in with many disciplines. That said, the most important thing you have is time; therefore, choose your collaborations wisely. Interdisciplinary work can be divided into collaboration and publication, and each of these has its own set of difficulties. A common experience with interdisciplinary work is this:

Any paper that aims for the union of two fields will appeal mainly to the intersection. -- Jon Kleinberg

  • What's the deal with interdisciplinary collaborations? How do they impact your academic reputation?
    There are three main points to consider when choosing interdisciplinary collaborations, and how they impact perceptions of your academic reputation.
    First, academia is very tribal, and the opinions of these tribes with regards to your work can have a huge impact on your career. Some departments won't value work outside their scope. (Some even have a short list of sanctioned publication venues, with work outside these venues counting literally as zero for your assessments.) Other departments are more open minded. In general, it's important to signal to your hopefully-future-colleagues that you are "one of them." This can mean publishing in certain places, or working on certain classes of problems, or using certain language in your work, etc. If you value interdisciplinary work, then you want to end up in a department that also values it.
    Second, it's strategically advantageous to be "the person who is the expert on X," where X might be algorithms or statistics or models for networks, or whatever. Your research specialty won't necessarily align completely with any particular department, but it should align well with a particular external research community. In the long run, it is much more important to fit into your community than to fit into your department, research-wise. This community will be the group of people who review your papers, who write your external letters when you go up for tenure, who review your grant proposals, who hire your students as postdocs, etc. The worst possible situation is to be community-less. You don't have to choose your community now, but it helps to choose far enough ahead of your tenure case that you have time to build a strong reputation with them.
    Third, make sure the research is interesting to you. If your contribution in some interdisciplinary collaboration is to point out that an off-the-shelf algorithm solves the problem at hand, it's probably not interesting to you, even if it's very interesting to the collaborator. Even if it gives you an easy publication, it won't have much value to your reputation in your community. Your work will be compared to the work of people who do only one type of research in both fields, and might not look particularly good to any field.
    Be very careful about potentially complicated collaborations in the early stages of your career. Be noncommittal until you're sure that your personalities and tastes in problems match. (Getting "divorced" from a collaborator, once a project has started, can be exhausting and complicated.) Being able to recognize cultural differences is an important first step to good collaborations, and moving forward effectively. Don't burn bridges, but don't fall into the trap of saying yes to too many things. Be open to writing for an audience that is not your primary research community, and be open to learning what makes an interesting question and a satisfying answer in another field.

  • What's the deal with publishing interdisciplinary work? Where should it go?
    As a mathematical or computer or data scientist doing work in a domain, be sure to engage with that domain's community. This helps ensure that you're doing relevant good work, and not reinventing wheels. Attend talks at other departments at your university, attend workshops/conferences in the domain, and discuss your results with people in the domain audience.

    When writing, vocabulary is important. Knowing how to speak another discipline's language will help you write in a way that satisfies reviewers from that community. Less cynically, it also helps the audience of that journal understand your results, which is the real goal. If publishing in the arena of a collaborator, trust your collaborator on the language/writing style.

    In general, know what part of the paper is the most interesting, e.g., the mathematics, or the method or algorithm, or the application and relationship to scientific hypotheses, etc., and send the paper to a venue that primarily values that thing. This can sometimes be difficult, since academic tribes are, by their nature, fairly conservative, and attempting to publish a new or interdisciplinary idea can meet with knee-jerk resistance. Interdisciplinary journals like PLOS ONE, which try not to consider domain, can be an okay solution for early work that has trouble finding a home. But, don't overuse these venues, since they tend also to not have a community of readers built in the way regular venues do.

    Note: When you interview for a faculty position, among the many questions that you should be asking the interviewing department: "In practice, how is your department interdisciplinary? How do you consider interdisciplinary work when evaluating young faculty (e.g., at tenure time)?"

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[1] Panelists were Mason Porter (Oxford), David Kempe (Southern California), and me (the MRC organizers), along with an ad hoc assortment of individuals from the MRC itself, as per their expertise. The notes were compiled by MRC participants, and I then edited and expanded upon them for clarity and completeness, and to remove identifying information. Notes made public with permission.

[2] Here is a complete copy of the notes for all four panels (PDF).

Posted on December 02, 2014 in Simply Academic | permalink | Comments (0)