Discussion of research tools (for students and collaborators)
Volker Franz, University of Tübingen, Germany
In practical research situations, we repeatedly encounter similar problems. Here is a list of things I found useful. Therefore, if you are working with me or intend to do so, you should take the time to have a look at the topics discussed here (no matter at which level: research-assistant/HiWi, BSc-candidate, MSc-candidate, PhD-candidate, PostDoc). It will speed up our discussions and also help you to know recurring themes in our practical scientific work...
Table of contents
- 1. Workflow for experiments and statistical analyses
- 2. Scientific writing
- 3. Mailing lists
- 4. Being a graduate student
1. Workflow for experiments and statistical analyses
A typical experiment in our lab consist of the following steps:Running the experiment
To program an experiment, we currently use Matlab with the PsychophysicsToolbox and my own OptotrakToolbox. We might switch to Python and PsychoPy at some point (we already wrote a basic OptoPy module to replace the OptotrakToolbox).
Data transfer from experimental machine
We use unison to sync the data between our experimental machines and our file-server. Unison is excellent, please try to learn it. You can use it in a wide variety of situations (for example, you can easily synchronize large and complete home directories between different machines).
Basic statistical analysis
We typically do the basic statistical processing (e.g., extracting the parameters of interest) in Matlab or Python. Typically, this results in plots for visually inspecting the data and ASCII-files for further analyses. Sometimes the issue of filtering the data arises. An excellent book on digital signal processing that is even available for free on the web is: The Scientist and Engineer's Guide to Digital Signal Processing by Steven W. Smith.
Further statistical analyses
We typically do all our further analyses in the R-programming language.. Often, this is just the most versatile way to do the analyses. Possible alternatives are, of course, Python, Matlab, SPSS. If you are not using a special package (like EEGLAB), I would not recommend Matlab because it is very bad in even the simplest statistical analyses we typically need in our experiments. In rare cases, SPSS can be a help (e.g., if you need a standard analysis and already know how to do it in SPSS). In that case, I would recommend to do it in SPSS and R in parallel and as soon as you know how to do it in R, go on with R.
Replications and reading data from published graphs
Replication is an integral part of our scientific work (although it is often undervalued, see for example the biting essay of Richard Feynman on: Cargo Cult Science). When we try to replicate the work of others, we want to compare our data to their data. This is complicated by the fact that quite often data are only available as graphs. Engauge is a good, free digitizing software that helps with this.
Archiving the data after publication
As mentioned in the last section, replication is an integral of our scientific work. This also includes that we retain our raw data and all statistical analyses for later use by other investigators (most journals expect us to retain our data for at least 10 years; please read this as: "for the rest of your lifetime").
Therefore, if you published an article as first author and with me as supervisor, I ask you to do the following after the manuscript was accepted for publication:
- Typically you should make your data openly available (open data).
- In addition (!), please make sure that all your data are available and accessible on our file server. This should include: All the raw data, all analyses, and all the files related to writing the article. It should also contain all important emails related to writing the article, e.g. correspondence with the editor, reviews, etc. and a README.txt file containing a short description of where to find the analyses, the raw data, etc. The file should be a plain text file (you can generate this in Word and save it as "text only", or in the Matlab Editor, or in Emacs, or in Sublime, or...).
2. Scientific writing
Writing a scientific manuscript / paper
Here is a short introduction to writing good scientific manuscripts: Gopen and Swan (1990). The Science of Scientific Writing. American Scientist (78), 550-558. ... and a nice talk by Steven Pinker on good writing. One take-home message of all this is that you have to take writing very serious and invest a lot of time to make your writing transparent. This involves many rounds of reading, re-reading, and re-writing with the sole purpose to make your arguments as clear and accessible as possible. If this sounds tedious: No, it is not necessarily. Clarity in writing helps to be clear in your own thinking and therefore can be fun (albeit, admittedly, is is not always fun...)
A guideline regarding the ethical aspects of writing a research article can be found at the pages of the Society for Neuroscience (SfN): Guidelines: Responsible Conduct Regarding Scientific Communication.
Writing a scientific paper with me
When you write a paper with me and you are first author (e.g., as a PhD student), I ask you to do the following:- Before giving a draft to me:
- Write an email, giving a short summary of what you did and in which state the manuscript is.
- If it is a revision, prepare in parallel the coverletter giving a detailed point-to-point response to the reviewers' and the editor's concerns. Typically, you should send the draft of this coverletter together with the draft of the manuscript to me.
- Allow enough time (typically at least one week) for me reading the draft and warn me a couple of days before that you are going to give me something to read soon.
- Pay close attention to formatting, citation style, references, etc. When reading a manuscript it can be very distracting to constantly have to correct these things. Under normal circumstances you should not postpone these things to later stages of your writing. If you have good reason to do so, make explicit in the above mentioned email.
- Run a spell checker.
- When submitting a paper or a revision:
- Be aware of and obey all deadlines.
- Carefully check the journal's "guidelines for authors" and obey all requirements (formatting, etc).
- Be sure to add an appropriate "Acknowledgments" section, mentioning all grants and funding agencies that were involved (for examples see my publications). It is very important that we mention all grants, otherwise the paper will not be counted for the grants, which essentially means that it look as if you had been lazy and we will get problems acquiring grants in the future.
- If it is a revision: Consider whether it is practical to mark everything that has changed relative to the original, submitted version (e.g., by using a yellow background). This does not always make sense but can help the editor, the reviewers, and me to focus on the changes. Some journals even require this.
- Ask me before you submit whether it is OK to submit.
- After submitting: Send me the final, submitted version of the manuscript. Typically you get a PDF-"proof" of your submitted version. Store this on our fileserver and send also a copy to me and also to the rest of the group.
- After your paper is accepted:
- Be happy! Typically you have worked app. 1-3 years for this moment, sometimes considerably longer. So it is time for a little party...
- Place an APA-style citation of your paper on your home-page, marked as "accepted for publication by JournalName" and send also to me
- Typically, journals do major formatting and some editing. The copy-editor is in charge of this and will send you (a couple of weeks after your paper was accepted) page proofs of the final to-be-published paper. The copy-editor will not warn you beforehand, but will expect you to control and correct the page proofs within 24-48 hours. Your job is to control whether the page proofs correspond to the final, submitted version. You need to do this very carefully, errors cannot be corrected later. Controlling the page proofs involves reading the page proofs from start to end, including figure legends, footnotes, references and controlling on a word-by-word level critical passages (e.g., all data in the results section. Data should, of course, not only be compared to the final, submitted draft but also to the original printouts of your data-analysis programs). Also check the Acknowledgments section again and make sure that all relevant grants and funding agencies are really mentioned. At this stage we are typically not allowed to deviate from the final, submitted version (we could in rare cases, e.g., if you found errors in the results section, but we might have to pay a hefty fee for doing so, because depending on the changes the formatting might have to start all over again). Also, of course, send me a copy of the page proofs and of the corrected page proofs and keep a copy on our file server. The page proofs can already be given to colleagues who want to read the paper.
- After the paper is (finally) published you typically get a PDF-file of the final, published version (this is different from the page proofs. E.g. now containing page-numbers). Please send a copy to me and update your home-page to show the full, official citation.
- Store all relevant data and the manuscript for the rest of your lifetime. See above: "Archiving the data after publication"
Writing reviews
Writing reviews is an integral part of our scientific work and the quality-control provided by the peer-review system is considered a hallmark of modern science. As soon as you have published your first scientific article, you might be asked by editors of scientific journals to review manuscripts that were submitted to the journal. When that happens, please talk to me shortly (nowadays, there are also 'predatory journals' around with which you do not want to be associated). For writing the review: Here is a collection of short tutorials and discussions of how to write a review for a scientific journal:
- Brainard, D. (2000). How to write an effective manuscript review. Optics & Photonics News, 11(6), 42-43.
- Benos, D. J., Kirk, K. L., & Hall, J. E. (2003). How to review a paper. Advances in Physiology Education, 27 (1-4), 47-52.
- Tutorial by the American Psychological Association (APA)
These tutorials should be enough to get you started. If you face any problem or are unsure about specific aspects: Talk to me. Nevertheless here a couple of more advanced resources, just in case: A guideline regarding the ethical aspects of writing a review can be found at the pages of the Society for Neuroscience (SfN): Guidelines: Responsible Conduct Regarding Scientific Communication. There is also a committee on publication ethics (COPE) formed by editors of peer-reviewed journals. They give detailed advice (but mainly for editors), including case-studies. See also: Council of Science editors and World Association of Medical Editors.
Word processing software
Typically, we use either LaTeX or MS-Word. Here some hints to decide, which to use:
- I encourage students to write with the text-processor they know best. So, if you know Word better, that is typically fine.
- I myself often use LaTeX and our more mathematical papers also often do so. But that is not necessarily a requirement. We should use that program that allows you and us to work most efficient and fast.
3. Mailing lists
Two mailing-lists are most important for our work and I recommend that you subscribe to these: Vision Science Mailinglist (visionlist) and Color and Vision Network (CVNet). If you have a special question, it is always worth having a look at the archive of visionlist mailing-list.4. Being a graduate student
Find here a nice discussion of what it is like to be a graduate student. Note, however, that part of this discussion is only related to the American system, not the German...If you want some more serious information related to the situation in Germany, you can have a look at: www.hochschulkarriere.de and: www.academics.de.