What are some fields in which a professional programmer (specializing in Data Science technologies) can pick up hobby projects that can actually contribute something to that particular field.

I have heard rumors that astronomy is a field where hobbyists make serious contributions, is it true? What is the reason for this, i.e why astronomy of all fields has this special feature?

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    Given your background I'd say machine learning is the obvious candidate. There is a huge need for quality implementations and this kind of software receives the value it deserves in the field. You can publish software, too. Commented Jul 16, 2015 at 15:08
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    Since this is an academia site, I assume your question is about fields in which a hobbyist can make contributions to research. Is my understanding correct?
    – ff524
    Commented Jul 16, 2015 at 15:10
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    While it's true that software is typically appreciated in ML, I would argue that's because PIs in that field can and do build software, so just being a good programmer is less of a relative distinction and might not make up for the lack of formal experience. On the other hand, in many social sciences great datasets go under-utilized due to a lack competent programmers and analysts.
    – Tim
    Commented Jul 16, 2015 at 20:42
  • @Tim...can you give an example...what field of social science.
    – Victor
    Commented Jul 16, 2015 at 21:05
  • You can, in principle, contribute to any field. You'll have to get up to speed in the field, and maybe there's some buy-in (for equipping a lab, say), but if you write up something worthwhile, there is nobody who'll stand in the way of publication.
    – Raphael
    Commented Jul 17, 2015 at 9:22

8 Answers 8


Traditionally almost all amateur contributions to astronomy came from observational hobbyists finding comets and supernovae, which benefit from having more eyes on the sky and don't require the absolute largest telescopes. Most of the sky goes unobserved each night, so just looking for transient phenomena often pays off. People like Joseph Brimacombe are well known to supernova observers, since they often are the first to see new supernovae. Note though that these people often invest significant personal resources into their hobby, and it's not clear what will be left for amateurs once the next generation of survey telescopes is built.

In terms of data and code, I've heard of some hobbyists helping astronomers find exoplanets. This is less solo work than the observations -- these people are often formally or informally members of research teams. There are all sorts of clever data reduction techniques being developed these days, but do note they are not generally pure abstract data analysis -- much astrophysical insight goes into the data pipelines these days.

Zooniverse was already mentioned. This is a collection of "citizen-science" projects, and it has more than its share of astronomy. This is no surprise since astronomy has enormous datasets, and in fact Zooniverse grew out of a single galaxy classification project. These projects are a nice way to get your feet wet with various data reduction projects, but note their focus in on crowd-sourcing results (usually to develop training sets for their own algorithms, which eventually replace the crowd-sourcing). If you want to actually develop algorithms and apply them to large datasets, you can try getting in touch with the people behind a particular crowd-sourced project and ask for more data to work with on your own. While sometimes the latest astronomy data is kept private for a time (no one wants to spend all the time and effort getting data only to have someone else swoop in and publish all the results), much of it is public or sharable.


With programming you can make a contribution to virtually any industry.

There's always a need for better, faster, smarter software that allows industry workers to get ahead of competitors and make the work day more efficient.

There's also always a need for open domain software which, if created well, almost always gets a huge community such as GIMP.

As a developer myself I can say that most worth while contributions will take more than just yourself and you may want to connect with other developers that want to help.

Astronomy software can show constellations, star formations, and even have algorithms that predict where a planet or solar system may be and the probability that human or extraterrestrial life could be sustained on said planet.

  • Agreed -- my favorite part about programming is that it's one of the only fields I can think of where self-learned people are actually more effective than university-trained, because of the nature of slow-to-change curriculum vs. the rapid change of IT. Of course, this doesn't apply to the MITs and Stanfords out there, but in my low-tier UC/State School experience... yeah.
    – HC_
    Commented Jul 16, 2015 at 19:29
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    Self-thought programmers usually have gigantic holes in their knowledge of algorithms and basically everything fundamental to CS. Teaching yourself Swift is something a competent programmer can do in a week, understanding 4 years of algorithms, cryptography etc. is not.
    – Davor
    Commented Jul 17, 2015 at 6:56
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    -1 "With programming you can make a contribution to virtually any industry." What does this have to do with Academia Stack Exchange? This whole answer says nothing at all about academia. Commented Jul 17, 2015 at 7:00
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    +1 For mentioning tool building. Even if there isn't room in a field for "doing science" directly, there's plenty of room to make tools to help out researchers. For example, coming out with a better (and freely available) lab inventory management system, or a better way to stay on top of the literature, or (insert solution to common topic-specific problem) would do wonders to advance research, even if it doesn't give scientific results directly. -- Most scientists aren't programmers and waste time on things trivial for a programmer to solve.
    – R.M.
    Commented Jul 17, 2015 at 15:48
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    @h22 - if you don't know how it's implemented, you don't understand how to use it properly.
    – Davor
    Commented Jul 20, 2015 at 6:14

Computer Science is a good field for an independent researcher: the main publishing venues are conferences with specific deadlines, not journals, so you can get some feedback much faster. The downside is that you need to pay non-trivial amounts of money to attend conferences.

This year I published and presented two papers at CS conferences as an independent researcher, and it was a very good experience (except using my paid time off and my own finances).

Within Computer Science there are many subfields for a professional programmer to contribute, especially the applied ones. A good place to look for conferences is http://wikicfp.com/cfp/.

  • I always thought of computer science as the study of algorithms and mathematics that is used to solve/automate problems in other 'fields'. My question was about these other fields. Can you elaborate with examples what kind of research work you did in CS field?
    – Victor
    Commented Jul 16, 2015 at 17:55
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    We demonstrated that declarative programming languages are fast enough and can be better suited for solving some kind of programming competition problems than mainstream programming languages: arxiv.org/abs/1412.2304, arxiv.org/abs/1504.00977 Commented Jul 16, 2015 at 18:02
  • can you elaborate what it takes to become independent researcher(e.g. like in your case?). how to find potential areas where to contribute(e.g. I am referring also to programming)
    – user37297
    Commented Jul 16, 2015 at 20:29
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    @Giorgi I just experimented with a not very popular programming paradigm, found some interesting things, wrote a paper, submitted, got rejected, found a co-author, improved the paper, resubmitted, got accepted. Commented Jul 16, 2015 at 22:06
  • @SergeyDymchenko: Thanks for response. Interesting parts about your response are like "found a co-author"-how??. Also what is your background in general have you published before? I am asking because myself I am interested in such route and would appreciate advice.
    – user37297
    Commented Jul 16, 2015 at 22:10

Astronomy may be such a science in some degree, see comet hunting. Or try Zooniverse.

  • Zooinverse looks awesome, thank you. Not sure about comet hunting, does not use programming skills...looks more like observing night sky with a telescope.
    – Victor
    Commented Jul 16, 2015 at 19:50
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    Most observations these days are carried out by comparing photographs taken some time apart. A perfect use of your programming skills. For a good description of how this method is used and what you can contribute take a look at "how I killed Pluto"
    – Stevetech
    Commented Jul 17, 2015 at 13:27

In numismatics (the study of coins) a lot of serious research is still done by amateurs (often collectors). Access to national collections and other research resources is available in most countries and non-academics frequently publish.


To answer the question in your title, there are several aspects of biology where amateur contribution is frequent. For example marine biology where professional divers and other people who are frequently at sea for business (like instructors or tour guides) contribute to wildlife observation, documentation and sometimes tagging. The same apply for ornithology and the study of mountain wildlife. I recall hiking in the Grand Teton park and seeing signs asking hikers to report sightings of mountain goats and bighorn sheep, preferably with time and date and the exact position.

There is also this project by NASA that welcomes general public's contribution on a large snowflake database (I know there was a famous physicist who was studying snowflake formation as a hobby but I can't remember which one it was. If somebody know, they are welcome to edit).

As for the specifics of contributing with computing you could look into plant morphometrics.


Many of the sciences (biology and chemistry in particular) are getting themselves into fields where the datasets they are dealing with are becoming increasingly large and complex. There is a definite need for software that can make data analysis more efficient.


If one studies the advances made in unmanned aviation, it quickly becomes clear that the hobby communities have been a significant force in the development of small unmanned aircraft. Beginning in the early '30s, radio controlled model aircraft were being developed by those pushing model aviation beyond free-flight and U-control. As the FAA defines radio controlled model aircraft as "unmanned aircraft." the history of unmanned aircraft systems would be incomplete without pointing out the contributions of countless "hobbyist" scientists. Among them, Walt and William Good, and multiple world record holder Maynard Hill, stand out as pioneers in the field.

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