Why bioinformaticians don't get no respect

by Paul Agapow
in science

tagged bioinformatics, academia

It's a common cry amongst working bioinformaticians that they're unappreciated, undervalued and generally "get no respect". While people love to complain, from discussions with peers and colleagues, the same stories come up again and again:

  • Not being consulted when projects are planned
  • Technical advice and results not taken seriously
  • Being last in line when resources are allocated
  • Doing a wide array of highly technical tasks (e.g. genome assembly, biostatistics, integrative biology), yet still be referred as "the database manager"
  • Being expected to produce results from incomplete, fragmented and statistically tiny samples
  • Assigned a poor position in author lists and sometimes omitted entirely
  • Career and advancement not considered important
  • As a single person, being expected to handle "all of our bioinformatics" regardless of workload, provision of necessary facilities and whether you possess the necessary specialities
  • Being expected to work long stressful "scientist" hours, while being treated as a technician

How did we get here? Why are bioinformaticians held in such low regard? To cut to the chase, I don't have a single answer here. But I do have several theories.

Theories

No one gets any respect

Proposal: This is academia and science. It's a zero sum game. Everyone's climbing the same greasy pole and fighting for the limited resources. Everyone is under stress, everything is under-resourced. Social niceties are pushed to one side to be replaced with "what have you done for me today?" Why should bioinformatics be any different?

Counterpoint: True, but this can't be a complete explanation. Other specialities don't have the job title problem, or get left out of planning discussions.

It'll take time

Proposal: Bioinformatics is too new and academic culture hasn't yet adapted to or understood it. Non-bioinformatic academics don't yet appreciate the way it works, seeing it as partially magic, partially ill-formed voodoo. Give it time.

Counterpoint: Certainly, this was true once upon a time. Certainly, some parts of the academy are slow to adapt (try employing a "research software engineer" and see what your HR department reacts). But we've had nearly a generation of working bioinformaticians now. Some aspects of science and technology and business has changed radically (GWAS, open access, mega-journals, etc.) and the academy adapted to that. Why not bioinformatics?

Bioinformatics looks like IT

Proposal: Bioinformatics is inherently computational, looks and acts a lot like IT and so it gets treated like IT, a fungible support service:

  • Early practitioners came from the IT side and many still do. Bioinformaticians leaving science will often move into pure IT.
  • Bioinformaticians look and act like IT workers: largely male, hyper-casual dress, an obsession with technical details, an obscurantist style.
  • Bioinformaticians are often referred explicitly as "computer guys", with bioinformatics and informatics / IT tasks are being functionally interleaved and conflated. A cluster needs to be set-up for an analysis, the lab needs a website or database, someone can't figure why a program isn't working: these are all handed to the lab bioinformatician.
  • Bioinformatics is treated by outsiders like a black box.
  • Bioinformatics "skill" is often equated with being the master of an obscure technical stack.

Counterpoint: None. I think this is completely true.

Bioinformatics is blue collar

Note: I can't find who first made this distinction or used these terms but it's an observant one.

Proposal: scientific tasks can be divided into white collar (creative, high profile, seen as "output", "thinkers" and "doers") and blue collar (essential but seen as services or purely technical, that support white collar workers). Essentially, researchers versus technicians. Bioinformatics is blue collar.

Counterpoint: The white-blue collar divide is absolutely real (quoting a colleague of mine, "in academia, you do not want to become known as a 'doer'".) While many bioinformaticians willingly slot themselves into blue collar roles, it's unclear what globally labels a speciality as one or the other. Why is someone that coaxes microbes to grow in culture or chains together a drug molecule a white collar worker? Why is it that scientists doing bioinformatics that is labelled as something else (e.g. evo devo, gene regulation) get treated as white collar? (Dare I say it's because their work is actually about biology not obscure technical shibboleths?)

The work is not tangible

Proposal: bioinformatics is "thought work" with little physical output and so is easy to forget about or discount.

Counterpoint: This is a problem but it's not one with mathematicians or statisticians, at least not to the same extent.

Bioinformatics isn't worthy of respect

Proposal: The bioinformatics literature and community contains a lot of obscure, deck-chair rearranging about obscure technical details as opposed to than scientific conversation.

Counterpoint: Fair cop. This is not to devalue methodological assessment or establishment of best practices. But the most visible conversations in the bioinformatic space sound like car enthusiasts barracking for their favourite models and waxing lyrical on how they spent the weekend rebuilding an engine. In a way, this is just another form of the "IT" issue. It doesn't sound like science.

Conclusions

As said, I don't have an answer. And the answer is probably a mix of all of the above. But if I was to boil it all down to a single statement, it might be:

Bioinformatics doesn't look like science. Sometimes it doesn't even look like work.

Before you ask how to fix this, should it be fixed? Bioinformatics is a broad, broad church and trying to fit everyone under one image or label (orone set of expectations) is not going to work. Many of the people who fill "blue collar" technical posts are happy with that and trying to force everyone to fully commit to being "a scientist" (white collar) incurs a new set of problems. Perhaps what we need more is clarity about roles and responsibilities. If you're supposed to be a scientist, do science, talk abdout science and ask to be treated like a scientist.