[Open] Science Sunday – 15.08.10
News hit the stands about a new research collaboration to find biological markers for Alzheimer’s disease (read the stories in the New York Times and the Wall Street Journal). (HT @atreolar on Twitter). One thing that sets this collaboration apart was that the work being done would have researchers
“share all the data, making every single finding public immediately, available to anyone with a computer anywhere in the world.”
The advantages of sharing data were made clear with respect to this project in the article:
“Different people using different methods on different subjects in different places were getting different results, which is not surprising. What was needed was to get everyone together and to get a common data set.”
And this is a very strong argument for data sharing. But as interesting as the story itself is, I find more interesting some of the issues it identified with respect to scientists sharing data at such a wide scale. Specifically this paragraph brought back some things to mind:
“At first, the collaboration struck many scientists as worrisome — they would be giving up ownership of data, and anyone could use it, publish papers, maybe even misinterpret it and publish information that was wrong. “
This (with different grammatic construction) is the argument floating around. We (scientists) may all see the advantage of data sharing, but are we willing to ‘give it up’?
If you ask scientists many of us would probably say that we do science for a specific purpose: try to help find a cure for a disease, solve some environmental problem, to contribute to human culture through the creation of knowledge. Data sharing makes us put our money where our mouths are.
But is it that easy?
I would argue it isn’t. Even when we may be willing to put our data out there, to have others use it and interpret it, there is a reality we still need to face: our hiring and promotion committees. And these look at our scientific output as ‘papers published’.
There has been a lot of chatter on what the values of the papers are: should impact factor matter? Should we be looking at article level metrics? But either still look at the papers. Should we stop valuing papers and start valuing datasets?
I brought this issue up at the Data Matters MoRST meeting I attended. The current PBRF system is incompatible with data sharing. It still measures ‘output’ as individual papers. And whether I like it or not, my University’s funding (and my ability to survive in the system) depends on me satisfying these criteria. So to promote data sharing, this too needs to change.
I wonder what would happen next time I apply for promotion if instead of listing my publications on my CV I were to list my ‘datasets’: This is the data I have generated (and made public), and this is how it has been used by me and by others. Wouldn’t that be a real measure of the impact of my work? Does it really matter ‘who’ used the data to advance knowledge? Or in other words, has the time come for ‘Data Level Metrics’?
Perhaps if we gave data the same hierarchy as papers when it comes to evaluating performance, people may quickly learn that by putting the data out there the impact of our work may be easily increased (and measured). And we may be quicker to put it out.
On other news:
The Open Science Summit‘s opening session are now online thanks to ForaTV. It was a great opening session to be at, and I am glad I managed to make it there. Unfortunately I wasn’t able to stay for the rest of the meeting.
At the same time that this was happening, the government of New Zeland released its Open Access and Licencing Framework (NZGOAL). You can read about it on the Open Knowledge Foundation website, which has links to all of the documents. This is indeed good news for data sharing in New Zealand. And when I returned from my trip I found an email from The Creative Commons Aotearoa New Zealand informing me that I had been selected as a member of the CCANZ Advisory Panel.
I want to thank CCANZ for allowing me to be part of this panel, it is indeed an honour and I look forward to the good things that promise to come out of it.