Mike the Mad Biologist

Last week, I wrote about the problems facing genomics and the concept of ownership of data. While I am sympathetic to researchers’ career needs under the current system, I don’t think we can, in good conscience, let that get in the way of rapid data release, especially in applied areas.

I, and others, cast this as a conflict between individual researchers and the larger community, but there was a third part that was missing: universities. To the extent that universities care about–and desperately need–grants, altering how funders determine what a successful outcome is critical. That’s why I found this interview with Cameron Neylon about ‘open science’ relevant (italics mine):

I think there are two different main classes of reason why funders support science. One is to build up knowledge, and the other is to support the generation of economic and social outcomes from research and innovation…

Our current metrics and policies largely optimise for prestige rather than knowledge building or social outcomes. On the assumption that most funders would choose one of these two outcomes as their mission I would say that the simple things to do are to actively measure and ask fundees to report on these things.

For knowledge building: Ask about, and measure the use and re-use of research outputs. Has data been re-used, is software being incorporated into other projects, are papers being cited and woven tightly into the networks of influence that we can now start to measure with more sophisticated analysis tools?

The re-use of data is the key point. If researchers can be rewarded–and acknowledged successful completion of grants seems to be a pretty good standard–based on the broad usefulness of the data they generated, this would go a long way in reducing the potential for conflicts between genome centers and individual researchers.

Comments

  1. #1 Youryu
    December 21, 2010

    current metrics and policies largely optimise for prestige rather than knowledge building or social outcomes. On the assumption that most funders would choose one of these two outcomes as their mission I would say that the simple things to do are to actively measure and ask fundees to report on these things.
    For knowledge building: Ask about, and measure the use and re-use of research outputs. Has data been re-used, is software being incorporated into other projects, are papers being cited and woven tightly into the networks of influence that we can now start to measure with more aaa sophisticated analysis tools?

    The re-use of data is the key point. If researchers can be rewarded–and acknowledged successful completion of grants seems to be a pretty good standard–based on the broad usefulness of the data they generated, this would go a long way in reducing the potential for conflicts between genome centers and individual researchers

  2. #2 metin2 hile
    December 22, 2010

    For knowledge building: Ask about, and measure the use and re-use of research outputs. Has data been re-used, is software being incorporated into other projects, are papers being cited and woven tightly into the networks of influence that we can now start to measure with more sophisticated analysis ..thanks.

  3. #3 tek link
    December 22, 2010

    actively measure and ask fundees to report on these things.
    For knowledge building: Ask about, and measure the use and re-use of research outputs. Has data been re-used, is software being incorporated into other projects, are papers being cited and woven tightly into the networks of influence that we can now start to measure with more aaa sophisticated analysis tools?

    The re-use of data is the key point. If researchers can be rewarded–and acknowledged successful completi

  4. #4 Oyun Hilesi
    December 22, 2010

    two outcomes as their mission I would say that the simple things to do are to actively measure and ask fundees to report on these things.
    For knowledge building: Ask about, and measure the use and re-use of research outputs. Has data been re-used, is software being incorporated into other projects, are papers being cited and woven tightly into the networks of influence that we can now start to measure with more aaa sophisticated analysis tools? thaks.

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