What uses for artificial intelligence (AI) might we expect outside of the publication workflow? Some answers to this question can be found through the lenses of sustainability, justice, and resilience.
The RECODE project is an EU funded project designed to compile a set of generic guidelines for EU funders to use when forming research data sharing policies. The premise is that publicly funded data should be openly accessible to the public, because they have paid for it. The workshop signalled the end of the first work-package of the project. This studied stakeholder values and ecosystems, that is individual’s and scientific groups’ concepts of open access to data and an examination of current good practice in the area. Other topics such as the ethical considerations and the technological solutions of sharing data are to be tackled in other work-packages. This workshop was of particular interest to the CRC and Sherpa Services because we have recently conducted research into journal research data (the JoRD project; http://jordproject.wordpress.com) and because of the implications for funder’s policies in SHERPA/JULIET.
It was with some relief that we found that our findings about stakeholder perspectives were broadly the same as the RECODE findings; it shows that we were right! I gathered some extra insights from presentations by representatives from participants of the RECODE case studies. For example, there is not a clear difference of opinion on opening out research data between scientific disciplines, but there are many opinions within each discipline. It reminded me of the adage “when you put two academics together you get three different opinions”. It seems to me that it would be easier to sort the factions across disciplinary lines into “pro data sharing”, “contra data sharing” and “no-one would want our data because it is boring”. Another major problem of sharing data that became apparent is that the person who can interpret the data best is the person who collected it because data needs a context. In other words, the knowledge that the data reveals is stuck inside someone’s head, and it is very hard to make that openly accessible. This is the knowledge management problem of intellectual capital. One of the RECODE team expressed it as, a lot of knowledge is lost when you lose another post-doc.
Other issues were raised about technological infrastructure, data licensing, data citation, lack of standardisation of practice within the same fields, the simply practicality of opening huge data sets (the word peta-bytes was bandied about) and whether some sort of reward to an academic could be triggered for openly sharing their data. Overall, the workshop raised some interesting points, and I do not envy the RECODE project team in trying to reach a generic set of open research data guidelines for funders. This is a project that we will follow with great interest.
You can find more about the RECODE project on their website http://recodeproject.eu/