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28 Apr 2017

Plenary Reflections: RDA's approach to getting things done

I am a post-doc researching collaborative learning at EPFL in Switzerland. I have long been interested in Open Access and innovations in how scientists communicate, because I believe that the goal of our work should be to advance science and be able to build upon each others' work. Initially, most of my work was around activism for Open Access publishing, like choosing OA journals, or self-archiving pre/post-prints for the many journals that allow that. Later, I became interested in the publishing formats in themselves (PDF is not ideal), standards for metadata, etc.

I enjoyed conferences like OAI organized by CERN, because of the amount of technical innovations showcases - going beyond simply advocating for policy change.Since then, I have seen a growth in the use of integrated analysis/reporting tools like RStudio Knitr or Jupyter Notebook, the concept of executable papers, the idea of reproducability of papers and open data sets, data citations, etc.

However, all of these conferences were for researchers to present their individual research projects, and network - there was never any attempt by the conference itself to come up with standards and guidelines. When I applied to attend the RDA Plenary, I did not have a good understanding of what RDA was, and I imagined it was simply a very large conference of people concerned with data formats, standardization and sharing, where I could catch up on the cutting edge work done in fields relevant to myself, and perhaps network with people with similar interests.

The session which introduced beginners to RDA was immensely helpful, and quickly dispelled my preconceived notions about how RDA operated. I was introduced to the concept of working groups, interest groups, recommendations and processes. I was very impressed by how quickly RDA had grown over a few short years (not so strange that I had not heard about it before recently), and how committed it is to real, usable outputs, anchored in the relevant communities, and adopted by large organizations

It would be interesting to see other organizations work in a similar manner - I often feel that there should be much more collaboration between academics on a number of points, but often, conferences and incentive systems encourage everyone to pursue their own project, leading to publications, but perhaps not to any long-lasting impact. However, this is also one of the challenges for RDA, and perhaps one of the reasons why many of the attendees were not researchers or academics, but rather university staff (librarians etc), as well as people working for consortia, government, etc. Getting deeply involved in RDA obviously requires spending quite a lot of time on the nitty-gritty of researching existing alternatives, agreeing on a common text, etc. The upside is that you get to participate in the production of a long-lasting recommendation that could be implemented widely, and have a great impact. The downside is that a hiring committee or tenure committee might not even count this contribution as valuable at all (although that is hopefully beginning to change, and might also be different in different disciplines/communities). 

As I am progressing in my post-doc, and thinking about my future academic career, one of the things I am concerned about, is how to make my advocacy and research on open scholarship, open data standards, and "Science 2.0" an integral part of my research program, so that I can pursue these interests as part of my day job, and not as a side-thing or hobby. One approach could be to function as a link between wider communities doing innovative work in this field, such as RDA, and my own field of learning research, which is in many ways just beginning to experiment and think about these issues. I would be interested in hearing from other young scholars who are thinking about how to integrate their community efforts and contributions with future careers. And I am grateful to RDA for having exposed me to a large community of people working for better interoperability of data, and efficiency of science, and prompted me to reflect upon my own role in this process.

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