RDM makes data analysis more effective and efficient Following the results of our analysis of researcher’s relation to data, we do think that the argument can touch researchers and convince them to seek for help and information about RDM questions. However, we would need a stronger evidence that it is actually true, as well as an understanding of what part of RDM is particularly important for data analysis. So…
latest change: 2018-10-15 Here we are, the first real output of this outreach eeFDM project is here, have a look at our video available on figshare at https://figshare.com/s/e2b14570b5991931c92c It will be used as a generic (front credit) for longer videos with more content, we will probably start with a video about finding the data (avoiding data loss). Do you think you will use the video on your website and talks?
original at https://politicalsciencereplication.wordpress.com/2017/11/22/what-has-reproducibility-promotion-done-for-me/ Summary: long term benefits on getting grants, collaborators, visibility and a different (interesting) profile on the job market. It is pretty difficult to show tangible benefits. But I’m noticing more and more now that being a data champion is not a distraction; it’s an important facet of my profile that has helped my academic career in many ways: Grant success: My project “Fostering Transparency in Government Institutions and Higher Education” has received funding from the British Academy.
modified from http://blogs.lse.ac.uk/impactofsocialsciences/2018/03/20/what-factors-do-scientists-perceive-as-promoting-or-hindering-scientific-data-reuse/ and the article DOI: 10.1371/journal.pone.0189288 (http://doi.org/10.1371/journal.pone.0189288) Interesting conclusions: 1. researchers who re-use the data are different from researchers making data open for reuse 2. expressed lack of trust in reused data was not a factor explaining a lack of data reuse: while trust is a problem per se, it does not impeede data reuse. 3. there is a correlation between data reuse and perceived efficacy of data reuse (in contrast to the authors, I am not infering in which direction this might be causal).
The very first Data Management Engagement Award, a competition sponsored by SPARC Europe, the University of Cambridge and Jisc to elicit new and imaginative ideas for engaging researchers in the practices of good Research Data Management (RDM). Our proposal is to link RDM with the open science movement via the Wikimedia suite of tools. Basically just share yours or others’ openly licensed research material via Wikimedia Commons to create an aggregated resource that can be used to improve Wikipedia.
Method Here, we use the text collected and analysed so far (mostly via browsing the web, few direct contribution from the crowd), comparing it to a report from the research data alliance report. Both reports can be found as blog posts found under the category analysis. Summary We focused our analysis on three interesting content: Marketing strategies (how to reach researchers), arguments for research data management, and stories to tell.