Going back to basics – reusing data

It is almost a year since the first set of data was gathered to analyse journal articles, and now the benefits of saving data well is becoming fruitful. Two things are happening that means we are getting the basic figures out, dusting them off and looking at them again. The first is a paper about the development of a model journal research data policy, which is being co-authored by the JoRD team members, and the second is in response to certain questions that various people are asking.

The idea of creating a model policy emerged from the mass of data that was being found in the analytical process, and it was based on what journals were already doing, and suggestions from the report “Sharing Publication-related Data and Materials: Responsibilities of Authorship in the Life Sciences” (Committee on Responsibilities of Authorship in the Biological Sciences, 2003,  http://www.nap.edu/openbook.php?isbn=0309088593). The report was the outcome of a workshop in the United States which involved Biological Scientists. The five principles and ten recommendations stated in the report were strongly in favour of open access to the data that underpins the research reported in published articles.  A summary of the principles and recommendations can be found here: http://www.councilscienceeditors.org/files/scienceeditor/v26n6p192-193.pdf. The report suggested that the data could either be included into the article , or deposited in a reputable repository and linked to the article. The focus of the first model data policy was therefore based on the rather patchy and inconsistent set of policies that were found, from less than half the journals we analysed, and a report which was biased towards one scientific discipline.  It was decided to compare the initial model data policy with the needs of the stakeholders, which were examined at a later stage in the JoRD project. This has entailed, not only going over the data gathered from the stakeholder interviews and questionnaire, but also digging retrospectively into the reasons for the initial model criteria to be chosen.

The second reason for examining the basic data has come from interesting questions asked by a number of bodies that know about the JoRD project, and therefore assume that the JoRD team are experts in the field of Journal research data policies, an assumption that is becoming increasingly true as more questions are answered. In order for the questions to be answered, the data needed to be looked at from a different perspective. For example, to answer “How many journals make sharing a requirement of publication?” the original data set was re-examined and journals counted, because the original analysis was looking at the number of policies, some journals having up to three different data policies. Here follows a table with figures from a journal perspective:

Results of Journal Survey
Total no. of Journals surveyed	371
Total no. of Journals with data sharing policies	162
Total no. of Journals that make sharing a requirement of publication	31
Total no. of Journals that enforce the policies	27
Total no. of Journals that state consequences for non compliance	7

This process is an illustration of the way that well organised data, saved  safely, and as in this case in digital form, can be re-used after a particular project has ended. Surely it is generally after research has been concluded that questions arise and the iterative process of dipping in and out of data to validate or extend the research then begins. The moral of this blog post? Manage your data well because you never know what you will asked.