SPARC’s OpenCon 2017:The Four Pain Points I found for Making Research Data Open

[jrineakter]

What are the barriers preventing you from making data open in your institution? At the 2017 OpenCon Conference I met an energized and inclusive community from all over the world overcoming a variety of barriers, while pushing their respective open access missions. I learned first-hand about a few of these challenges while leading an unconference on open data licensing. A diverse group of folks attended, including grad students, post-docs, university librarians, policy advocates, a researcher, a data scientist and analyst.

opened the unconference, titled Lack of Open Data Licensing in Open Data Efforts, with the question: “What does open data mean?” The simple question led us down a rabbit hole of discussions around the various data issues in academia. Though the perspectives were diverse, there were a few shared challenges: how to encourage institutions to move from ostensible to earnest open data enforcement, how to make funders or universities default to an open data policy, and how to integrate better open data policies into grant applications.

So what’s preventing the application and enforcement of a clear open data policy? After reviewing the notes from the unconference, there were four main pain points that stood out:

Cut Out Vague Language
What does “sharing data” mean? What does “open data” mean? Though I was in a room with a dozen smart people from similar fields, the terms “sharing” and “open” were more subjective hong kong whatsapp number data than I realized. Therefore, the practice of attaching such nebulous terms results in very little guidance for the end user and can invalidate the intentions of the data provider. This leads me to my next point.

2. Set Clear Instructions
How is data used or not used? Using an established license is the most straight-forward way to provide guidance on the freedoms or limitations one has when using the data. What came up a few times in the conversation, was the now prevalent requirement by many funders for there to be an open data policy attached to a grant proposal. (Check out the American Heart Society’s to see an example.) Yet, often the policies are vague, and do not require applicants to provide formal licensing or terms in their open data policies. This leads me to my next point!

3. Enforce Rules and or Incentivize Compliance
Why should researchers and PIs provide an open data license? Often researchers are spread very thin as it is, and do not have the resources or training to know how to create a sustainable open data policy or how to share their data properly. In addition, the incentives for going the extra mile to publish data or research licensing terms are not necessarily there. For example, a lot of researchers still don’t know that statistics show open data result in more citations. In addition, if grant providers were more stringent about their open data policy terms adoption inevitably improve. Generally speaking, the requirements for open data policies for researchers applying for grants are relatively lenient.