This half-hour session will include the following two short talks:
A new open data badge: promoting trust and transparency through validation and verification(
Rebecca Pearce)
Studies by the Center for Open Science (CoS) and others have shown that digital badging can be an incentive for authors to participate in open science practices, particularly with respect to data sharing (Kidwell, 2015:
https://doi.org/10.1371/journal.pbio.1002456; Rowhani-Farid, Allen, and Bennet 2017:
https://doi.org/10.1186/s41073-017-0028-9). In general, the Open Data Badges utilized by CoS and others require authors to indicate their own adherence to open data sharing criteria in order to get their badge. Springer Nature are adding additional accountability into the process. We've created our own set of criteria in consultation with CoS and our Research Data Support team, designed to be applicable across disciplines, achievable for authors and easily verifiable by us. Badges are awarded to articles (not people) that are systematically checked for compliance with these criteria. The goal is to ultimately increase trust and transparency in open science by providing validation and verification of openly shared data sets to the benefit of authors and readers alike. This talk will summarize the most recent findings from this pilot and the refinements that are being made as we attempt to answer the following questions:
- What influence does badging have on data sharing behavior?
- What are author attitudes and challenges around data sharing, and how can we better support/incentivize data sharing?
- How much engagement are articles with badges receiving, and how does it differ from articles without badges?
- Would it be possible to automate badge criteria checks?
- Would it be possible to expand digital badging, so that it recognizes authors for participating in other open science initiatives, such as protocol sharing and reproducibility checklists?
Annotation for transparent inquiry: using open web annotation for transparent qualitative research(
Sebastian Karcher)
While templates for transparent research are well established for quantitative work, little work exists on the practicalities of transparent qualitative research. My presentation introduces Annotation for Transparent Inquiry (ATI), an approach developed by the Qualitative Data Repository in collaboration with the open source software non-profit Hypothesis (
https://web.hypothes.is/) and Cambridge University Press. Using open web annotations, a W3C web standard, authors annotate key passages of their publications with additional analytical information, extended excerpts, and links to underlying sources - qualitative data - stored in a trusted digital repository. ATI demonstrates the possibilities for transparent research beyond quantitative work, as well as the promise of using open standards and open source tools for research transparency.
