Julia Stoyanovich welcomed everyone as the main speaker and introduced the common theme of the conference – Responsible Data – focusing on the reality of statistical bias in data-processing algorithms & its societal impact.
The speaker’s proposal to tackle this issue was by enforcing the following aspects:
- Algorithmic transparency (not just releasing source code, which can be unnecessary and often insufficient)
- Algorithmic transparency requires data transparency,
- Data transparency is not synonymous with making all data public but should release it whenever possible, inc. releasing data selection, collection, pre-processing methodologies, provenance, quality info. known sources of bias, privacy preservation statistical summaries of the data.
- Data transparency – helps prevent discrimination and enables establishment of trust.
- Technology alone is not enough. We also need regulation and civic engagement, something we should drive through engagement with the public, both technical and non-technical.
Working Group FAIR Data Maturity Model
- The meeting gathered around 60 attendees from all over the world. The discussion went around the scope and methodology to create a common set of core assessment criteria for FAIRness via a bottom up approach: definition, development, testing and delivery.
- We continued to discuss whether this assessment should be automatic (done by machines/algorithms) or manual, using examples of the volume of data & practicality considerations. We agreed that the scope should be cross-disciplinary rather than domain specific.
Joint Meeting: From observational data to information
- Two Information Groups were introduced and included aspects of bringing raw data to usable information for research, and VREs, Science Gateways or Virtual Labs. These were followed by a number of different talks including one that raised much interest about a method for Annotating Data (implemented using a MongoDB separate from the data) and tools for measuring quality of preserved data.
- I gave a presentation introducing the SKA/AENEAS project and the plans for a Science Gateway and agreed with the Chairs of the groups to continue engagement until the end of the project.
Meeting: Assessing FAIR Data Policy Implementation in Health Research
- The meeting introduced the new FAIR4Health project and the landscape analysis it will conduct to assess FAIR implementation in health research.
- I mentioned the importance of engaging with existing eInfrastructures to help most important outputs, workable implementations, e.g. ELIXIR and AAI aspects