Data governance and frameworks
In March the IRISS project team came together to talk about what social scientists need to help them do their research, that is:
- their requirements for access to longitudinal, satellite, sensor, private and social media data held in public and private organisations
- the different methodologies employed to integrate social science data with geospatial data and with vocabulary data and the importance of developing best practices
- how survey and analysis tools and secure environments are employed and assist their work with data that’s often personal and therefore sensitive
- the careful judgements they make for collecting, selecting and curating data based on their research questions and the importance of capturing provenance information to support research transparency and furthering scholarship
After fourteen workshops with 15 domain experts in social science, ethics, informatics, geospatial science, data science, and technology what became abundantly clear was that new data governance and frameworks need to be created to set the foundations in place for integrated research infrastructure for social science. Frameworks will be created for: data curation, data integration, and survey integration. It is critical for a range of data sources to be examined to ensure the frameworks are generalisable and also extensible and also to inform how new data products and integration methodologies are delivered to establish good data science practices as benchmarks.
The IRISS project team are starting their work with longitudinal and survey based social science datasets to capture the techniques and methods of data integration (with geospatial and vocabulary data). Five personas have been developed: data scientist/analyst, researcher (data collector), researcher (data analyst), policy-maker and data analyst. This is to guide project activity towards meeting the needs of social science researchers and those that use social science research data and findings in policy setting.