Due to the Covid-19 pandemic, this workshop was cancelled.
This workshop builds on the outcomes of two previous Dagstuhl Workshops in 2018 and 2019 on the alignment of standards and technologies for cross-domain data combination. The first two workshops in this series have produced draft guidelines and use case documentation to provide insight into the cross-domain challenges which form the focus of the ISC CODATA Decadal Programme on ‘Making Data Work for Cross-Domain Grand Challenges’.
Four initial Working Groups emerged from discussions at the workshop in 2019. This third workshop will act as a face-to-face meeting and as a sprint for them, following and augmenting their online collaboration.
Scope and Background
To face many of today’s global grand challenges, data is needed from different domains and disciplines, and from different institutional levels, and it must be interoperable to be useful. Research projects in such fields, whether for policy or scientific purposes, often involve the use of data from a wide variety of sources, ranging from specific, local data sets to those supplied by higher-level national and international organizations. A huge proportion of research effort is expended to integrate and harmonize this data so that a meaningful analysis can be conducted.
Global grand challenges require data coming from a wide range of domains and institutional levels, presenting us with diverse issues:
Semantics, classifications, and terminology must be clear not only across domains and national boundaries, but also vertically within chains of data reporting and use
Metadata specifications for different purposes must be comprehensible at a computational as well as human-readable level, requiring both harmonization/alignment and better machine-actionable models and techniques
The provenance and processing of data must be made explicit in a fashion which supports further computation, enabling machine reproducibility of findings
The connection between scientific micro-data and official statistics at the national and international level must be strengthened, to improve both usability and quality for policy and scientific researchers alike
This work brings together experts from both the world of official statistics and global policy monitoring data, technologists, and researchers with a scientific and academic focus. Technologies which address the creation, management and exchange of metadata will be central to this work, to support discovery, analysis, automated processing, and enhanced reusability of data. Further, the intersection of these technologies with machine learning approaches will be considered. A broad range of standard models and specifications in these areas will serve as a focus of the effort, looking not only at how such models can be aligned, but also how best to perform computation across them.