15th European DDI Users Conference, Ljubljana

Rich, standard-based metadata can a) improve the fulfillmentfulfilment of the need for better documentation for researchers and other users; b) improve efficiency by providing infrastructures that drive data collection, data processing and dissemination (e.g. metadata-portals); c) improve quality of our products and processes. There has been increasing interest in metadata in Europe in the context of building the European Open Science Cloud (EOSC). Papers describing innovative solutions covering the parts of or the whole life-cycle from collection to dissemination based on metadata are encouraged. Papers focusing on metadata driven production are welcomed as well.

National and international statistical organizations share a need for inter-related standards like the Generic Statistical Business Process Model (GSBPM), the Generic Activity Model for Statistical Organizations (GAMSO), the Generic Statistical Information Model (GSIM), the Common Statistical Production Architecture (CSPA), DDI, and SDMX. We welcome papers with a focus on standards in the context of official statistics.

DDI is strongly focused on the principles of metadata re-use and interoperability. “Enter once and use many times” is a powerful paradigm that can lead to improved fulfillment of user needs, improved quality and improved efficiency. The FAIR principles emphasize the use of formal, accessible, shared and broadly applicable language for knowledge representation and use of vocabularies and references. Papers that demonstrate achieving interoperability using DDI, interaction with other metadata standards, or innovative ways to reuse, share and harmonize metadata are welcomed.

(Meta)data harmonization can maximize the value of large scale population research in health and social sciences for both documentation and processing purposes. DDI has rich metadata constructs such as Concept, Comparison, Group, ConceptualVariable and RepresentedVariable in DDI 3.x. We encourage papers which describe projects utilizing DDI or exploring DDI as a basis for harmonizing (meta)data.

The advantage of having good documentation on data is rarely challenged, but it is often left as the last thing (or maybe not even that) to do on a research project. This is because the benefits for researchers come largely from publication and not from the data itself. In this context, changing both the culture and the rewards for documentation and sharing of data might be seen as key motivators. We encourage papers exploring this topic with the focus on DDI and metadata.

As the “Open Data” movement – which aims to make data more freely available – gains more and more attention in science and humanities, especially in the area of government data, the value of data that are easy to access and not limited by restrictive licenses is acknowledged. By using “Linked Open Data” technologies the ability to create reproducible and transparent research is enabled. For both, high quality metadata that is standardized and machine-actionable, like DDI metadata, is crucial. We encourage papers in the area of Open Data and Linked Open Data with a focus on DDI.

The sharing of data or metadata is sometimes restricted due to privacy issues or property rights. Especially, but not exclusively, in health research there is the need to protect the privacy of persons to whom the data refer. In social sciences and humanities, data can contain copyrighted material like texts and photos. Access rights can be determined by well standardized metadata. Thus good metadata management enables the protection of research participants’ and researchers’ rights and ensures an organization’s investment in data and metadata. We encourage papers in the area of concepts or implementations of privacy and access control issues with a focus on DDI.

In the case of surveys, there is usually a clear distinction between data and metadata. However, for example, in the context of qualitative research the boundary between data and metadata is less clear-cut. This issue also arises with big data sources like Facebook and other social media. Ultimately what is perceived to be data and what is perceived to be metadata is defined by research questions. This poses some difficult questions for research ethics when release, use and access to data usually have governance, yet metadata conceivably does not. We encourage papers focusing on this area of tension with the background of DDI.

Machine learning and AI technologies offer the potential to create, evaluate and enhance metadata reducing the manual labor often associated with metadata production. We encourage papers which address the use and limitations of these technologies with a focus on DDI and related metadata such as ontologies, thesauri, controlled vocabularies and classifications.

The acceptance and adoption of a “standard” depends on the availability of re-usable tools and software to utilize it. Many new tools that leverage DDI are emerging, and they target different parts of the data life cycle. We encourage papers showcasing tools and software which make use of DDI or parts of it.