DDI Lifecycle: Moving Forward

Motivation

The DDI (Data Documentation Initiative) metadata standard, created since 1995 to document social science research data, has in recent years become relevant to new user groups, including the official statistics and medical research communities. In order to respond to these new users, DDI is developing a model-based specification (DDI Version 4) that can be expressed in XML Schema, RDF/OWL Ontology, relational database schema, and other languages. Such a data model will make it easier to interact with other disciplines and other standards, to understand the specification, to develop and maintain it in a consistent and structured way, and to enable software development that is less dependent on specific DDI versions.

Throughout the past year, content modeling teams have been working virtually to model DDI 4 to ensure that it can document a broad spectrum of data. This year’s Dagstuhl “sprint” will focus again on content modeling, bringing experts face to face to make accelerated progress.

Goals

The 2014 Dagstuhl workshop will extend and build upon progress made during the year to develop and implement the model in a community-driven way. Work will also continue on fine-tuning the production framework to automate as much as possible in a model-driven environment for the development of the standard. The goal is to move quickly to a basic version of the new model that can be released for review iterations.

This year there will also be a focus on incorporating enhanced data citation into the DDI model-based specification. With funding from the U.S. National Science Foundation, the University of Kansas and the University of Michigan are bringing together experts in data citation who will use the week at Dagstuhl to model data citation across the research data life cycle. Research data are important scientific contributions, adding to the global knowledge base and to our understanding of the world. Documentation standards like DDI need to incorporate mechanisms for attribution so that individuals can receive credit for their contributions to research datasets through proper data citation. Representatives from other metadata standards will collaborate with DDI modelers in adding comprehensive citation support to the DDI model. A taxonomy for the role of contributor to a dataset will also be developed. This work will provide a unique opportunity for cross-fertilization of the different metadata standards.

Expected Results

The 2014 workshop will provide a forum for interested participants with both a substantive and technical focus to contribute to a re-envisioned model-driven DDI specification. Deliverables from the workshop will include drafts of the model and its documentation, which will then be made available for public review, and mappings to other standards. The workshop will also produce a set of best practices for citing data at all levels and providing attribution to all dataset contributors. These best practices could be applied to other metadata standards in other disciplines.