Scenarios for the DDI-RDF Discovery Vocabulary
Johanna Vompras, Arofan Gregory, Thomas Bosch, Joachim Wackerow, DDI · ICPSR Data Holdings · 2015
.. Introduction This document describes the scenarios which the DDI-RDF Discovery Vocabulary was designed to support. These are not formal UML use cases instead, they are scenarios for the possible use of the vocabulary, based on an analysis of existing search interfaces and known behaviors for those looking for research data. The process around these scenarios is to define them, posit the thinking of the researcher/user seeking to find data, to identify needed classes and properties in the vocabulary, and then to render the search as it might be implemented. An examination of the implementation of the searches/queries (in SPARQL) will show if the vocabulary is optimized for the most common scenarios. DDI-RDF Discovery Vocabulary Figure 1 gives an overview over the conceptual model containing a small subset of the DDI-XML specification. More detailed descriptions of the DDI-RDF Discovery Vocabulary are given in the specification and two conference papers (Bosch et al. 2012 and Bosch et al. 2013). To understand the DDI Discovery Vocabulary, there are a few central classes, which can serve as entry points. The first of these is Study. A Study represents the process by which a data set was generated or collected. Literal properties include information about the funding, organizational affiliation, abstract, title, version, and other such high-level information. In some cases, where data collection is cyclic or on-going, data sets may be released as a StudyGroup, where each cycle or wave of the data collection activity produces one or more data sets. This is typical for longitudinal studies, panel studies, and other types of series. In this case, a number of Study objects would be collected into a single StudyGroup. 1 http://www.ddialliance.org/Specification/ 2 http://rdf-vocabulary.ddialliance.org/discovery