This paper is part of a series that focuses on DDI usage and how the metadata specification should be applied in a variety of settings by a variety of organizations and individuals. Support for this working paper series was provided by the authors' home institutions; by GESIS -Leibniz Institute for the Social Sciences; by Schloss Dagstuhl -Leibniz Center for Informatics; and by the DDI Alliance.

This paper is part of a series that focuses on DDI usage and how the metadata specification should be applied in a variety of settings by a variety of organizations and individuals. Support for this working paper series was provided by the authors' home institutions; by GESISLeibniz Institute for the Social Sciences; by Schloss Dagstuhl -Leibniz Center for Informatics; and by the DDI Alliance.By Larry Hoyle and Joachim Wackerow with Oliver Hopt B Y L A R R Y H O Y L E A N D J O A C H I M W A C K E R O W W I T H O L I V E R H O P T ABSTRACTIn many instances the only source of certain metadata may be in a file saved from some data analysis program. This is an exploration of what metadata can be harvested from several commonly used programs, and therefore by deduction what else is not available from these programs. These metadata elements are mapped into the appropriate DDI 3 structure.

FORWARDThis paper is the product of one of the three working groups at Dagstuhl event 11382. The group was charged with producing a reference model for the process of longitudinal data production and use, with an emphasis on the specification and management of the supporting metadata. This model is designed to be useful for the gamut of study types where data are collected across time, including panel studies and repeated cross-sectional studies. It should also be useful for single cross-section studies.

No abstract

DDI as a Common Format for Export and Import for Statistical Packages

DDI and Enhanced Data Citation

The Qualitative Data Model Working Group was established in January 2010 with the charge "To develop a robust XMLbased schema for qualitative data exchange (compliant with DDI) and encourage tools development based upon these needs." This report describes the preliminary model developed by that group via online meetings, and working meetings in Gothenburg (2011) and Bergen (2012). This model, described in UML, was developed to cover three main scenarios:1. Qualitative data collections needing metadata at the object level only 2. Qualitative data collections where segments of objects need to be delineated and described and where segments of different physical representations of the same logical objects possibly need to be linked 3. Qualitative data collections as in the second case where related quantitative data have been generated through techniques such as text mining

No abstract