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Appendix_A for Hope, Self-Efficacy, and Crushed Dreams: Exploring How Adolescent Girls’ Future Aspirations Relate to Marriage and Childbearing in Rural Mozambique by Catherine Packer, Kathleen Ridgeway, Rachel Lenzi, Lázaro González-Calvo, Troy D. Moon, Ann F. Green and Holly McClain Burke in Journal of Adolescent Research

The Economic Growth Center Digital Library (ssrs.yale.edu/egcdl), funded by the Andrew W. Mellon Foundation, digitizes and makes accessible a selection of Mexican state statistical abstracts from Yale University Library's Economic Growth Center Library Collection. In a departure from most digital libraries, which concentrate on images or texts, EGCDL focuses on statistical tables. This project addresses issues and challenges unique to statistical materials, such as: Evaluating whether common digitization practices and standards, generally developed for images and text, are ideally suited to statistically-intensive documents.Automating metadata production for thousands of PDF and Excel files. Detailed table-level metadata records will be created in XML according to the Data Documentation Initiative (DDI) specification, including the DDI aggregate data extension. In addition to a user interface that presents the PDF versions of the statistical abstracts along with individual tables from the series, a selection of tables and metadata also will be presented in the Nesstar system. This will allow users to browse lists of tables by topic, state, and year, and to search across the entire collection for specific individual tables. We also address the long-term preservation of the digital materials produced in this project and their relationship to the original printed source materials.

As presented at IASSIST 2002 conference

Focusing on the experience of the Yale University (Connecticut) social science data preservation project, this document presents a case study of migration as a preservation strategy, exploring options for migrating data stored in a technically obsolete format and their associated documentation stored on paper. The first section provides background and a project description, an overview of the Yale Roper Collection of public opinion research data sets and paper records, and a summary of the literature search. The following nine steps of the data track are described in the second section: identify equipment; copy files from mainframe-based media to local hard disks; examine documentation; define the column binary format; develop standard variable-naming classifications; read in data with SAS (Statistical Analysis System) and SPSS (Statistical Package for the Social Sciences); identify migration formats; recode data files with SAS; and create spread ASCII data files without recoding. The next section addresses the documentation track, including software/equipment, TextBridge Pro optical character recognition software, PDF (portable document format) files from Adobe Capture, and HTML and SGML/XML marked-up files. Findings and recommendations are presented in the fourth section, including user evaluation, findings about data/documentation conversion, and recommendations to data producers. A glossary is included, and support documents are appended.