Lowering the Barriers to Capturing Questionnaire Metadata Throughout the Data Lifecycle

Sufficient metadata facilitates the discovery, use, and interpretation of survey research data and is necessary to maximize the value of collected data. Usually this information is appended to survey datasets or summarized in a codebook toward the end of the research data lifecycle, immediately prior to analysis, preservation, and/or storage. Yet this same metadata has often been captured, administered, or managed by different stakeholders numerous times at different points along the data lifecycle. Capturing research metadata earlier in the data lifecycle—from conceptualization and instrument development onwards—not only provides richer and more accurate information, but it also introduces efficiencies to workflows by reducing redundancies and lowering costs. The Data Documentation Initiative (DDI) metadata standard can organize the means by which this metadata is tracked and managed at each stage of a survey’s lifecycle. DDI has a comprehensive and richly structured XML schema that can pose challenges for clients, researchers, and project managers who aren’t fluent in metadata standards or software. There may also be cultural and technical hurdles for these stakeholders to overcome when describing questions and assessments in the manner that DDI does. The core of the problem is how to achieve DDI buy-­in early in the process so that metadata follows the data at every stage of its existence. This presentation proposes a means by which a simple Word template may serve as a bridge from conceptualization to instrument development to fielding. By providing a familiar interface that many survey clientele already use to develop questionnaires, this template could substantially lower the entry barriers to using DDI in survey research. The presentation will propose a mapping of the template fields to DDI schema elements and will elucidate how DDI can provide information on versioning, harmonization, and provenance in a standardized and machine-­actionable manner.