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One of the most important components of research is access to quality data. Digital data archives must work to increase submission rates to insure that quality data exist for future researchers. This is a challenge given that recent studies show that vast amounts of data collected during publicly funded projects are not being archived. Even the best-planned methodology will not succeed when researchers use tainted data or fail to find adequate data. Social science data archivists play a key role in the effort to maintain quality sources of data for social science investigators to repurpose and reuse. The dynamic, circular movement of data between the producers and archives is critical to the future of social science research. Data archives have historically provided for this data interchange using considerable human capital. Dedicated archivists and investigators have worked together to ensure that data were processed and placed into an archive best designed for their preservation, a manual process that has become increasingly expensive and unwieldy due to the volume of data being produced and the advanced metadata required to provide future researchers enough details to reuse the study. Typical methods have the researchers working with the archives to deposit the data long after the project has been complete and the papers published. The manual creation of metadata at this point takes far long than if it were collected earlier in the research life cycle. Recent advances in archival repository software may be the key to streamlining this increasingly inefficient archival process by allowing archivist and researchers the ability to create detailed metadata earlier in the research lifecycle at a point where it will take far less time. Software allows researchers greater personal control over archival ingest processes, bridging the gap between researchers and archives and possibly increasing submission rates of valuable data to archives. Archival technology provides tools that manage automated ingest, data cataloging, advanced search and indexing, and rights and access issues. Archival tools also provide proper citation, creation of persistent identifiers, automatic creation of preservation formats, format migration, and statistical analysis of data. Customized branding and citation management can provide investigators collecting these data with a tool that will ensure that they get the credit they deserve. The Dataverse Network Technology has the potential to aid many research groups at UNC in the data management processes and has the potential for use in many disciplines. This presentation will explain the technology and its applicability for managing research data.