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• W2093142196 abstract "[Context] Replication Data Management (RDM) aims at enabling the use of data collections from several itera-tions of an experiment. However, there are several major chal-lenges to RDM from integrating data models and data from em-pirical study infrastructures that were not designed to cooperate, e.g., data model variation of local data sources. [Objective] In this paper we analyze RDM needs and evaluate conceptual RDM approaches to support replication researchers. [Method] We adapted the ATAM evaluation process to (a) analyze RDM use cases and needs of empirical replication study research groups and (b) compare three conceptual approaches to address these RDM needs: central data repositories with a fixed data model, heterogeneous local repositories, and an empirical ecosystem. [Results] While the central and local approaches have major issues that are hard to resolve in practice, the empirical ecosys-tem allows bridging current gaps in RDM from heterogeneous data sources. [Conclusions] The empirical ecosystem approach should be explored in diverse empirical environments." @default.
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• W2093142196 date "2013-10-01" @default.
• W2093142196 modified "2023-10-03" @default.
• W2093142196 title "Replication Data Management: Needs and Solutions -- An Initial Evaluation of Conceptual Approaches for Integrating Heterogeneous Replication Study Data" @default.
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• W2093142196 doi "https://doi.org/10.1109/esem.2013.60" @default.
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