Regresar

Replication data management: Needs and solutions - An initial evaluation of conceptual approaches for integrating heterogeneous replication study data

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. © 2013 IEEE.