Describing Research Data: A Case Study for Archaeology Nicola Aloia 1 , Christos Papatheodorou 2,3 , Dimitris Gavrilis 3 , Franca Debole 1 , and Carlo Meghini 1 1 Istituto di Scienza e Tecnologie dell’Informazione, National Research Council, Pisa, Italy {Nicola.Aloia,Franca.Debole,Carlo.Meghini}@isti.cnr.it 2 Dept. of Archives, Library Science and Museology, Ionian University, Corfu, Greece 3 Digital Curation Unit, Institute for the Management of Information Systems, ‘Athena’ Research Centre, Athens, Greece {c.papatheodorou,d.gavrilis}@dcu.gr Abstract. The growth of the digital resources produced by the re- search activities demand the development of e-Infrastructures in which researchers can access remote facilities, select and re-use huge volumes of data and services, run complex experimental processes and share results. Data registries aim to describe uniformly the data of e-Infrastructures contributing to the re-usability and interoperability of big scientific data. However the current situation requires the development of powerful re- source integration mechanisms that step beyond the principles guaran- teed by the data registries standards. This paper proposes a conceptual model for describing data resources and services and extends the exist- ing specifications for the development of data registries. The model has been implemented in the context of the ARIADNE project, a EU funded project that focuses on the integration of Archaeological digital resources all over the Europe. Keywords: Data registries, Research infrastructures, Interoperability, Archaeological digital resource. 1 Introduction Extremely large scientific datasets are being generated and the issues for iden- tifying, locating, re-using and exploiting data are getting more difficult and im- perative. This data deluge affects the way research is carried out leading to a data-oriented paradigm. Data integration functionalities, data analysis, data mining and visualization tools should support this shift of the research and scholar communication paradigm. For this purpose Global Research Data In- frastructures infrastructures are being developed to assure the interoperability and discoverability of scientific resources and cope with the (i) structural (syn- tactic) heterogeneity of data organized in datasets, following particular database schemas, or in collections described by different metadata schemas at collection R. Meersman et al. (Eds.): OTM 2014, LNCS 8841, pp. 768–775, 2014. c  Springer-Verlag Berlin Heidelberg 2014