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DIANA LOD

The Linked Data paradigm involves practices to publish, share, and connect data on the Web. Thus, it is a  compelling approach for the dissemination and re-use of scientific data, realizing the vision of the so-called Linked Science. However, by just converting legacy scientific data as Linked Data, we do not fully meet the  requirements of data re-use. Scientific data is evolving data. To ensure re-use and allow exploitation and  validation of scientific results, several challenges related to scientific data dynamics should be tackled. In order to deal with the publication of diachronic life science linked data, we propose a change model based on  RDF to capture versioned entities. Based on this model we convert legacy data from biological databases as diachronic linked data. Our linked data server can assist biologists to explore biological entities and their  evolution by either using SPARQL queries or navigating among entity versions.

Keyword Search

We have developed a novel approach for keyword search on graph-structured data, and in particular temporal RDF graph, i.e. RDF data that involve temporal properties. Our method, instead of providing answers directly from the RDF data graph, automatically generates a set of candidate SPARQL queries that try to capture users information need as expressed by the keywords used. To support temporal exploration, our method is enriched with temporal operators allowing the user to explore data within predefined time ranges.

LinkZoo

LinkZoo is a web-based platform for collaborative management, editing and sharing of Data Web resources. LinkZoo supports the following functionalities: (1) creating and publishing different type of resources as Linked Data, (2) collaborative data management with three levels of privileges represented by three user roles: owner, editor (read/write accesss) and viewer (read only access), (3) two keyword search utilities, one interactive, two-step  keyword search service within LinkZoo, and a second a keyword search service for exploring remote datasets, which automatically generates a set of candidate SPARQL queries that try to capture user’s information need as expressed by the keywords used, (4) multiple static and dynamic views of the data offering intuitive means for organizing,  searching and discovering new resources either within the platform or the entire LOD cloud and (5) data annotations and enrichment with established ontologies and vocabularies, that either pre-exist within LinkZoo or that can be imported.

RDF Graph Anonymization

An RDF Graph Anonymization platform has been developed as a Java/Swing application. The platform guarantees protection against identity disclosure from a malicious attacker, who have partial background knowledge of an RDF data graph G, by implementing an extension of k-anonymity with generalization specifically designed for RDF graph data. The basic functionalities of the platform are the following (1) importing data through csv files, (2) importing generalization hierarchies, (3) automatic creation of a generalization hierarchy based on the imported data, (4) visualization and management of generalization hierarchies, (5) anonymization of sensitive data, (6) visualization of possible set of generalization, (7) visualization of anonymized data and (8) saving anonymized data.