The CHAIN-REDS Semantic Search Engine

e-Infrastructures, and in particular Data Repositories and Open Access Data Infrastructures, are essential platforms for e-Science and e-Research and are being built since several years both in Europe and the rest of the world to support diverse multi/inter-disciplinary Virtual Research Communities. So far, however, it is difficult for scientists to correlate papers to datasets used to produce them and to discover data and documents in an easy way. In this paper, the CHAINREDS project’s Knowledge Base and its Semantic Search Engine are presented, which attempt to address those drawbacks and contribute to the reproducibility of science

Towards Semantic Data Management in LifeWatch Italy: the Phytoplankton Study Case

LifeWatch Italy, the Italian node of LifeWatch-ERIC, has promoted and stimulated the debate on the use of semantic in the biodiversity data management. Actually, information from biodiversity and ecosystems is very heterogeneous and needs to be better managed in order to improve the actual scientific knowledge, as well as to address the urgent societal challenges concerning environmental issues. Here we present the Phytoplankton Study Case, where the semantic approach was used to address data harmonisation, integration and discovery. An interdisciplinary team of LifeWatch Italy has developed a thesaurus on phytoplankton functional traits and linked its concepts to other existing conceptual schema related to the specific domain. In the meantime, the team has produced the LifeWatch Core Ontology, a customization of the OBOE core ontology, for the semantic description/capture of basic concepts and relationships in ecological studies. This framework ontology is based on 7 main concepts (classes) as Domain, Entity, Observation, Characteristic, Measurement, Protocol, Standard, providing a structured yet generic approach for semantic data annotation, and for developing domain-specific ecological ontologies as the Phytoplankton Trait Ontology (PhyTO). To date, LifeWatch e-Infrastructure stores and manages data and metadata using an mix of Database Management Systems (the Relational MySQL and the NoSQL MONGO DB); for the purpose of the study case, we selected the VIRTUOSO Triple Store as semantic repository and we developed different modules to automate the management workflow. A first software module has been developed to allow the data annotation with classes, subclasses and properties of the PhyTO (i.e. Semantic Annotation). The designed module allows to map metadata and data stored in the LifeWatch Data Portal with the OWL schema of the PhyTO and to produce .rdf output files. A second developed module uses as input the .rdf files and store the data in the VIRTUOSO Graph to make them available for the semantic search. Moreover, a user-friendly search interface (i.e. Java Portlet) has been implemented to retrieve annotated data with queries suggested by the data users. This approach facilitates data discovery and integration, and can provide guidance for, and automate, data aggregation and summary

CHAIN-REDS DART Challenge

CHAIN-REDS (Coordination and Harmonisation of Advanced e-infrastructure for Research and Education Data Sharing) is EU project focused on promoting and supporting technological and scientific collaboration across different communities established in various continents. Nowadays, one of the most challenging scenarios scientist and scientific communities are facing is huge amount of data emerging from vast networks of sensors and form computational simulations performed in a diversity of computing architectures and e-infrastructure. The new knowledge coming out from the interpretation of these datasets, reported on the scholar literature, is increasingly problematic to be reproducible due to the difficulty to access measured data repositories and/or computational applications that generate synthetic data through computer simulations. This paper presents CHAIN REDS approach, several tools and services, based on the adoption of standards, aimed at providing easy/seamless access to datasets, data repositories, open access document repositories and to the applications that could make use of them. All these tools and services are enclosed in what we have called the Data Accessibility, Reproducibility and Trustworthiness (DART) challenge. This initiative allows researchers to easily find data of his interest and directly use them in a code running by means of a Science Gateway (SG) that provides access to cluster, Grid and Cloud infrastructure worldwide. In this scenario, the datasets are found by means of either the CHAIN-REDS Knowledge Base (KB) or the Semantic Search Engine (SSE), the applications ran on the CHAIN-REDS SG, accessible through an Identity Federation. The datasets can be both identified by Persistent Identifier (PID) and assigned unique number ID. Scientists can then access the data and the corresponding application in order to either reproduce and extend the results of a given study or start a new investigation. The new data (and the new paper if any) are stored on the Data Infrastructure and can be easily found by the people belonging to the same domain making possible to start the cycle again.Repositório de dados científicos.Ibero-American Science and Technology Education Consortium (ISTEC

CHAIN-REDS DART Challenge

CHAIN-REDS (Coordination and Harmonisation of Advanced e-infrastructure for Research and Education Data Sharing) is EU project focused on promoting and supporting technological and scientific collaboration across different communities established in various continents. Nowadays, one of the most challenging scenarios scientist and scientific communities are facing is huge amount of data emerging from vast networks of sensors and form computational simulations performed in a diversity of computing architectures and e-infrastructure. The new knowledge coming out from the interpretation of these datasets, reported on the scholar literature, is increasingly problematic to be reproducible due to the difficulty to access measured data repositories and/or computational applications that generate synthetic data through computer simulations. This paper presents CHAIN REDS approach, several tools and services, based on the adoption of standards, aimed at providing easy/seamless access to datasets, data repositories, open access document repositories and to the applications that could make use of them. All these tools and services are enclosed in what we have called the Data Accessibility, Reproducibility and Trustworthiness (DART) challenge. This initiative allows researchers to easily find data of his interest and directly use them in a code running by means of a Science Gateway (SG) that provides access to cluster, Grid and Cloud infrastructure worldwide. In this scenario, the datasets are found by means of either the CHAIN-REDS Knowledge Base (KB) or the Semantic Search Engine (SSE), the applications ran on the CHAIN-REDS SG, accessible through an Identity Federation. The datasets can be both identified by Persistent Identifier (PID) and assigned unique number ID. Scientists can then access the data and the corresponding application in order to either reproduce and extend the results of a given study or start a new investigation. The new data (and the new paper if any) are stored on the Data Infrastructure and can be easily found by the people belonging to the same domain making possible to start the cycle again.Repositório de dados científicos.Ibero-American Science and Technology Education Consortium (ISTEC

Analysis with the Africa Grid Science Gateway of ALICE Data from the ALICE Collaboration - LHC2010b_pp_ESD_117222

This is the software of a JSR 286 compliant "portlet" installed on the <a href="http://sgw.africa-grid.org" target="_blank">Africa Grid Science Gateway</a> that allows the analysis of the dataset mentioned in the title. Click on the External link below to be automatically re-directed to the execution page of the portlet on the Science Gateway