Find Linked Datasets of your interest with LODAtlas
In October 2018, the 1.0 version of LODAtlas was released as an open source project under GNU General Public License v3.0. The LODAtlas' source code is hosted on GitLab. LODAtlas was developed by project-team ILDA at Inria, CNRS and Université Paris-Sud; with contributions from project-team CEDAR (RDFQuotients).
"In an increasing number of domains, computer users are faced with large datasets, that are often interlinked and organized according to elaborate structures thanks to new data models such as those that are arising with the development of, e.g., the Web of Data. Rather than seeing the inherent complexity of those data models as a hindrance, we aim at leveraging it to design new interactive systems that can better assist users in their data understanding and processing tasks" (Ilda at Inria).
LODAtlas is a Web tool that helps users find linked datasets of interest through faceted browsing + keyword & URI search on the datasets' metadata and their schema-level content.
The LODAtlas tool provides a set of interactive visualization widgets that help compare datasets along different criteria:
- number of triples,
- last update,
- interlinking with other datasets in the Linked Open Data (LOD) cloud, etc..
Users can also get an idea of the contents of a given dataset thanks to a visual summary of the statements it contains.
- the entire DataHub catalogue, that of data.gov, and
- partial access to the EU data portal (data processing is still ongoing).
LODAtlas instances can be set up by anyone, using CKAN-compliant linked dataset descriptions. LODAtlas is available as a Docker image, or can be compiled locally.
LODATLAS DATA PROCESSING COMPRISES THE FOLLOWING STEPS:
- Download the metadata describing linked datasets from the CKAN repository;
- Download the associated RDF dump files (when available);
- Process the dump files using LODStats to extract classes, properties and vocabularies;
- Process dump files together with schema/ontology files using the RDF Quotients framework to generate visual summaries of the dumps’ contents.
- Linked Data : Get started
- LODE-BD : How to select appropriate encoding strategies for producing Linked Open Data (LOD)-enabled bibliographic data
- Meaningful Bibliographic Metadata (M2B): Recommendations of a set of metadata properties and encoding vocabularies
- AGROVOC - a Linked Open Data controlled vocabulary covering all areas of interest of the Food and Agriculture Organization (FAO) of the United Nations, including food, nutrition, agriculture, fisheries, forestry, environment etc. It is published by FAO and edited by a community of experts
- Priorities for the next few years for the AGROVOC multilingual thesaurus published as Linked Open Data
- What does Data Interoperability Require in Practice?
- Semantic Interoperability
- The role of AGROVOC and other Linked Data vocabularies in architectural models of interoperability
- SPAR Ontologies to enhance the scholarly articles with annotations about its structural and semantic characterisations
- The Basel Register of Thesauri, Ontologies & Classifications (BARTOC) is a database of Knowledge Organization Systems and KOS related Registries
- Data, Big data and Database Semantics (entry in ISKO Encyclopedia, 2018)
- Data Interoperability: The Land Portal experience of Open Data management (recorded GODAN Webinar)
- Proceedings from SEMANTICS Vienna2018
- The Sixteenth Extended Semantic Web Conference (ESWC 2019), 2nd June - 6th June 2019, Portorož, Slovenia
And, thanks again for your interest !