GeoPython 2024: Using Python for Improving Geospatial Data Discovery скачать в хорошем качестве

GeoPython 2024: Using Python for Improving Geospatial Data Discovery

Pekka Latvala Using Python for Improving Geospatial Data Discovery A Python-based web service provides related terms search for the given query word in order to enhance geospatial metadata queries. The related terms are retrieved from an RDF-based ontology or thesaurus data via SPARQL queries. The AquaInfra project is developing a virtual environment for marine and freshwater domains that contain FAIR data and services that support the activities related to restoring healthy waters. One of the AquaInfra services is the Data Discovery and Access Service (DDAS) that provides federated metadata search and data access across multiple APIs. The metadata search can connect to services that implement either the Open Geospatial Consortium's (OGC) Catalogue Service for the Web (CSW) or the OGC API Records standards. In addition, access to custom APIs is supported through data provider plugins. The DDAS service contains also a local metadata catalogue that utililizes the CKAN application. The data access support will include services that follow the OGC API Features and the OGC API Coverages interfaces. The DDAS service contains a Python-based web service component that enhances the metadata queries by providing related terms search to the query words used in the metadata search. The related terms are retrieved from a RDF-based ontology or thesaurus data via SPARQL queries. The python libraries django, django REST framework and SPARQLWrapper are utilized in the service implementation. The RDF data is hosted on the Apache Jena Fuseki SPARQL server. Currently, the service uses thesaurus data from the GEMET (General Multilingual Environmental Thesaurus). The GEMET data contains concepts that may have links to other concepts that are modeled either with "broader", "narrower" or "related" relations. The inclusion of the linked concepts to the search can be controlled with query parameters. The found related terms may not always be relevant to the original query word and the final decicion for their inclusion to the metadata query can be left to the user.