23 research outputs found

    RDF and PIDs for INSPIRE: a missing item in ARE3NA

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    The presentation will outline intermediate results of a study in the context of geospatial data sharing across borders and at European level. The study is aiming to develop a common approach to generating common RDF schemas for representing INSPIRE data and metadata, as well as guidelines for the governance of persistent identifiers (PIDs). These are important elements for enabling the re-use of INSPIRE data in other sectors, in particular in e-government. The results of the study may feed into a proposal for additional encoding rules and guidelines for INSPIRE and will be performed in close collaboration with the INSPIRE Maintenance and Implementation Group and the ISA Programme’s Spatial Information and Services Working Group.JRC.H.6-Digital Earth and Reference Dat

    Geo-Semantic Labelling of Open Data. SEMANTiCS 2018-14th International Conference on Semantic Systems

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    In the past years Open Data has become a trend among governments to increase transparency and public engagement by opening up national, regional, and local datasets. However, while many of these datasets come in semi-structured file formats, they use di ff erent schemata and lack geo-references or semantically meaningful links and descriptions of the corresponding geo-entities. We aim to address this by detecting and establishing links to geo-entities in the datasets found in Open Data catalogs and their respective metadata descriptions and link them to a knowledge graph of geo-entities. This knowledge graph does not yet readily exist, though, or at least, not a single one: so, we integrate and interlink several datasets to construct our (extensible) base geo-entities knowledge graph: (i) the openly available geospatial data repository GeoNames, (ii) the map service OpenStreetMap, (iii) country-specific sets of postal codes, and (iv) the European Union's classification system NUTS. As a second step, this base knowledge graph is used to add semantic labels to the open datasets, i.e., we heuristically disambiguate the geo-entities in CSV columns using the context of the labels and the hierarchical graph structure of our base knowledge graph. Finally, in order to interact with and retrieve the content, we index the datasets and provide a demo user interface. Currently we indexed resources from four Open Data portals, and allow search queries for geo-entities as well as full-text matches at http://data.wu.ac.at/odgraph/

    Why Geospatial Linked Open Data for Smart Mobility?

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    While the concept of Smart Cities is gaining momentum around the world and government data are increasingly available and accessible on the World Wide Web, key issues remain about Open Data and data standards for smart cities. A better integration and interoperabilty of data through the World Wide Web is only possible when everyone agrees on the standards for data representation and sharing. Linked Open Data positions itself as a solution for such standardization, being a method of publishing structured data using standard Web technologies. This facilitates the interlinking between datasets, makes them readable by computers, and easily accesible on the World Wide Web. We illustrate this through the example of an evolution from a traditional Content Management System with a geoportal, to a semantic based aproach. The Traffic Safety Monitor was developed in the period of 2012-2015 to monitor the road safety and to support policy development on road safety in Flanders (the northern part of Belgium). The system is built as a Content Management System (CMS), with publication tools to present geospatial indicators on road safety (e.g. the number of accidents with cars and the number of positive alcohol tests) as Web maps using stardardized Open Geospatial Consortium Webservices. The Traffic Safety Monitor is currently further developed towards a Mobility Monitor. Here, the focus is on the development of a business process model for the semantic exchange and publication of spatial data using Linked Open Data principles targeting indicators of sustainable and smart mobility. In the future, the usability of cycling Infrastructure for vehicles such as mobility scooters, bicycle trailers etc. can be assessed using Linked Open Data. The data and metadata is published in Linked open data format, opening the door for their reuse by a wide range of (smart) applications

    Citizen Science and Smart Cities

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    The report summarizes the presentations, discussions, and conclusions of the Citizen Science and Smart Cities Summit organised by the European Commission Joint Research Centre on 5-7th February 2014. In the context of the Summit, the label Citizen Science was used to include both citizen science projects, and others that are about user-generated content, not necessarily addressing a scientific process or issues. The evidence presented by 27 different projects shows the vitality and diversity of the field but also a number of critical points: • Citizen science project are more than collecting data: they are about raising awareness, building capacity, and strengthening communities. • Likewise, smart cities are not only about ICT, energy and transport infrastructures: Smart cities are about smart citizens, who participate in their city’s daily governance, are concerned about increasing the quality of life of their fellow-citizens, and about protecting their environment. Technology may facilitate, but is no solution per se. • Unfortunately to date there seems to be little synergy between citizen science and smart cities initiatives, and there is little interoperability and reusability of the data, apps, and services developed in each project. • It is difficult to compare the results among citizen science, and smart cities projects or translate from one context to another. • The ephemeral nature of much of the data, which disappear short after the end of the projects, means lack of reproducibility of results and longitudinal analysis of time series challenging, if not impossible. • There are also new challenges with respect to the analytical methods needed to integrate quantitative and qualitative data from heterogeneous sources that need further research. • Building and maintaining trust are key points of any citizen science or smart city project. There is a need to work with the community and not just for, or on, the community. It is critical not just to take (data, information, knowledge) but to give back something that is valued by the community itself. The development of citizen science associations in Europe and the US are important developments that may address some of the points above. There are also actions through which the European Commission Joint Research Centre can make an important contribution: • Map citizen science and smart cities projects, and generate a semantic network of concepts between the projects to facilitate search of related activities, and community building. • Provide a repository for citizen science and smart cities data (anonymised and aggregated), software, services, and applications so that they are maintained beyond the life of the projects they originate from, and made shareable and reusable. • Develop regional test beds for the analysis and integration of social and environmental data from heterogeneous sources, with a focus on quality of life and well-being. • Undertake comparative studies, and analyse issues related to scaling up to the European dimension. • Support citizen science and smart cities projects with the JRC knowledge on semantic interoperability, data models, and interoperability arrangements. • Partner with the European Citizen Science Association, and contribute to its interoperability activities. • Work towards making the JRC, and the European Commission, a champion of citizen participation in European science.JRC.H.6-Digital Earth and Reference Dat

    Quality metrics to measure the standards conformance of geospatial linked data

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    This paper describes three new Geospatial Linked Data (GLD) quality metrics that help evaluate conformance to standards. Standards conformance is a key quality criteria, for example for FAIR data. The metrics were implemented in the open source Luzzu quality assessment framework and used to evaluate four public geospatial datasets that showed a wide variation in standards conformance. This is the first set of Linked Data quality metrics developed specifically for GL

    LinkedDataOps: linked data operations based on quality process cycle

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    This paper describes three new Geospatial Linked Data (GLD) quality metrics that help evaluate conformance to standards. Standards conformance is a key quality criteria, for example for FAIR data. The metrics were implemented in the open source Luzzu quality assessment framework and used to evaluate four public geospatial datasets that showed a wide variation in standards conformance. This is the first set of Linked Data quality metrics developed specifically for GLD

    Sustainable Linked Open Data Creation: An Experience Report

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    A flexible platform supporting the linked data life-cycle has been developed and applied in various use cases in the context of the large scale linked open data project Fusepool P3. Besides the description of the aims and achievements, experiences from publishing and reusing linked data in public sector and business are summarized. It is highlighted that without further help it is difficult for domain experts to estimate the time, effort and necessary skills when trying to transfer the platform to other use cases. Applying a new publishing methodology turned out to be useful in these cases

    A Web GIS-based Integration of 3D Digital Models with Linked Open Data for Cultural Heritage Exploration

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    This PhD project explores how geospatial semantic web concepts, 3D web-based visualisation, digital interactive map, and cloud computing concepts could be integrated to enhance digital cultural heritage exploration; to offer long-term archiving and dissemination of 3D digital cultural heritage models; to better interlink heterogeneous and sparse cultural heritage data. The research findings were disseminated via four peer-reviewed journal articles and a conference article presented at GISTAM 2020 conference (which received the ‘Best Student Paper Award’)
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