175 results on '"Hammar, Karl"'
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152. Aligning Biomedical Metadata with Ontologies Using Clustering and Embeddings
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Gonçalves, Rafael S., Kamdar, Maulik R., Musen, Mark A., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Hitzler, Pascal, editor, Fernández, Miriam, editor, Janowicz, Krzysztof, editor, Zaveri, Amrapali, editor, Gray, Alasdair J.G., editor, Lopez, Vanessa, editor, Haller, Armin, editor, and Hammar, Karl, editor
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- 2019
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153. Mini-ME Swift: The First Mobile OWL Reasoner for iOS
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Ruta, Michele, Scioscia, Floriano, Gramegna, Filippo, Bilenchi, Ivano, Di Sciascio, Eugenio, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Hitzler, Pascal, editor, Fernández, Miriam, editor, Janowicz, Krzysztof, editor, Zaveri, Amrapali, editor, Gray, Alasdair J.G., editor, Lopez, Vanessa, editor, Haller, Armin, editor, and Hammar, Karl, editor
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- 2019
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154. Validation of SHACL Constraints over KGs with OWL 2 QL Ontologies via Rewriting
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Savković, Ognjen, Kharlamov, Evgeny, Lamparter, Steffen, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Hitzler, Pascal, editor, Fernández, Miriam, editor, Janowicz, Krzysztof, editor, Zaveri, Amrapali, editor, Gray, Alasdair J.G., editor, Lopez, Vanessa, editor, Haller, Armin, editor, and Hammar, Karl, editor
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- 2019
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155. An Ontology-Based Interactive System for Understanding User Queries
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Stoilos, Giorgos, Wartak, Szymon, Juric, Damir, Moore, Jonathan, Khodadadi, Mohammad, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Hitzler, Pascal, editor, Fernández, Miriam, editor, Janowicz, Krzysztof, editor, Zaveri, Amrapali, editor, Gray, Alasdair J.G., editor, Lopez, Vanessa, editor, Haller, Armin, editor, and Hammar, Karl, editor
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- 2019
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156. Learning URI Selection Criteria to Improve the Crawling of Linked Open Data
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Huang, Hai, Gandon, Fabien, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Hitzler, Pascal, editor, Fernández, Miriam, editor, Janowicz, Krzysztof, editor, Zaveri, Amrapali, editor, Gray, Alasdair J.G., editor, Lopez, Vanessa, editor, Haller, Armin, editor, and Hammar, Karl, editor
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- 2019
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157. Latent Relational Model for Relation Extraction
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Rossiello, Gaetano, Gliozzo, Alfio, Fauceglia, Nicolas, Semeraro, Giovanni, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Hitzler, Pascal, editor, Fernández, Miriam, editor, Janowicz, Krzysztof, editor, Zaveri, Amrapali, editor, Gray, Alasdair J.G., editor, Lopez, Vanessa, editor, Haller, Armin, editor, and Hammar, Karl, editor
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- 2019
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158. Incorporating Joint Embeddings into Goal-Oriented Dialogues with Multi-task Learning
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Kassawat, Firas, Chaudhuri, Debanjan, Lehmann, Jens, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Hitzler, Pascal, editor, Fernández, Miriam, editor, Janowicz, Krzysztof, editor, Zaveri, Amrapali, editor, Gray, Alasdair J.G., editor, Lopez, Vanessa, editor, Haller, Armin, editor, and Hammar, Karl, editor
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- 2019
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159. Modelling the Compatibility of Licenses
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Moreau, Benjamin, Serrano-Alvarado, Patricia, Perrin, Matthieu, Desmontils, Emmanuel, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Hitzler, Pascal, editor, Fernández, Miriam, editor, Janowicz, Krzysztof, editor, Zaveri, Amrapali, editor, Gray, Alasdair J.G., editor, Lopez, Vanessa, editor, Haller, Armin, editor, and Hammar, Karl, editor
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- 2019
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160. GConsent - A Consent Ontology Based on the GDPR
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Pandit, Harshvardhan J., Debruyne, Christophe, O’Sullivan, Declan, Lewis, Dave, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Hitzler, Pascal, editor, Fernández, Miriam, editor, Janowicz, Krzysztof, editor, Zaveri, Amrapali, editor, Gray, Alasdair J.G., editor, Lopez, Vanessa, editor, Haller, Armin, editor, and Hammar, Karl, editor
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- 2019
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161. Link Prediction Using Multi Part Embeddings
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Mohamed, Sameh K., Nováček, Vít, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Hitzler, Pascal, editor, Fernández, Miriam, editor, Janowicz, Krzysztof, editor, Zaveri, Amrapali, editor, Gray, Alasdair J.G., editor, Lopez, Vanessa, editor, Haller, Armin, editor, and Hammar, Karl, editor
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- 2019
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162. Deontic Reasoning for Legal Ontologies
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Emani, Cheikh Kacfah, Haralambous, Yannis, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Hitzler, Pascal, editor, Fernández, Miriam, editor, Janowicz, Krzysztof, editor, Zaveri, Amrapali, editor, Gray, Alasdair J.G., editor, Lopez, Vanessa, editor, Haller, Armin, editor, and Hammar, Karl, editor
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- 2019
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163. A Recommender System for Complex Real-World Applications with Nonlinear Dependencies and Knowledge Graph Context
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Hildebrandt, Marcel, Sunder, Swathi Shyam, Mogoreanu, Serghei, Joblin, Mitchell, Mehta, Akhil, Thon, Ingo, Tresp, Volker, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Hitzler, Pascal, editor, Fernández, Miriam, editor, Janowicz, Krzysztof, editor, Zaveri, Amrapali, editor, Gray, Alasdair J.G., editor, Lopez, Vanessa, editor, Haller, Armin, editor, and Hammar, Karl, editor
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- 2019
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164. Generating Semantic Aspects for Queries
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Gupta, Dhruv, Berberich, Klaus, Strötgen, Jannik, Zeinalipour-Yazti, Demetrios, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Hitzler, Pascal, editor, Fernández, Miriam, editor, Janowicz, Krzysztof, editor, Zaveri, Amrapali, editor, Gray, Alasdair J.G., editor, Lopez, Vanessa, editor, Haller, Armin, editor, and Hammar, Karl, editor
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- 2019
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165. Correction to: Using Shape Expressions (ShEx) to Share RDF Data Models and to Guide Curation with Rigorous Validation
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Thornton, Katherine, Solbrig, Harold, Stupp, Gregory S., Labra Gayo, Jose Emilio, Mietchen, Daniel, Prud’hommeaux, Eric, Waagmeester, Andra, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Hitzler, Pascal, editor, Fernández, Miriam, editor, Janowicz, Krzysztof, editor, Zaveri, Amrapali, editor, Gray, Alasdair J.G., editor, Lopez, Vanessa, editor, Haller, Armin, editor, and Hammar, Karl, editor
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- 2019
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166. Using linked data to help robots understand product-related actions
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Michaela Kümpel, Anna de Groot, Ilaria Tiddi, Michael Beetz, Hammar, Karl, Kutz, Oliver, Dimou, Anastasia, Hahmann, Torsten, Hoehndorf, Robert, Masolo, Claudio, and Vita, Randi
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Knowledge graph ,SDG 16 - Peace ,Knowledge representation ,Linked data ,SDG 16 - Peace, Justice and Strong Institutions ,Knowledge acquisition ,Product ontology ,Justice and Strong Institutions - Abstract
Household robots need semantics to understand that a detergent is a cleaning product that can be used to clean physical objects like a table, but laundry detergent is only used to clean/wash laundry. A safely acting autonomous robot should also know that both will not be used as ingredients for meal preparation. We propose a new approach to connect robot sensor data to Linked Data in order to give robotic agents semantic product information about objects that can be found in their environment so that the action to be performed with a given object can be inferred. For this, we use the robot’s belief state when recognizing a product and link it to a product ontology that follows Semantic Web standards. We then use the product class information to fetch further information from external sources like Wikidata or ConceptNet that contain action information (e.g. laundry detergent is used for laundering). At last, the action results are mapped to internally known actions of the robotic agent so that it knows which action can be performed with the perceived object.
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- 2020
167. Using an Existing Website as a Queryable Low-Cost LOD Publishing Interface
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Brecht Van de Vyvere, Pieter Colpaert, Ruben Verborgh, Ruben Taelman, Hitzler, Pascal, Kirrane, Sabrina, Hartig, Olaf, de Boer, Victor, Vidal, Maria-Esther, Maleshkova, Maria, Schlobach, Stefan, Hammar, Karl, Lasierra, Nelia, Stadtmüller, Steffen, Hose, Katja, and Verborgh, Ruben
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Hypermedia web APIs ,Technology and Engineering ,Computer science ,Interface (Java) ,Intelligent agents ,Interoperability ,JSON-LD data snippets ,020206 networking & telecommunications ,02 engineering and technology ,Linked data ,computer.file_format ,Reuse ,computer.software_genre ,World Wide Web ,Intelligent agent ,020204 information systems ,0202 electrical engineering, electronic engineering, information engineering ,SPARQL ,User interface ,Semantic Web ,computer ,Linked Open Data ,Semantic web ,Digital humanities - Abstract
Maintaining an Open Dataset comes at an extra recurring cost when it is published in a dedicated Web interface. As there is not often a direct financial return from publishing a dataset publicly, these extra costs need to be minimized. Therefore we want to explore reusing existing infrastructure by enriching existing websites with Linked Data. In this demonstrator, we advised the data owner to annotate a digital heritage website with JSON-LD snippets, resulting in a dataset of more than three million triples that is now available and officially maintained. The website itself is paged, and thus hydra partial collection view controls were added in the snippets. We then extended the modular query engine Comunica to support following page controls and extracting data from HTML documents while querying. This way, a SPARQL or GraphQL query over multiple heterogeneous data sources can power automated data reuse. While the query performance on such an interface is visibly poor, it becomes easy to create composite data dumps. As a result of implementing these building blocks in Comunica, any paged collection and enriched HTML page now becomes queryable by the query engine. This enables heterogenous data interfaces to share functionality and become technically interoperable.
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- 2019
168. Demonstration of a Stream Reasoning Platform on Low-End Devices to Enable Personalized Real-Time Cycling Feedback
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Mathias De Brouwer, Femke Ongenae, Filip De Turck, Hitzler, Pascal, Kirrane, Sabrina, Hartig, Olaf, de Boer, Victor, Vidal, Maria-Esther, Maleshkova, Maria, Schlobach, Stefan, Hammar, Karl, Lasierra, Nelia, Stadtmüller, Steffen, Hose, Katja, and Verborgh, Ruben
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Technology and Engineering ,Personalization ,Computer science ,Data stream mining ,Training (meteorology) ,Cycling ,02 engineering and technology ,Human–computer interaction ,Low-end devices ,020204 information systems ,Real-time feedback ,0202 electrical engineering, electronic engineering, information engineering ,Domain knowledge ,Virtual training ,020201 artificial intelligence & image processing ,Stream reasoning ,Amateur ,Semantic Web - Abstract
During amateur cycling training, analyzing sensor data in real-time would allow riders to receive immediate feedback on how they are performing, and adapt their training accordingly. In this paper, a solution with Semantic Web technologies is presented that gives such real-time personalized feedback, by integrating the data streams with domain knowledge, rider profiles {\&} other context data. This solution consists of a stream reasoning engine running on a low-end Raspberry Pi device, and a tablet app showing feedback based on the continuous query results. To demonstrate this in a static environment, a virtual training app is presented, allowing a user to simulate an amateur cycling training.
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- 2019
169. The Function Hub : an implementation-independent read/write function description repository
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Anastasia Dimou, Ruben Verborgh, Lander Noterman, Ben De Meester, Hitzler, Pascal, Kirrane, Sabrina, Hartig, Olaf, de Boer, Victor, Vidal, Maria-Esther, Maleshkova, Maria, Schlobach, Stefan, Hammar, Karl, Lasierra, Nelia, Stadtmüller, Steffen, Hose, Katja, and Verborgh, Ruben
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Technology and Engineering ,business.industry ,Computer science ,media_common.quotation_subject ,010401 analytical chemistry ,Interoperability ,Access method ,Repository ,020206 networking & telecommunications ,Context (language use) ,02 engineering and technology ,Linked data ,01 natural sciences ,0104 chemical sciences ,Metadata ,Map ,Linked Data ,0202 electrical engineering, electronic engineering, information engineering ,Web application ,Function ,Software engineering ,business ,Function (engineering) ,media_common - Abstract
Functions are essential building blocks of any (computer) information system. However, development efforts to implement these functions are fragmented: a function has multiple implementations, each within a specific development context. Manual effort is needed handling various search interfaces and access methods to find the desired function, its metadata (if any), and associated implementations. This laborious process inhibits discovery, and thus reuse. Uniform, implementation-independent access is needed. We demo the Function Hub, available online at https://fno.io/hub: a Web application using a semantic interoperable model to map function descriptions to (multiple) implementations. The Function Hub allows editing and discovering function description metadata, and add information about alternative implementations. This way, the Function Hub enables users to discover relevant functions independently of their implementation, and to link to original published implementations.
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- 2019
170. ToCo: An Ontology for Representing Hybrid Telecommunication Networks
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Qianru Zhou, Alasdair J. G. Gray, Stephen McLaughlin, Hitzler, Pascal, Fernández, Miriam, Janowicz, Krzysztof, Zaveri, Amrapali, Gray, Alasdair J.G., Lopez, Vanessa, Haller, Armin, and Hammar, Karl
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0303 health sciences ,Physical infrastructure ,Computer science ,business.industry ,Design pattern ,030302 biochemistry & molecular biology ,Linked data ,Ontology (information science) ,03 medical and health sciences ,Knowledge-based systems ,Use case ,Telecommunications ,business ,Semantic Web ,030304 developmental biology - Abstract
The TOUCAN project proposed an ontology for telecommunication networks with hybrid technologies – the TOUCAN Ontology (ToCo), available at http://purl.org/toco/, as well as a knowledge design pattern Device-Interface-Link (DIL) pattern. The core classes and relationships forming the ontology are discussed in detail. The ToCo ontology can describe the physical infrastructure, quality of channel, services and users in heterogeneous telecommunication networks which span multiple technology domains. The DIL pattern is observed and summarised when modelling networks with various technology domains. Examples and use cases of ToCo are presented for demonstration.
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- 2019
171. The Semantic Web: ESWC 2019 Satellite Events – ESWC 2019 Satellite Events, Portoroz, Slovenia, June 2-6, 2019, Revised Selected Papers
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Stefan Schlobach, Victor de Boer, Olaf Hartig, Maria Maleshkova, Nelia Lasierra, Karl Hammar, Katja Hose, Ruben Verborgh, Pascal Hitzler, Steffen Stadtmüller, Sabrina Kirrane, Maria-Esther Vidal, Hitzler, Pascal, Kirrane, Sabrina, Hartig, Olaf, de Boer, Victor, Vidal, Maria-Esther, Maleshkova, Maria, Schlobach, Stefan, Hammar, Karl, Lasierra, Nelia, Stadtmüller, Steffen, Hose, Katja, and Verborgh, Ruben
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World Wide Web ,Computer science ,Satellite ,Semantic Web - Abstract
The Semantic Web: ESWC 2019 Satellite Events - ESWC 2019 Satellite Events, Portorož, Slovenia, June 2-6, 2019, Revised Selected Papers
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- 2019
172. Extracting Genealogical Networks of Linked Data from Biographical Texts
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Petri Leskinen, Eero Hyvönen, Hitzler, Pascal, Kirrane, Sabrina, Hartig, Olaf, de Boer, Victor, Vidal, Maria-Esther, Maleshkova, Maria, Schlobach, Stefan, Hammar, Karl, Lasierra, Nelia, Stadtmüller, Steffen, Hose, Katja, Verborgh, Ruben, Department of Digital Humanities, Mind and Matter, Professorship Hyvönen Eero, Department of Computer Science, Aalto-yliopisto, and Aalto University
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Service (systems architecture) ,Computer science ,education ,02 engineering and technology ,Linked data ,113 Computer and information sciences ,Semantic portal ,World Wide Web ,Work (electrical) ,020204 information systems ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,6121 Languages ,Data as a service ,Semantic Web ,Network analysis - Abstract
This paper presents the idea and our work of extracting and reassembling a genealogical network automatically from a collection of biographies. The network can be used as a tool for network analysis of historical persons. The data has been published as Linked Data and as an interactive online service as part of the in-use data service and semantic portal BiographySampo—Finnish Biographies on the Semantic Web.
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- 2019
173. An Ontology of Finnish Historical Occupations
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Mikko Koho, Lia Gasbarra, Eero Hyvönen, Heikki Rantala, Ilkka Jokipii, Hitzler, Pascal, Kirrane, Sabrina, Hartig, Olaf, de Boer, Victor, Vidal, Maria-Esther, Maleshkova, Maria, Schlobach, Stefan, Hammar, Karl, Lasierra, Nelia, Stadtmüller, Steffen, Hose, Katja, Verborgh, Ruben, Helsinki University Library, Department of Digital Humanities, Department of Philosophy, History and Art Studies, and Mind and Matter
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Occupational group ,Computer science ,education ,010401 analytical chemistry ,05 social sciences ,Interoperability ,Ontology (information science) ,113 Computer and information sciences ,Social class ,01 natural sciences ,0104 chemical sciences ,Social group ,Component (UML) ,Selection (linguistics) ,6121 Languages ,0501 psychology and cognitive sciences ,Social science ,050104 developmental & child psychology ,Social status - Abstract
Historical datasets often impose the need to study groups of people based on occupation or social status. This paper presents first results in creating an ontology of historical Finnish occupations, AMMO, that enables selection of groups of people based on their occupation, occupational groups, or socioeconomic class. For interoperability, AMMO is linked to the HISCO international historical occupation classification and to a late 20th century Finnish occupational classification. AMMO will be used as a component in two semantic portals for Finnish war history.
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- 2019
174. Ordia:A Web Application for Wikidata Lexemes
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Nielsen, Finn Årup, Hitzler, Pascal, Kirrane, Sabrina, Hartig, Olaf, de Boer, Victor, Schlobach, Stefan, Vidal, Maria-Esther, Maleshkova, Maria, Hammar, Karl, Lasierra, Nelia, Stadtmüller, Steffen, Hose, Katja, and Verborgh, Ruben
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InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL ,InformationSystems_DATABASEMANAGEMENT - Abstract
Since 2018, Wikidata has had the ability to describe lexemes, and the associated SPARQL endpoint Wikidata Query Service can query this information and visualize the results. Ordia is a Web application that displays the multilingual lexeme data of Wikidata based on embedding of the responses from the Wikidata Query Service via templated SPARQL queries. Ordia has also a SPARQL-based approach for online matching of the words of a text with Wikidata lexemes and the ability to use a knowledge graph embedding as part of a SPARQL query. Ordia is available from https://tools.wmflabs.org/ordia/.
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- 2019
175. Republishing OpenStreetMap’s roads as linked routable tiles
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Ben Abelshausen, Julian Andres Rojas Melendez, Ruben Verborgh, Harm Delva, Pieter Colpaert, Hitzler, Pascal, Kirrane, Sabrina, Hartig, Olaf, de Boer, Victor, Vidal, Maria-Esther, Maleshkova, Maria, Schlobach, Stefan, Hammar, Karl, Lasierra, Nelia, Stadtmüller, Steffen, Hose, Katja, and Verborgh, Ruben
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Technology and Engineering ,Computer science ,Interoperability ,Mobility as a service ,Hypermedia ,02 engineering and technology ,Reuse ,Ontology (information science) ,computer.software_genre ,Route planning ,01 natural sciences ,law.invention ,World Wide Web ,law ,020204 information systems ,0202 electrical engineering, electronic engineering, information engineering ,Linked open data ,010401 analytical chemistry ,Open data ,Linked data ,0104 chemical sciences ,Scripting language ,Web service ,computer ,Smart cities ,Journey planning - Abstract
Route planning providers manually integrate different geo-spatial datasets before offering a Web service to developers, thus creating a closed world view. In contrast, combining open datasets at runtime can provide more information for user-specific route planning needs. For example, an extra dataset of bike sharing availabilities may provide more relevant information to the occasional cyclist. A strategy for automating the adoption of open geo-spatial datasets is needed to allow an ecosystem of route planners able to answer more specific and complex queries. This raises new challenges such as (i) how open geo-spatial datasets should be published on the Web to raise interoperability, and (ii) how route planners can discover and integrate relevant data for a certain query on the fly. We republished OpenStreetMap’s road network as “Routable Tiles” to facilitate its integration into open route planners. To achieve this, we use a Linked Data strategy and follow an approach similar to vector tiles. In a demo, we show how client-side code can automatically discover tiles and perform a shortest path algorithm. We provide four contributions: (i) we launched an open geo-spatial dataset that is available for everyone to reuse at no cost, (ii) we published a Linked Data version of the OpenStreetMap ontology, (iii) we introduced a hypermedia specification for vector tiles that extends the Hydra ontology, and (iv) we released the mapping scripts, demo and routing scripts as open source software.
- Published
- 2019
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