FORMULATING and OBTAINING Uris: a GUIDE to COMMONLY USED VOCABULARIES and REFERENCE SOURCES
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Mapping Spatiotemporal Data to RDF: a SPARQL Endpoint for Brussels
International Journal of Geo-Information Article Mapping Spatiotemporal Data to RDF: A SPARQL Endpoint for Brussels Alejandro Vaisman 1, * and Kevin Chentout 2 1 Instituto Tecnológico de Buenos Aires, Buenos Aires 1424, Argentina 2 Sopra Banking Software, Avenue de Tevuren 226, B-1150 Brussels, Belgium * Correspondence: [email protected]; Tel.: +54-11-3457-4864 Received: 20 June 2019; Accepted: 7 August 2019; Published: 10 August 2019 Abstract: This paper describes how a platform for publishing and querying linked open data for the Brussels Capital region in Belgium is built. Data are provided as relational tables or XML documents and are mapped into the RDF data model using R2RML, a standard language that allows defining customized mappings from relational databases to RDF datasets. In this work, data are spatiotemporal in nature; therefore, R2RML must be adapted to allow producing spatiotemporal Linked Open Data.Data generated in this way are used to populate a SPARQL endpoint, where queries are submitted and the result can be displayed on a map. This endpoint is implemented using Strabon, a spatiotemporal RDF triple store built by extending the RDF store Sesame. The first part of the paper describes how R2RML is adapted to allow producing spatial RDF data and to support XML data sources. These techniques are then used to map data about cultural events and public transport in Brussels into RDF. Spatial data are stored in the form of stRDF triples, the format required by Strabon. In addition, the endpoint is enriched with external data obtained from the Linked Open Data Cloud, from sites like DBpedia, Geonames, and LinkedGeoData, to provide context for analysis. -
LEI in the Payments Market
LEI in the Payments Market Discussion Paper – Industry Update This purpose of this paper is to continue the dialogue that the PMPG started with the community on the introduction of LEI in payments November 2017 Note: Relevant regulations and any applicable legislation take precedence over the guidance notes issued by this body. These Guidelines represent an industry’s best effort to assist peers in the interpretation and implementation of the relevant topic(s). The PMPG - or any of its Members- cannot be held responsible for any error in these Guidelines or any consequence thereof. The Payments Market Practice Group (PMPG) is an independent body of payments subject matter experts from Asia Pacific, EMEA and North America. The mission of the PMPG is to: • Take stock of payments market practices across regions; • Discuss, explain, and document market practice issues, including possible commercial impact; • Recommend market practices covering end-to-end transactions; • Propose best practice, business responsibilities and rules, message flows, consistent implementation of ISO messaging standards and exception definitions; • Ensure publication of recommended best practices; • Recommend payments market practices in response to changing compliance requirements. The PMPG provides a truly global forum to drive better market practices which, together with correct use of standards, will help in achieving full STP, help risk mitigation, meet regulatory requirements and improved customer service. This purpose of this paper is to continue the dialogue that the PMPG started with the community on the introduction of LEI in payments. This initiative started in connection with the recommendations of the Committee on Payments and Market Infrastructure published in their technical report on Correspondent Banking. -
Thesauruses and Ontologies
Thesauruses and ontologies Silvia Arano Citación recomendada: Silvia Arano. Thesauruses and ontologies [en linea]. "Hipertext.net", num. 3, 2005. <http://www.hipertext.net> [Consulted: 12 feb. 2007]. 1. Introduction During the past few years, the information representation and retrieval sector in the area of Documentation and Biblioteconomy has had to assume the important repercussions of the Internet and its associated technologies, and in particular, the World Wide Web (WWW). Technological modifications arising from these important changes are leading to the gradual digitalisation of the information representation and retrieval sector, affecting information artefacts, representation and retrieval tools and user requirements. In the light of this growing context of digitalisation, diverse information representation and retrieval tools exist, which must be studied in addition to diverse fields of knowledge in which these tools have originated: Linguistics, Artificial Intelligence, Documentation, Linguistic Engineering... Hence, in specialised literature, analyses are performed on information representation and retrieval tools, taxonomies, classification systems, computational lexicons, lexical databases, thesauruses, titles lists, knowledge bases, conceptual maps, ontologies, synonym rings and semantic networks, among others. Among this wide spectrum of information representation and retrieval tools are thesauruses and ontologies, which are most often linked in bibliography, even though they come from completely different disciplinary areas. However, the conceptualisation applied by authors to the terms "thesaurus" and "ontology" is quite diverse, and sometimes authors confuse, oppose, complement or overlap both these concepts. The overall objective of the present article [ 1] is to establish the relationship between the concepts of thesaurus and ontology in the Documentation and Biblioteconomy field. Two specific objectives have been established for this purpose. -
Discovering Alignments in Ontologies of Linked Data∗
Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence Discovering Alignments in Ontologies of Linked Data∗ Rahul Parundekar, Craig A. Knoblock, and Jose´ Luis Ambite University of Southern California Information Sciences Institute 4676 Admiralty Way Marina del Rey, CA 90292 Abstract The problem of schema linking (aka schema matching in databases and ontology alignment in the Semantic Web) has Recently, large amounts of data are being published received much attention [Bellahsene et al., 2011; Euzenat and using Semantic Web standards. Simultaneously, Shvaiko, 2007; Bernstein et al., 2011; Gal, 2011]. In this there has been a steady rise in links between objects paper we present a novel extensional approach to generate from multiple sources. However, the ontologies alignments between ontologies of linked data sources. Sim- behind these sources have remained largely dis- ilar to previous work on instance-based matching [Duckham connected, thereby challenging the interoperabil- and Worboys, 2005; Doan et al., 2004; Isaac et al., 2007], ity goal of the Semantic Web. We address this we rely on linked instances to determine the alignments. Two problem by automatically finding alignments be- concepts are equivalent if all (or most of) their respective in- tween concepts from multiple linked data sources. stances are linked (by owl:sameAs or similar links). How- Instead of only considering the existing concepts ever, our search is not limited to the existing concepts in in each ontology, we hypothesize new composite the ontology. We hypothesize new concepts by combining concepts, defined using conjunctions and disjunc- existing elements in the ontologies and seek alignments be- tions of (RDF) types and value restrictions, and tween these more general concepts. -
Linked Data Enables Such Web of Data Global Identifier
Lift your data Introduction to Linked Data Ghislain Atemezing1 , Boris Villazón-Terrazas2 1 EURECOM, France [email protected] 2 Ontology Engineering Group , FI , UPM [email protected] Slides available at: http://www.slideshare.net/atemezing/ INSPIRE Conference 2012, Istanbul Acknowledgements: Oscar Corcho, Asunción Gómez-Pérez, Luis Vilches, Raphaël Troncy, Olaf Hartig, Luis Vilches and many others that we may have omitted. Workdistributed under the license Creative Commons Attribution- Noncommercial-Share Alike 3.0 Agenda Linked Data Geospatial LD Datasets 5-star deployment scheme for Linked Open Data Tutorial “Lift your data”, Istanbul 2012 2 Agenda Linked Data Geospatial LD Datasets 5-star deployment scheme for Linked Open Data Tutorial “Lift your data”, Istanbul 2012 3 Current Web Geospatial Database (Spain) Data exposed to the Web via HTML, pdf, etc. Statistical Database (Spain) © Slide adapted from “5min Introduction to Linked Data”- Olaf Hartig Tutorial “Lift your data”, Istanbul 2012 4 Information from ssgeingle pages can be found via sear ch eegngin es © Slide adapted from “5min Introduction to Linked Data”- Olaf Hartig Tutorial “Lift your data”, Istanbul 2012 5 Complex queries over muliltipl e pages/data sources? © Slide adapted from “5min Introduction to Linked Data”- Olaf Hartig Tutorial “Lift your data”, Istanbul 2012 6 What do we actually want? • Use the Web like a single global database • web of documents -> web of data Geospatial Statistical Database Database (Spain) (Spain) © Slide adapted from “5min Introduction to Linked Data”- Olaf Hartig 7 Tutorial “Lift your data”, Istanbul 2012 7 Linked Data enables such Web of Data Global Identifier: URI (Uniform Resource Identifier), which is a string of characters used to identify a name or a resource on the Internet. -
OGC Testbed-14: Semantically Enabled Aviation Data Models Engineering Report
OGC Testbed-14 Semantically Enabled Aviation Data Models Engineering Report Table of Contents 1. Summary . 4 1.1. Requirements & Research Motivation . 4 1.2. Prior-After Comparison. 4 1.3. Recommendations for Future Work . 5 1.4. What does this ER mean for the Working Group and OGC in general . 6 1.5. Document contributor contact points . 6 1.6. Foreword . 6 2. References . 8 3. Terms and definitions . 9 3.1. Semantics . 9 3.2. Service Description. 9 3.3. Service-Oriented Architecture (SOA) . 9 3.4. Registry . 9 3.5. System Wide Information Management (SWIM) . 9 3.6. Taxonomy . 9 3.7. Web Service . 10 4. Abbreviated Terms . 11 5. Overview . 12 6. Review of Data Models . 13 6.1. Information Exchange Models . 13 6.1.1. Flight Information Exchange Model (FIXM). 13 6.1.2. Aeronautical Information Exchange (AIXM) Model. 13 6.1.3. Weather Information Exchange Model (WXXM) . 14 6.1.4. NASA Air Traffic Management (ATM) Model . 14 6.2. Service description models . 19 6.2.1. Service Description Conceptual Model (SDCM) . 19 6.2.2. Web Service Description Ontological Model (WSDOM). 23 6.2.3. SWIM Documentation Controlled Vocabulary (FAA) . 25 7. Semantic Enablement Approaches . 27 8. Metadata level semantic enablement . 33 8.1. Issues with existing metadata standards . 34 8.1.1. Identification of Resources. 34 8.1.2. Resolvable URI. 34 8.1.3. Multilingual Support . 35 8.1.4. External Resource Descriptions . 35 8.1.5. Controlled Vocabulary Management . 36 8.1.6. Keywords Types . 37 8.1.7. Keyword Labeling Inconsistencies . -
Contents the Three Languages Theory In
Ie Contents The Three LanguagesTheory in Information Retrieval Part-controlled Vocabulary for Literature Studies UDC: International Medium Edition - English Text Class Number Searching in an Experimental Online Catalog UDC 168 + International Classification Vol. 13 (1986) Nr. 3 025.4 + 001.4 (05) INTERNATIONAL CLASSIFICATION Devoted to Concept Theory, Systematic Ter minology and Organization of Knowledge Editors Dr. phil. Ingetraut Dahlberg, 0-6000 Frank furt 50, Woogstr. 36a, Editor-in-chief Prof. Dr. med. Dr. phil. Alwin Diemer, Philo sophisches Institut der Universitat Dusseldorf, D-4000 Dusseldorf 1, Universitatsstr. 1, FRG. Prof. Jean M. Perreault, University Library, University of Alabama, P. O. B. 2600 Hunts Contents ville, Alabama 35807, USA Prof. Arashanipalai Neelameghan, clo Unes Editorial co PGI. 7, Place de Fontenoy, F-75700 Paris New Uses for Old Schemes 125 co-sponsored by - FID/CR (Federation Internationale de Do Articles cumentation, Committee on Classification Re G.Deschatelets: The three languages theory in information retrieval. 126 search, address see Dr. I. Dahlberg K.Harris: Part-controlled vocabulary for literature studies ..... 133 A.Chatterjee, G.G.Choudhury: UDC: International Medium Edition - Consulting Editors Mrs. Jean Aitchison, 12, Sollershott West, English text ....... ,. .. ....... ... .... 137 K.Markey: Class number searching in an experimental online catalog 142 Letchworth, Herts., SG6 3PX, England Prof. Asterio T. Campos, Departamento de Bi Reports and Communications . ... .. 151 blioteconomia, Universidade de Brasilia, Bra CSNA Annual Meeting 1986 - COMPSTAT 1986 - Fall Meeting of SEK DA-NK, silia OF, Brazil Gesellschaft flir Klassifikation - Stability in Classification - Dr. A.1. Cernyj, VINITI, Moscow A-219 Bal Standardization in Computerized Lexicography - Going for Gold - tijskaja u1. -
What Are Controlled Vocabularies?
2. What Are Controlled Vocabularies? A controlled vocabulary is an organized arrangement of words and phrases used to index content and/or to retrieve content through browsing or searching. It typically includes preferred and variant terms and has a defined scope or describes a specific domain. 2.1. Purpose of Controlled Vocabularies The purpose of controlled vocabularies is to organize information and to provide terminology to catalog and retrieve information. While capturing the richness of variant terms, controlled vocabularies also promote consistency in preferred terms and the assignment of the same terms to similar content. Given that a shared goal of the cultural heritage community is to improve access to visual arts and material culture information, controlled vocabularies are essential. They are necessary at the indexing phase because without them catalogers will not consistently use the same term to refer to the same person, place, or thing. In the retrieval process, various end users may use different synonyms or more generic terms to refer to a given concept. End users are often not specialists and thus need to be guided because they may not know the correct term. The most important functions of a controlled vocabulary are to gather together variant terms and synonyms for concepts and to link concepts in a logical order or sort them into categories. Are a rose window and a Catherine wheel the same thing? How is pot-metal glass related to the more general term stained glass? The links and relationships in a controlled vocabulary ensure that these connections are defined and maintained, for both cataloging and retrieval. -
Taxonomy Directed Folksonomies
2nd Version Date : 19/06/2007 TAXONOMY DIRECTED FOLKSONOMIES Integrating user tagging and controlled vocabularies for Australian education networks Sarah Hayman and Nick Lothian education.au Adelaide Australia Meeting: 157 Classification and Indexing Simultaneous Interpretation: No WORLD LIBRARY AND INFORMATION CONGRESS: 73RD IFLA GENERAL CONFERENCE AND COUNCIL 19-23 August 2007, Durban, South Africa http://www.ifla.org/iv/ifla73/index.htm 1 Abstract What is the role of controlled vocabulary in a Web 2.0 world? Can we have the best of both worlds: balancing folksonomies and controlled vocabularies to help communities of users find and share information and resources most relevant to them? education.au develops and manages Australian online services for education and training. Its goal is to bring people, learning and technology together. education.au projects are increasingly involved in exploring the use of Web 2.0 developments building on user ideas, knowledge and experience, and how these might be integrated with existing information management systems. This paper presents work being undertaken in this area, particularly in relation to controlled vocabularies, and discusses the challenges faced. Education Network Australia (edna) is a leading online resource collection and collaborative network for education, with an extensive repository of selected educational resources with metadata created by educators and information specialists. It uses controlled vocabularies for metadata creation and searching, where users receive suggested related terms from an education thesaurus, with their results. We recognise that no formal thesaurus can keep pace with user needs so are interested in exploiting the power of folksonomies. We describe a proof of concept project to develop community contributions to managing information and resources, using Taxonomy-Directed Folksonomy. -
Download the 2021 IEEE Thesaurus
2021 IEEE Thesaurus Version 1.0 Created by The Institute of Electrical and Electronics Engineers (IEEE) 2021 IEEE Thesaurus The IEEE Thesaurus is a controlled The IEEE Thesaurus also provides a vocabulary of almost 10,900 descriptive conceptual map through the use of engineering, technical and scientific terms, semantic relationships such as broader as well as IEEE-specific society terms terms (BT), narrower terms (NT), 'used for' [referred to as “descriptors” or “preferred relationships (USE/UF), and related terms terms”] .* Each descriptor included in the (RT). These semantic relationships identify thesaurus represents a single concept or theoretical connections between terms. unit of thought. The descriptors are Italic text denotes Non-preferred terms. considered the preferred terms for use in Bold text is used for preferred headings. describing IEEE content. The scope of descriptors is based on the material presented in IEEE journals, conference Abbreviations used in the Thesaurus: papers, standards, and/or IEEE organizational material. A controlled BT - Broader term vocabulary is a specific terminology used in NT - Narrower term a consistent and controlled fashion that RT - Related term results in better information searching and USE- Use preferred term retrieval. UF - Used for Thesaurus construction is based on the ANSI/NISO Z39.19-2005(2010) standard, Guidelines for the Construction, Format, and Management of Monolingual Controlled Vocabulary. The Thesaurus vocabulary uses American-based spellings with cross references to British variant spellings. The scope and structure of the IEEE Thesaurus reflects the engineering and scientific disciplines that comprise the Societies, Councils, and Communities of the IEEE in *Refer to ANSI/NISO NISO Z39.19-2005 addition to the technologies IEEE serves. -
Historical Gazetteer System Integration: CHGIS, Regnum Francorum, and Geonames
p. 1 Historical Gazetteer System Integration: CHGIS, Regnum Francorum, and GeoNames Merrick Lex Berman (CGA, Harvard University) Johan Åhlfeldt (Regnum Francorum Online) Marc Wick 24 Jul 2014 [draft chapter for submission to publisher] Abstract: Integrating digital gazetteers involves the matching of place name records, disambiguation of unique places and conflation of duplicates or variant place names. The challenge of mapping between historical instances of place names is also an ongoing concern for several important projects dealing with ancient place names. Here the matching of historical place names from two unrelated datasets (for China and France) to gazetteer web services is undertaken using a basic geospatial and geonomial algorithm. The quantitative results of the matching trials are considered, problems in dealing with vernacular scripts considered, and practical implications for integrating historical gazetteers discussed. 1. Gazetteer Web Services and Digital Historical Gazetteers Online gazetteers provide essential services. They serve as authority records for geocoding place names and for retrieval of place names associated with real world coordinates (reverse geocoding). For example, the expanding interconnections of LinkedOpenData [LOD] 1 on the semantic web have consistently placed GeoNames 2 at or near the center of the semantic web's social graph. The centrality of GeoNames is largely due to three factors: first, it is a free and open Application Programming Interface [API]; second, the API is simple and easy-to-use; and third, it is currently the only global geographic resource with stable URIs. Traffic for the GeoNames web service topped twenty million requests per day (in 2012); and since half of these requests are from smart phones, 3 it is clear that geographic information retrieval [GIR] is being p. -
Controlled Vocabulary and Folksonomies
Controlled Vocabulary and Folksonomies Louise Spiteri School of Information Management What are folksonomies? Folksonomies (known also as “social classifications”) are user created metadata. They are grassroots community classification of digital assets. The term “folksonomy” was created by Thomas Vander Val and represents a merging of the terms “folk” and “taxonomy.” One form of explicit user created metadata was popularized in the late 1990s with link-focused websites called weblogs. Where are folksonomies found? Folksonomies are found in social bookmarks managers such as Del.icio.us (http://del.icio.us/) and Furl (http://www.furl.net/), which allow users to: Add bookmarks of sites they like to their personal collections of links Organize and categorize these sites by adding their own terms, or tags Share this collection with other people with the same interests. The tags are used to collocate bookmarks: (a) within a user’s collection; and (b) across the entire system, e.g., the page http://del.icio.us/tag/blogging will show all bookmarks that are tagged with “blogging” by any user. Inter-term relationships There are no clearly defined relations between and among the terms in the vocabulary, unlike formal taxonomies and classification schemes, where there are multiple kinds of explicit relationships (e.g., broader, narrower, and related terms) between and among terms. Folksonomies are simply the set of terms that a group of users tagged content with; they are not a predetermined set of classification terms or labels. Popular folksonomy sites Del.icio.us (http://del.icio.us) Flickr (http://www.flickr.com) Frassle (http://www.frassle.org) Furl (http://www.furl.net) Simpy (http://www.simpy.com) Spurl (http://www.spurl.com) Technorati (http://www.technorati.com) How folksonomies work Registration is free.