Ontotext

Last updated

Ontotext AD
Company type Private corporation
Industry Software

Semantic Web
Semantic technology
Linked Data
Text mining
Information discovery
Graph database
Knowledge Engineering Triplestore

Contents

Knowledge Graph
Founded2000
Headquarters
Bulgaria   OOjs UI icon edit-ltr-progressive.svg
Key people
Atanas Kiryakov, CEO

Vassil Momtchev, CTO

Veska Davidova, COO
Products Ontotext GraphDB, [1]

Ontotext Semantic Platform, GraphDB Cloud, [2] Media & Publishing, Marketing Intelligence, Life Sciences & Healthcare, Compliance & Document Management,

Galleries, Libraries, Archives & Museums (GLAM)
Website Ontotext web site

Ontotext is a software company that produces software relating to data management. Its main products are GraphDB, an RDF database; and Ontotext Platform, a general data management platform based on knowledge graphs. It was founded in 2000 in Bulgaria, and now has offices internationally. [3] Together with the BBC, Ontotext developed one of the early large-scale industrial semantic applications, Dynamic Semantic Publishing, starting in 2010. [4]

Ontotext GraphDB, formerly OWLIM, is an RDF triplestore optimized for metadata and master data management, as well as graph analytics and data publishing. Since version 8.0 GraphDB integrates OpenRefine to allow for easy ingestion and reconciliation of tabular data. [5] Ontotext Platform is a general-purpose data management tool centered around the idea of knowledge graphs. [3]

Ontotext GraphDB

Ontotext GraphDB (previously known as BigOWLIM) is a graph-based database [6] capable of working with knowledge graphs [7] produced by Ontotext, compliant with the RDF graph data model [8] and the SPARQL query language. [9] Some categorize it as a NoSQL database, meaning that it does not use tables like some other databases. [10] In 2014 Ontotext acquired the trademark "GraphDB" from Sones.[ citation needed ]

GraphDB is also an advanced ontology (specification of entities, their properties, and their relationships) repository. [11] The underlying idea of the database is of a semantic repository, storing semantic relationships between objects. [12]

Architecture

GraphDB is used to store and manage semantic knowledge graph data. [7] It is built on top of the RDF4J architecture for handling RDF data, implemented through the use of RDF4J's Storage and Inference Layer (SAIL).[ citation needed ] The architecture is made of three main components:[ citation needed ]

Uses

Ontotext Graph DB has been used in genetics, [14] healthcare, [15] data forensics, [16] cultural heritage studies, [17] geography, [18] infrastructure planning, [19] civil engineering, [20] digital historiography, [21] and oceanography. [22] Commercial clients include the BBC, [23] the Financial Times, [24] Springer Nature, [25] the UK Parliament, [26] [27] and AstraZeneca. [23]


See also

Related Research Articles

<span class="mw-page-title-main">Semantic Web</span> Extension of the Web to facilitate data exchange

The Semantic Web, sometimes known as Web 3.0, is an extension of the World Wide Web through standards set by the World Wide Web Consortium (W3C). The goal of the Semantic Web is to make Internet data machine-readable.

The Resource Description Framework (RDF) is a World Wide Web Consortium (W3C) standard originally designed as a data model for metadata. It has come to be used as a general method for description and exchange of graph data. RDF provides a variety of syntax notations and data serialization formats, with Turtle currently being the most widely used notation.

SPARQL is an RDF query language—that is, a semantic query language for databases—able to retrieve and manipulate data stored in Resource Description Framework (RDF) format. It was made a standard by the RDF Data Access Working Group (DAWG) of the World Wide Web Consortium, and is recognized as one of the key technologies of the semantic web. On 15 January 2008, SPARQL 1.0 was acknowledged by W3C as an official recommendation, and SPARQL 1.1 in March, 2013.

Oracle Spatial and Graph, formerly Oracle Spatial, is a free option component of the Oracle Database. The spatial features in Oracle Spatial and Graph aid users in managing geographic and location-data in a native type within an Oracle database, potentially supporting a wide range of applications — from automated mapping, facilities management, and geographic information systems (AM/FM/GIS), to wireless location services and location-enabled e-business. The graph features in Oracle Spatial and Graph include Oracle Network Data Model (NDM) graphs used in traditional network applications in major transportation, telcos, utilities and energy organizations and RDF semantic graphs used in social networks and social interactions and in linking disparate data sets to address requirements from the research, health sciences, finance, media and intelligence communities.

<span class="mw-page-title-main">Apache Jena</span> Open source semantic web framework for Java

Apache Jena is an open source Semantic Web framework for Java. It provides an API to extract data from and write to RDF graphs. The graphs are represented as an abstract "model". A model can be sourced with data from files, databases, URLs or a combination of these. A model can also be queried through SPARQL 1.1.

<span class="mw-page-title-main">RDF4J</span>

Eclipse RDF4J is an open-source framework for storing, querying, and analysing RDF data. It was created by the Dutch software company Aduna as part of "On-To-Knowledge", a semantic web project that ran from 1999 to 2002. It contains implementations of an in-memory triplestore and an on-disk triplestore, along with two separate Servlet packages that can be used to manage and provide access to these triplestores, on a permanent server. The RDF4J Rio package contains a simple API for Java-based RDF parsers and writers. Parsers and writers for popular RDF serialisations are distributed along with RDF4J, and users can easily extend the list by putting their parsers and writers on the Java classpath when running their application.

<span class="mw-page-title-main">Linked data</span> Structured data and method for its publication

In computing, linked data is structured data which is interlinked with other data so it becomes more useful through semantic queries. It builds upon standard Web technologies such as HTTP, RDF and URIs, but rather than using them to serve web pages only for human readers, it extends them to share information in a way that can be read automatically by computers. Part of the vision of linked data is for the Internet to become a global database.

<span class="mw-page-title-main">DBpedia</span> Online database project

DBpedia is a project aiming to extract structured content from the information created in the Wikipedia project. This structured information is made available on the World Wide Web using OpenLink Virtuoso. DBpedia allows users to semantically query relationships and properties of Wikipedia resources, including links to other related datasets.

SPARUL, or SPARQL/Update, was a declarative data manipulation language that extended the SPARQL 1.0 query language standard. SPARUL provided the ability to insert, delete and update RDF data held within a triple store or quad store. SPARUL was originally written by Hewlett-Packard and has been used as the foundation for the current W3C recommendation entitled SPARQL 1.1 Update. With the publication of SPARQL 1.1, SPARUL is superseded and should only be consulted as a source of inspiration for possible future refinements of SPARQL, but not for real-world applications.

A triplestore or RDF store is a purpose-built database for the storage and retrieval of triples through semantic queries. A triple is a data entity composed of subject–predicate–object, like "Bob is 35" or "Bob knows Fred".

A graph database (GDB) is a database that uses graph structures for semantic queries with nodes, edges, and properties to represent and store data. A key concept of the system is the graph. The graph relates the data items in the store to a collection of nodes and edges, the edges representing the relationships between the nodes. The relationships allow data in the store to be linked together directly and, in many cases, retrieved with one operation. Graph databases hold the relationships between data as a priority. Querying relationships is fast because they are perpetually stored in the database. Relationships can be intuitively visualized using graph databases, making them useful for heavily inter-connected data.

AllegroGraph is a closed source triplestore which is designed to store RDF triples, a standard format for Linked Data. It also operates as a document store designed for storing, retrieving and managing document-oriented information, in JSON-LD format. AllegroGraph is currently in use in commercial projects and a US Department of Defense project. It is also the storage component for the TwitLogic project that is bringing the Semantic Web to Twitter data.

The International Semantic Web Conference (ISWC) is a series of academic conferences and the premier international forum for the Semantic Web, Linked Data and Knowledge Graph Community. Here, scientists, industry specialists, and practitioners meet to discuss the future of practical, scalable, user-friendly, and game changing solutions. Its proceedings are published in the Lecture Notes in Computer Science by Springer-Verlag.

GeoSPARQL is a standard for representation and querying of geospatial linked data for the Semantic Web from the Open Geospatial Consortium (OGC). The definition of a small ontology based on well-understood OGC standards is intended to provide a standardized exchange basis for geospatial RDF data which can support both qualitative and quantitative spatial reasoning and querying with the SPARQL database query language.

The Extended Semantic Web Conference, formerly known as the European Semantic Web Conference, is a yearly international academic conference on the topic of the Semantic Web. The event began in 2004, as the European Semantic Web Symposium. The goal of the event is "to bring together researchers and practitioners dealing with different aspects of semantics on the Web".

Semantic queries allow for queries and analytics of associative and contextual nature. Semantic queries enable the retrieval of both explicitly and implicitly derived information based on syntactic, semantic and structural information contained in data. They are designed to deliver precise results or to answer more fuzzy and wide open questions through pattern matching and digital reasoning.

Shapes Constraint Language (SHACL) is a World Wide Web Consortium (W3C) standard language for describing Resource Description Framework (RDF) graphs. SHACL has been designed to enhance the semantic and technical interoperability layers of ontologies expressed as RDF graphs.

<span class="mw-page-title-main">Blazegraph</span> Open source triplestore and graph database

Blazegraph is an open source triplestore and graph database, developed by Systap, which is used in the Wikidata SPARQL endpoint and by other large customers. It is licensed under the GNU GPL.

<span class="mw-page-title-main">Knowledge graph</span> Type of knowledge base

In knowledge representation and reasoning, a knowledge graph is a knowledge base that uses a graph-structured data model or topology to represent and operate on data. Knowledge graphs are often used to store interlinked descriptions of entities – objects, events, situations or abstract concepts – while also encoding the free-form semantics or relationships underlying these entities.

Datacommons.org is an open knowledge graph hosted by Google that provides a unified view across multiple public datasets, combining economic, scientific and other open datasets into an integrated data graph. The Datacommons.org site was launched in May 2018 with an initial dataset consisting of fact-checking data published in Schema.org "ClaimReview" format by several fact checkers from the International Fact-Checking Network. Google has worked with partners including the United States Census, the World Bank, and US Bureau of Labor Statistics to populate the repository, which also hosts data from Wikipedia, the National Oceanic and Atmospheric Administration and the Federal Bureau of Investigation. The service expanded during 2019 to include an RDF-style Knowledge Graph populated from a number of largely statistical open datasets. The service was announced to a wider audience in 2019. In 2020 the service improved its coverage of non-US datasets, while also increasing its coverage of bioinformatics and coronavirus.

References

  1. ↑ "Ontotext GraphDB". Ontotext.
  2. ↑ "GraphDB Cloud". Ontotext.
  3. 1 2 "Ontotext". Bloor Research. 31 January 2024. Retrieved 25 June 2024.
  4. ↑ O'Donovan, John. "The World Cup and a call to action around Linked Data". BBC Internet Blog. Retrieved 2 November 2016.
  5. ↑ Howard, Philip (10 May 2017). "Graph update: Ontotext GraphDB". Bloor Research.
  6. ↑ "Graph Databases (Technology)". Bloor Research. Retrieved 9 December 2020. We would argue that the market leaders in this space continue to be Neo4J and OntoText (GraphDB), which are graph and RDF database providers respectively.
  7. 1 2 Buchmann, Robert (2019). "Model-Aware Software EngineeringA Knowledge-based Approach to Model-Driven Software Engineering" (PDF). Retrieved 15 April 2021.
  8. ↑ "About GraphDB". GraphDB Free 8.4 documentation. Retrieved 25 June 2024.
  9. ↑ "SparqlImplementations - W3C Wiki". www.w3.org. Retrieved 15 April 2021.
  10. ↑ "GraphDB". Capterra. Retrieved 9 December 2020.
  11. ↑ Ledvinka, Martin (2015). "JOPA: Accessing Ontologies in an Object-oriented Way" (PDF). Retrieved 15 April 2021.
  12. 1 2 Kiryakov, Atanas; Ognyanov, Damyan; Manov, Dimitar (2005). "OWLIM – A Pragmatic Semantic Repository for OWL". In Dean, Mike; Guo, Yuanbo; Jun, Woochun; Kaschek, Roland; Krishnaswamy, Shonali; Pan, Zhengxiang; Sheng, Quan Z. (eds.). Web Information Systems Engineering – WISE 2005 Workshops. Lecture Notes in Computer Science. Vol. 3807. Berlin, Heidelberg: Springer. pp. 182–192. doi:10.1007/11581116_19. ISBN   978-3-540-32287-0.
  13. ↑ Stoilos, Giorgos; Grau, Bernardo Cuenca; Horrocks, Ian (5 July 2010). "How Incomplete is Your Semantic Web Reasoner?". Proceedings of the AAAI Conference on Artificial Intelligence. 24 (1): 1431–1436. doi: 10.1609/aaai.v24i1.7498 . ISSN   2374-3468. S2CID   34119609.
  14. ↑ Poncheewin, Wasin; Hermes, Gerben D. A.; van Dam, Jesse C. J.; Koehorst, Jasper J.; Smidt, Hauke; Schaap, Peter J. (2020). "NG-Tax 2.0: A Semantic Framework for High-Throughput Amplicon Analysis". Frontiers in Genetics. 10: 1366. doi: 10.3389/fgene.2019.01366 . ISSN   1664-8021. PMC   6989550 . PMID   32117417.
  15. ↑ Barisevičius, Gintaras; Coste, Martin; Geleta, David; Juric, Damir; Khodadadi, Mohammad; Stoilos, Giorgos; Zaihrayeu, Ilya (2018). "Supporting Digital Healthcare Services Using Semantic Web Technologies". In Vrandečić, Denny; Bontcheva, Kalina; Suárez-Figueroa, Mari Carmen; Presutti, Valentina; Celino, Irene; Sabou, Marta; Kaffee, Lucie-Aimée; Simperl, Elena (eds.). The Semantic Web – ISWC 2018. Lecture Notes in Computer Science. Vol. 11137. Cham: Springer International Publishing. pp. 291–306. doi:10.1007/978-3-030-00668-6_18. ISBN   978-3-030-00668-6.
  16. ↑ Zhuhadar, Leyla; Ciampa, Mark (1 March 2019). "Leveraging learning innovations in cognitive computing with massive data sets: Using the offshore Panama papers leak to discover patterns". Computers in Human Behavior. 92: 507–518. doi:10.1016/j.chb.2017.12.013. ISSN   0747-5632. S2CID   59528294.
  17. ↑ Damiano, Rossana; Lombardo, Vincenzo; Lieto, Antonio; Borra, Davide (1 July 2016). "Exploring cultural heritage repositories with creative intelligence. The Labyrinth 3D system". Entertainment Computing. 16: 41–52. doi:10.1016/j.entcom.2016.05.002. hdl: 2318/1578514 . ISSN   1875-9521. S2CID   31774697.
  18. ↑ Panasiuk, Oleksandra (2019). "Representing GeoData for Tourism with Schema.org" (PDF). Retrieved 15 April 2021.
  19. ↑ Azzam, Amr; Aryan, Peb Ruswono; Cecconi, Alessio; Di Ciccio, Claudio; Ekaputra, Fajar J.; Fernandez Garcia, Javier David; Karampatakis, Sotiris; Kiesling, Elmar; Musil, Angelika (2019), Antonella Longo, Maria Fazio (ed.), The CitySPIN Platform: A CPSS Environment for City-Wide Infrastructures (PDF), Bilbao, Spain: CEUR Workshop Proceedings, pp. 57–64, retrieved 15 April 2021
  20. ↑ Nundloll, Vatsala; Lamb, Rob; Hankin, Barry; Blair, Gordon (1 April 2021). "A semantic approach to enable data integration for the domain of flood risk management". Environmental Challenges. 3: 100064. Bibcode:2021EnvCh...300064N. doi: 10.1016/j.envc.2021.100064 . ISSN   2667-0100.
  21. ↑ Quaresma, Paulo (2020). "Information Extraction from Historical Texts:a Case Study" (PDF). Retrieved 15 April 2021.
  22. ↑ Zárate, Marcos; Rosales, Pablo; Braun, Germán; Lewis, Mirtha; Fillottrani, Pablo Rubén; Delrieux, Claudio (2019). "OceanGraph: Some Initial Steps Toward a Oceanographic Knowledge Graph". In Villazón-Terrazas, Boris; Hidalgo-Delgado, Yusniel (eds.). Knowledge Graphs and Semantic Web. Communications in Computer and Information Science. Vol. 1029. Cham: Springer International Publishing. pp. 33–40. doi:10.1007/978-3-030-21395-4_3. ISBN   978-3-030-21395-4. S2CID   160011396.
  23. 1 2 Anadiotis, George. "Graph databases and RDF: It's a family affair". ZDNet. Retrieved 9 December 2020.
  24. ↑ "Semantic Technology for online, broadcast and print media". videolectures.net. Retrieved 9 December 2020.
  25. ↑ "SciGraph | For Researchers". Springer Nature. Retrieved 9 December 2020.
  26. ↑ "Linked Government Data". nationalarchives.gov.uk. Retrieved 9 December 2020.
  27. ↑ "Performance testing a graph database | Parliamentary Digital Service". pds.blog.parliament.uk. Retrieved 15 April 2021.
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.