Knowledge Creation

  • Chapter
  • First Online:
An Introduction to Knowledge Graphs
  • 161 Accesses

Abstract

The first step in building a knowledge graph is creating knowledge from heterogeonous sources. First, we explain how to create terminological knowledge with a focus on ontologies and ontology engineering. Then we explain how assertional knowledge can be created from heterogonous sources, with examples of declarative map** languages like the Resource Description Framework Map** Language (RDFML).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
EUR 29.95
Price includes VAT (France)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
EUR 58.84
Price includes VAT (France)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
EUR 73.84
Price includes VAT (France)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Arenas-Guerrero J, Chaves-Fraga D, Toledo J, Perez MS, Corcho O (2022) Morph-KGC: scalable knowledge graph materialization with map** partitions. Semantic Web (Preprint) 1–20

    Google Scholar 

  • Benjamins R, Fensel D, Decker S, Gomez Perez A (1999) (KA)2: building ontologies for the internet: a mid-term report. Int J Hum Comput Stud 51(3):687–712

    Article  Google Scholar 

  • Bernaras A, Laresgoiti I, Corera J (1996) Building and reusing ontologies for electrical network applications. Proc ECAI 96(1996):298–302

    Google Scholar 

  • Calvanese D, Cogrel B, Komla-Ebri S, Kontchakov R, Dv L, Rezk M, Rodriguez-Muro M, **ao G (2017) Ontop: answering SPARQL queries over relational databases. Semantic Web 8(3):471–487

    Article  Google Scholar 

  • Clark A, Fox C, Lappin S (eds) (2012) The handbook of computational linguistics and natural language processing, vol 118. Wiley

    Google Scholar 

  • De Nicola A, Missikoff M, Navigli R (2005) A proposal for a unified process for ontology building: upon. In: Database and expert systems applications: 16th international conference, DEXA 2005, Copenhagen, Denmark, August 22–26, 2005. Proceedings 16, Springer, pp 655–664

    Google Scholar 

  • Deng C, Ji X, Rainey C, Zhang J, Lu W (2020) Integrating machine learning with human knowledge. iScience 23(11):101656

    Article  Google Scholar 

  • Dimou A, Vander Sande M, Colpaert P, Verborgh R, Mannens E, Van de Walle R (2014) RML: a generic language for integrated RDF map**s of heterogeneous data. In: LDOW 1184

    Google Scholar 

  • Fensel D, Bussler C (2002) The web service modeling framework WSMF. Electron Commer Res Appl 1(2):113–137

    Article  Google Scholar 

  • Fensel D, Erdmann M, Studer R (1997) Ontology groups: Semantically enriched subnets of the www. In: Proceedings of the 1st International Workshop Intelligent Information Integration during the 21st German Annual Conference on Artificial Intelligence, Freiburg, Germany, September

    Google Scholar 

  • Fensel D, Simsek U, Angele K, Huaman E, Karle E, Panasiuk O, Toma I, Umbrich J, Wahler A (2020) Knowledge graphs. Springer

    Book  Google Scholar 

  • Fernández-López M, Gómez-Pérez A, Juristo N (1997) METHONTOLOGY: from ontological art towards ontological engineering. AAAI Conference on Artificial Intelligence

    Google Scholar 

  • Garcia-Gonzalez H, Boneva I, Staworko S, Labra-Gayo JE, Lovelle JMC (2020) ShExML: Improving the usability of heterogeneous data map** languages for first-time users. PeerJ Comput Sci 6:318

    Article  Google Scholar 

  • Goldbeck G, Ghedini E, Hashibon A, Schmitz G, Friis J (2019) A reference language and ontology for materials modelling and interoperability. https://publica.fraunhofer.de/handle/publica/406693

  • Gomez-Perez A, Fernandez-Lopez M, Corcho O (2006) Ontological engineering: with examples from the areas of knowledge management, e-Commerce and the Semantic Web. Springer

    Google Scholar 

  • Gruber TR (1993) Toward principles for the design of ontologies used for knowledge sharing, knowledge systems laboratory. Computer Science Department, Stanford University, Stanford, CA

    Google Scholar 

  • Gruninger M, Fox MS (1995) Methodology for the design and evaluation of ontologies. In: Proceedings of IJCAI’95, Workshop on Basic Ontological Issues in Knowledge Sharing

    Google Scholar 

  • Guha RV (1991) Contexts: a formalization and some applications. Stanford University

    Google Scholar 

  • Hepp M (2005) eClassOWL: a fully-fledged products and services ontology in OWL. In: The Poster Proceedings of International Semantic Web Conference (ISWC) 2005, Galway, Ireland

    Google Scholar 

  • Heyvaert P, De Meester B, Dimou A, Verborgh R (2018) Declarative Rules for Linked Data Generation at your Finger-tips! In: Proceedings of the 15th ESWC: Posters and Demo

    Google Scholar 

  • Iglesias E, Jozashoori S, Chaves-Fraga D, Collarana D, Vidal ME (2020) SDM-RDFizer: An RML interpreter for the efficient creation of RDF knowledge graphs. In: Proceedings of the 29th ACM International Conference on Information and Knowledge Management, Association for Computing Machinery, New York, NY, USA, CIKM’20, pp 3039–3046. https://doi.org/10.1145/3340531.3412881

  • Kärle E, Simsek U, Fensel D (2017) semantify.it, a platform for creation, publication and distribution of semantic annotations. In: Proceedings of SEMAPRO 2017: The Eleventh International Conference on Advances in Semantic Processing, Barcelona, November 25–29, pp 22–30

    Google Scholar 

  • Kotis K, Vouros GA, Alonso JP (2005) HCOME: a tool-supported methodology for engineering living ontologies. In: Semantic Web and Databases: Second International Workshop, SWDB 2004, Toronto, Canada, August 29–30, 2004, Revised Selected Papers 2, Springer, pp 155–166

    Google Scholar 

  • Lanthaler M, Gütl C (2013) Hydra: a vocabulary for hypermedia-driven Web APIs. LDOW 996:35–38

    Google Scholar 

  • Lefrançois M, Zimmermann A, Bakerally N (2017) Flexible RDF generation from RDF and heterogeneous data sources with SPARQL-Generate. In: Knowledge Engineering and Knowledge Management: EKAW 2016 Satellite Events, EKM and Drift-an-LOD, Bologna, Italy, November 19–23, 2016, Revised Selected Papers, Springer, pp 131–135

    Google Scholar 

  • Lenat DB, Guha RV (1989) Building large knowledge-based systems; representation and inference in the Cyc project. Addison-Wesley

    Google Scholar 

  • Li H, Armiento R, Lambrix P (2020) An ontology for the materials design domain. In: Pan JZ, Tamma V, d’Amato C, Janowicz K, Fu B, Polleres A, Seneviratne O, Kagal L (eds) The Semantic Web – ISWC 2020. Springer, Cham, pp 212–227

    Chapter  Google Scholar 

  • Lourdusamy R, John A (2018) A review on metrics for ontology evaluation. In: 2018 2nd International Conference on Inventive Systems and Control (ICISC), pp 1415–1421. https://doi.org/10.1109/ICISC.2018.8399041

  • Manning CD, Surdeanu M, Bauer J, Finkel JR, Bethard S, McClosky D (2014) The Stanford CoreNLP natural language processing toolkit. In: Proceedings of 52nd annual meeting of the association for computational linguistics: System demonstrations, pp 55–60

    Google Scholar 

  • Martin D, Burstein M, McDermott D, McIlraith S, Paolucci M, Sycara K, McGuinness DL, Sirin E, Srinivasan N (2007) Bringing semantics to web services with OWL-S. World Wide Web 10:243–277

    Article  Google Scholar 

  • Masolo C, Borgo S, Gangemi A, Guarino N, Oltramari A (2003) WonderWeb deliverable D18: ontology library. Laboratory for Applied Ontology, ISTC-CNR

    Google Scholar 

  • Mausam M (2016) Open information extraction systems and downstream applications. In: Proceedings of the twenty-fifth international joint conference on artificial intelligence, pp 4074–4077

    Google Scholar 

  • Maynard D, Bontcheva K, Augenstein I (2016) Natural language processing for the semantic web. In: Ding Y, Groth P (eds) Synthesis lectures on the semantic web: theory and technology, vol 15. Morgan & Claypool Publishers, pp 1–184

    Google Scholar 

  • Michel F, Djimenou L, Zucker CF, Montagnat J (2017) xR2RML: relational and non-relational databases to RDF map** language. Technical report, CNRS

    Google Scholar 

  • Michel F, Faron-Zucker C, Gandon F (2018) Bridging Web APIs and linked data with SPARQL micro-services. In: The Semantic Web: ESWC 2018 Satellite Events: ESWC 2018 Satellite Events, Heraklion, Crete, Greece, June 3–7, 2018, Revised Selected Papers 15, Springer, pp 187–191

    Google Scholar 

  • Mitchell T, Cohen W, Hruschka E, Talukdar P, Yang B, Betteridge J, Carlson A, Dalvi B, Gardner M, Kisiel B et al (2018) Never-ending learning. Commun ACM 61(5):103–115

    Article  Google Scholar 

  • Neches R, Fikes RE, Finin T, Gruber T, Patil R, Senator T, Swartout WR (1991) Enabling technology for knowledge sharing. AI Mag 12(3):36–36

    Google Scholar 

  • Noy NF, McGuinness DL (2001) Ontology development 101: a guide to creating your first ontology. Stanford University, Stanford, CA

    Google Scholar 

  • Paulheim H (2018) Machine learning with and for semantic web knowledge graphs. In: Reasoning web learning, uncertainty, streaming, and scalability: 14th International Summer School 2018, Esch-sur-Alzette, Luxembourg, September 22–26, 2018, Tutorial Lectures 14, pp 110–114

    Google Scholar 

  • Pinto HS, Staab S, Tempich C (2004) Diligent: towards a fine-grained methodology for distributed, loosely-controlled and evolving engineering of ontologies. ECAI 16:393

    Google Scholar 

  • Poveda-Villalon M, Fernandez-Izquierdo A, Fernandez-Lopez M, Garcia-Castro R (2022) LOT: an industrial oriented ontology engineering framework. Eng Appl Artif Intell 111:104755. https://doi.org/10.1016/j.engappai.2022.104755. https://www.sciencedirect.com/science/article/pii/S0952197622000525

    Article  Google Scholar 

  • Radford A, Narasimhan K, Salimans T, Sutskever I, et al (2018) Improving language understanding by generative pre-training. Technical report. https://www.cs.ubc.ca/amuham01/LING530/papers/radford2018improving.pdf

  • Sack H (2015) Ontology alignment. OpenHPI tutorial - knowledge engineering with semantic web technologies. https://open.hpi.de/courses/semanticweb2015/items/2d5hp8qEjA2Mm0rXLtLG4v

  • Schreiber AT, Schreiber G, Akkermans H, Anjewierden A, Shadbolt N, de Hoog R, Van de Velde W, Wielinga B (2000) Knowledge engineering and management: the CommonKADS methodology. MIT Press

    Google Scholar 

  • ÅžimÅŸek U, Kärle E, Fensel D (2018) Machine readable Web APIs with schema.org action annotations. Procedia Comput Sci 137:255–261

    Article  Google Scholar 

  • ÅžimÅŸek U, Kärle E, Fensel D (2019) RocketRML - a NodeJS implementation of a use-case specific RML mapper. In: Proceedings of 1st Knowledge Graph Building Workshop co-located with 16th Extended Semantic Web Conference (ESWC), Portoroz, Slovenia, June 3, 2019. CEUR, vol 2489

    Google Scholar 

  • ÅžimÅŸek U, Angele K, Kärle E, Panasiuk O, Fensel D (2020) Domain-specific customization of schema.org based on SHACL. In: The Semantic Web–ISWC 2020: 19th International Semantic Web Conference, Athens, Greece, November 2–6, 2020, Proceedings, Part II 19, Springer, pp 585–600

    Google Scholar 

  • Simsek U, Kärle E, Angele K, Huaman E, Opdenplatz J, Sommer D, Umbrich J, Fensel D (2022) A knowledge graph perspective on knowledge engineering. SN Comput Sci 4(1):16

    Article  Google Scholar 

  • Studer R, Benjamins VR, Fensel D (1998) Knowledge engineering: Principles and methods. Data Knowl Eng 25(1–2):161–197

    Article  Google Scholar 

  • Suarez-Figueroa MC (2007) D5.3.1 NeOn development process and ontology life cycle. NEON Project Consortium, Technical Report

    Google Scholar 

  • Sure Y, Staab S, Studer R (2004) On-to-knowledge methodology (OTKM). In: Handbook on ontologies. Springer, pp 117–132

    Chapter  Google Scholar 

  • Swartout B, Patil R, Knight K, Russ T (1996) Toward distributed use of large-scale ontologies. In: Proceedings of the tenth workshop on knowledge acquisition for knowledge-based systems, vol 138, p 25

    Google Scholar 

  • Uschold M, King M (1995) Towards a methodology for building ontologies. Technical report

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Serles, U., Fensel, D. (2024). Knowledge Creation. In: An Introduction to Knowledge Graphs. Springer, Cham. https://doi.org/10.1007/978-3-031-45256-7_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-45256-7_18

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-45255-0

  • Online ISBN: 978-3-031-45256-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Navigation