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SciGraph
Type of site
Search engine
Created bySpringer Nature
URLscigraph.springernature.com/explorer
LaunchedMarch 2017 (2017-03)

SciGraph is a search engine tool developed by Springer Nature. The technology, which is considered a Linked Open Dat (LOD) platform,[1] collects information that covers the research landscape, which includes research projects, publications, conferences, funding agencies, and others.[2] Key features of the platform include the detailed semantic description of the relationship of information and the visualization of the scholarly domain.

Development[edit]

The development of SciGraph began with an initiative to create a platform that will host Springer Nature's entire publication archive, which cover texts published as early as 1815.[3] The number of these resources is reported to be about 13 million.[3] The technology behind the platform was built on earlier Springer Nature projects developed for the purpose of collecting information on the research landscape.[4] The first SciGraph data set was published in February 2017.[4] The platform was launched in March 2017 and significantly expanded with the addition of publications of key partners.[5] The datasets span a broad range of topics, which include computer science, medicine, life sciences, chemistry, engineering, and astronomy, among others.[6] The developers also plan to include citations, patents, and clinical trials in the future.[7]

Technology[edit]

SciGraph constitutes 1.5 to 2 billion triples where a triple is formatted as "subject-predicate-object" and could link any subject or concept through a predicate (verb) to another object, demonstrating the type of relationship that exists between them.[8] Its graph structure is used by other academic search engines such as Semantic Scholar.[9]

SciGraph collects data from Springer Nature and its partners from the scholarly domain as well as funders, research projects, conferences, affiliations, and publications.[10] The collected information serves as rich semantic description of how information is related and it also provides a visualization of the scholarly domain.[11] The platform has been considered the only large-scale dataset that reconciles authors' affiliations through the disambiguation and linking with external authoritative datasets according to institutions.[6]

References[edit]

  1. ^ "Springer Nature SciGraph". EurekAlert!. Retrieved 2021-10-25.
  2. ^ Rucci, Enzo (2020). Cloud Computing, Big Data & Emerging Topics: 8th Conference, JCC-BD&ET 2020, La Plata, Argentina, September 8-10, 2020, Proceedings. Cham, Switzerland: Springer Nature. p. 86. ISBN 978-3-030-61217-7.
  3. ^ a b "Springer Nature Uses LOD to Create a Rich Database for Scientists to Work Together". Ontotext. Retrieved 2021-11-04.
  4. ^ a b Hammond, Tony; Pasin, Michele; Theodoris, Evangelos. "Data integration and disintegration: Managing Springer Nature SciGraph with SHACL and OWL" (PDF). Retrieved October 26, 2021.{{cite web}}: CS1 maint: url-status (link)
  5. ^ "SciGraph – Access". Retrieved 2021-10-25.
  6. ^ a b González-Beltrán, Alejandra; Osborne, Francesco; Peroni, Silvio; Vahdati, Sahar (2018). Semantics, Analytics, Visualization: 3rd International Workshop, SAVE-SD 2017, Perth, Australia, April 3, 2017, and 4th International Workshop, SAVE-SD 2018, Lyon, France, April 24, 2018, Revised Selected Papers. Cham: Springer. p. 64. ISBN 978-3-030-01378-3.
  7. ^ Garcia-Silva, Andres and José Manuél Gómez-Pérez (2018). “Not Just About Size - A Study on the Role of Distributed Word Representations in the Analysis of Scientific Publications.” DL4KGS@ESWC.
  8. ^ Light, Ryan; Moody, James (2020). The Oxford Handbook of Social Networks. New York: Oxford University Press. p. 603. ISBN 978-0-19-025176-5.
  9. ^ Jose, Joemon M.; Yilmaz, Emine; Magalhães, João; Castells, Pablo; Ferro, Nicola; Silva, Mário J.; Martins, Flávio (2020). Advances in Information Retrieval: 42nd European Conference on IR Research, ECIR 2020, Lisbon, Portugal, April 14–17, 2020, Proceedings, Part I. Cham, Switzerland: Springer Nature. p. 254. ISBN 978-3-030-45438-8.
  10. ^ Bespalov, Anton; Michel, Martin C.; Steckler, Thomas (2020). Good Research Practice in Non-Clinical Pharmacology and Biomedicine. Cham: Springer Nature. p. 343. ISBN 978-3-030-33655-4.
  11. ^ Gayo, Jose Emilio Labra; Prud'hommeaux, Eric; Boneva, Iovka; Kontokostas, Dimitris (2017). Validating RDF Data. Morgan & Claypool Publishers. p. 212. ISBN 978-1-68173-164-3.
source: https://web.archive.org/web/20220302212619/https://en.wikipedia.org/wiki/SciGraph

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