SciGraph was a search engine tool developed bySpringer Nature, the former URL washttps://scigraph.springernature.com/explorer. The technology, which was considered aLinked Open Data (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.
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 includecomputer science,medicine,life sciences,chemistry,engineering, andastronomy, among others.[6] The developers also plan to include citations,patents, andclinical trials in the future.[7]
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 academicsearch engines such asSemantic 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]
