Main page for documentation associated with knowledge graph creation and update for the Plants humanities project
In September 2018 Dumbarton Oaks and JSTOR Labs received partner grants from the National Endowment for the Humanities (NEH) to advance a Plant Humanities Initiative. These grants integrate elements of the digital humanities with scholarly programming, to set forth a new, interdisciplinary field that communicates the unparalleled significance of plants to human culture. The grant has three main goals: to provide innovative research and professional development opportunities for early-career humanists; to create a digital tool informed by the insights and needs of teachers and students as well as librarians and technical experts; and to supplement existing digitized resources with new primary source material, contextualize them, and disseminate them.
This knowledge graph aims to compliment that digital tool while extending current digitized resources. As such it employs Resource Description Framework (RDF) metadata standards that allow researchers to contribute to a semantic web architecture by cataloguing, navigating, and organizing data surrounding the cultural history of plants.
JSTOR Labs Plant Humanities Knowledge Graph (https://kg.jstor.org/wiki/Plants_humanities) emulates the technical and philosophical architecture of Wikidata. It is a collaboratively edited knowledge base committed to producing linked open data under a public domain license.
How much background do we need?
Links out to Global Plants: https://plants.jstor.org/
Discuss structure of kg. People -> Herbals -> Plants -> Uses
The Plant Humanities Knowledge Graph is a document-oriented database focused on items, which represent topics, concepts, or objects. Each item is identified by a unique, "PID," number that enables basic information about an item to be stored without favoring any particular language. Fundamentally, an item consists of a label, a description, and some number of statements.
Editing / Contributing
KG Query Service
The Labs Knowledge Graph Query Service (https://kg-query.jstor.org/) employs the standard SPARQL language to retrieve and manipulate data stored in the RDF format. SPARQL allows users to write queries as triples, conjunctions, disjunctions, and optional patterns.