Biodiversity Information Science and Standards :
Conference Abstract
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Corresponding author: Roderic Page (roderic.page@glasgow.ac.uk)
Received: 01 Sep 2021 | Published: 01 Sep 2021
© 2021 Roderic Page
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Page R (2021) Knowledge Graphs. Biodiversity Information Science and Standards 5: e73796. https://doi.org/10.3897/biss.5.73796
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Knowledge graphs embody the idea of "everything connected to everything else." As attractive as this seems, there is a substantial gap between the dream of fully interconnected knowledge and the reality of data that is still mostly siloed, or weakly connected by shared strings such as taxonomic names. How do we move forward? Do we focus on building our own domain- or project-specific knowledge graphs, or do we engage with global projects such as Wikidata? Do we construct knowledge graphs, or focus on making our data "knowledge graph ready" by adopting structured markup in the hope that knowledge graphs will spontaneously self-assemble from that data? Do we focus on large-scale, database-driven projects (e.g., triple stores in the cloud), or do we rely on more localised and distributed approaches, such as annotations (e.g., hypothes.is), "content-hash" systems where a cryptographic hash of the data is also its identifier (
biodiversity knowledge graph, linked data
Roderic Page
TDWG 2021