The Linked Data Modeling Language (LinkML): A General-Purpose Data Modeling Framework Grounded in Machine-Readable Semantics

Sierra Moxon; Harold Solbrig; Deepak Unni; Dazhi Jiao; Richard Bruskiewich; James Balhoff; Gaurav Vaidya; William Duncan; Harshad Hegde; Mark Miller; Matthew Brush; Nomi Harris; Melissa Haendel; Christopher Mungall

The Linked Data Modeling Language (LinkML): A General-Purpose Data Modeling Framework Grounded in Machine-Readable Semantics

Sierra Moxon
, Harold Solbrig
, Deepak Unni
, Dazhi Jiao
, Richard Bruskiewich
, James Balhoff
, Gaurav Vaidya
, William Duncan
, Harshad Hegde
, Mark Miller
, Matthew Brush
, Nomi Harris
, Melissa Haendel
, Christopher Mungall

School of Medicine

Research output: Contribution to journal › Conference article › peer-review

Abstract

Data integration is a major challenge in the life sciences, due to heterogeneity, complexity, the proliferation of ad-hoc formats and data structures, and poor compliance with FAIR guidelines. The Linked data Modeling Language (LinkML, https://linkml.github.io) is an object-oriented data modeling framework that aims to bring semantic web standards to the masses, simplifying the production of FAIR ontology-ready data. It can be used for schematizing a variety of kinds of data, ranging from simple flat checklist-style standards to complex interrelated normalized data utilizing polymorphism/inheritance. Although it is still a young and evolving standard, LinkML is already in use across a wide variety of projects with different applications including cancer data harmonization, environmental genomics, and knowledge graph integration.

Original language	English (US)
Pages (from-to)	148-151
Number of pages	4
Journal	CEUR Workshop Proceedings
Volume	3073
State	Published - 2021
Event	2021 International Conference on Biomedical Ontologies, ICBO 2021 - Bozen-Bolzano, Italy Duration: Sep 16 2021 → Sep 18 2021

Keywords

JSON-schema
Ontology
RDF
Semantic web

ASJC Scopus subject areas

General Computer Science

Cite this

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title = "The Linked Data Modeling Language (LinkML): A General-Purpose Data Modeling Framework Grounded in Machine-Readable Semantics",

abstract = "Data integration is a major challenge in the life sciences, due to heterogeneity, complexity, the proliferation of ad-hoc formats and data structures, and poor compliance with FAIR guidelines. The Linked data Modeling Language (LinkML, https://linkml.github.io) is an object-oriented data modeling framework that aims to bring semantic web standards to the masses, simplifying the production of FAIR ontology-ready data. It can be used for schematizing a variety of kinds of data, ranging from simple flat checklist-style standards to complex interrelated normalized data utilizing polymorphism/inheritance. Although it is still a young and evolving standard, LinkML is already in use across a wide variety of projects with different applications including cancer data harmonization, environmental genomics, and knowledge graph integration. ",

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author = "Sierra Moxon and Harold Solbrig and Deepak Unni and Dazhi Jiao and Richard Bruskiewich and James Balhoff and Gaurav Vaidya and William Duncan and Harshad Hegde and Mark Miller and Matthew Brush and Nomi Harris and Melissa Haendel and Christopher Mungall",

note = "Funding Information: This work is supported in part by the Genomic Science Program in the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (BER) under contract number DE-AC02-05CH112(LBN3L). A1dditional support was provided by NIH OD R4 OD2011883, NHGRI Center of Excellence in Genome Sciences R1 HMG010860, NHGRI 5U01HG00-03,9and4NCI IA5A 3 \#ACO201-070-00000.01 Publisher Copyright: {\textcopyright} 2021 Copyright for this paper by its authors.; 2021 International Conference on Biomedical Ontologies, ICBO 2021 ; Conference date: 16-09-2021 Through 18-09-2021",

year = "2021",

language = "English (US)",

volume = "3073",

pages = "148--151",

journal = "CEUR Workshop Proceedings",

issn = "1613-0073",

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T1 - The Linked Data Modeling Language (LinkML)

T2 - 2021 International Conference on Biomedical Ontologies, ICBO 2021

AU - Moxon, Sierra

AU - Solbrig, Harold

AU - Unni, Deepak

AU - Jiao, Dazhi

AU - Bruskiewich, Richard

AU - Balhoff, James

AU - Vaidya, Gaurav

AU - Duncan, William

AU - Hegde, Harshad

AU - Miller, Mark

AU - Brush, Matthew

AU - Harris, Nomi

AU - Haendel, Melissa

AU - Mungall, Christopher

N1 - Funding Information: This work is supported in part by the Genomic Science Program in the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research (BER) under contract number DE-AC02-05CH112(LBN3L). A1dditional support was provided by NIH OD R4 OD2011883, NHGRI Center of Excellence in Genome Sciences R1 HMG010860, NHGRI 5U01HG00-03,9and4NCI IA5A 3 #ACO201-070-00000.01 Publisher Copyright: © 2021 Copyright for this paper by its authors.

PY - 2021

Y1 - 2021

N2 - Data integration is a major challenge in the life sciences, due to heterogeneity, complexity, the proliferation of ad-hoc formats and data structures, and poor compliance with FAIR guidelines. The Linked data Modeling Language (LinkML, https://linkml.github.io) is an object-oriented data modeling framework that aims to bring semantic web standards to the masses, simplifying the production of FAIR ontology-ready data. It can be used for schematizing a variety of kinds of data, ranging from simple flat checklist-style standards to complex interrelated normalized data utilizing polymorphism/inheritance. Although it is still a young and evolving standard, LinkML is already in use across a wide variety of projects with different applications including cancer data harmonization, environmental genomics, and knowledge graph integration.

AB - Data integration is a major challenge in the life sciences, due to heterogeneity, complexity, the proliferation of ad-hoc formats and data structures, and poor compliance with FAIR guidelines. The Linked data Modeling Language (LinkML, https://linkml.github.io) is an object-oriented data modeling framework that aims to bring semantic web standards to the masses, simplifying the production of FAIR ontology-ready data. It can be used for schematizing a variety of kinds of data, ranging from simple flat checklist-style standards to complex interrelated normalized data utilizing polymorphism/inheritance. Although it is still a young and evolving standard, LinkML is already in use across a wide variety of projects with different applications including cancer data harmonization, environmental genomics, and knowledge graph integration.

KW - JSON-schema

KW - Ontology

KW - RDF

KW - Semantic web

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UR - https://www.scopus.com/pages/publications/85124428968#tab=citedBy

M3 - Conference article

AN - SCOPUS:85124428968

SN - 1613-0073

VL - 3073

SP - 148

EP - 151

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

Y2 - 16 September 2021 through 18 September 2021

ER -

The Linked Data Modeling Language (LinkML): A General-Purpose Data Modeling Framework Grounded in Machine-Readable Semantics

Abstract

Keywords

ASJC Scopus subject areas

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