Mark Alan Musen

• Professor at Stanford University

BioPortal (https://bioportal.bioontology.org) is the world’s most comprehensive repository of biomedical ontologies. It provides infrastructure for finding, sharing, searching, and utilizing biomedical ontologies. Launched in 2005, BioPortal now includes 1549 ontologies (1182 of them public). Its open, freely accessible website enables anyone (i) t...

In the age of big data, it is important for primary research data to follow the FAIR principles of findability, accessibility, interoperability, and reusability. Data harmonization enhances interoperability and reusability by aligning heterogeneous data under standardized representations, benefiting both repository curators responsible for upholdin...

Scientists increasingly recognize the importance of providing rich, standards-adherent metadata to describe their experimental results. Despite the availability of sophisticated tools to assist in the process of data annotation, investigators generally seem to prefer to use spreadsheets when supplying metadata, despite the limitations of spreadshee...

Current metadata often suffer from incompleteness, inconsistency, and incorrect formatting, hindering effective data reuse and discovery. Using GPT-4 and a metadata knowledge base (CEDAR), we devised a method that standardizes metadata in scientific data sets, ensuring the adherence to community standards. The standardization process involves corre...

The COVID-19 pandemic highlighted the urgent need for robust systems to enable rapid data collection, integration, and analysis for public health responses. Existing approaches often relied on disparate, non-interoperable systems, creating bottlenecks in comprehensive analyses and timely decision-making. To address these challenges, the U.S. Nation...

Ontologies and knowledge graphs (KGs) are general-purpose computable representations of some domain, such as human anatomy, and are frequently a crucial part of modern information systems. Most of these structures change over time, incorporating new knowledge or information that was previously missing. Managing these changes is a challenge, both in...

The Human Reference Atlas (HRA) for the healthy, adult body is developed by a team of international, interdisciplinary experts across 20+ consortia. It provides standard terminologies and data structures for describing specimens, biological structures, and spatial positions of experimental datasets and ontology-linked reference anatomical structure...

Annotation with widely used, well-structured ontologies, combined with the use of ontology-aware software tools, ensures data and analyses are Findable, Accessible, Interoperable and Reusable (FAIR). Standardized terms with synonyms support lexical search. Ontology structure supports biologically meaningful grouping of annotations (typically by loc...

Ontologies and knowledge graphs (KGs) are general-purpose computable representations of some domain, such as human anatomy, and are frequently a crucial part of modern information systems. Most of these structures change over time, incorporating new knowledge or information that was previously missing. Managing these changes is a challenge, both in...

Scientists increasingly recognize the importance of providing rich, standards-adherent metadata to describe their experimental results. Despite the availability of sophisticated tools to assist in the process of data annotation, investigators generally seem to prefer to use spreadsheets when supplying metadata, despite the limitations of spreadshee...

There is an explosion in the number of ontologies and semantic artefacts being produced in science. This paper discusses the need for common platforms to receive, host, serve, align, and enable their reuse. Ontology repositories and semantic artefact catalogues are necessary to address this need and to make ontologies FAIR (Findable, Accessible, In...

With the global increase in experimental data artifacts, harnessing them in a unified fashion leads to a major stumbling block - bad metadata. To bridge this gap, this work presents a Natural Language Processing (NLP) informed application, called FAIRMetaText, that compares metadata. Specifically, FAIRMetaText analyzes the natural language descript...

The Human Reference Atlas (HRA) is defined as a comprehensive, three-dimensional (3D) atlas of all the cells in the healthy human body. It is compiled by an international team of experts who develop standard terminologies that they link to 3D reference objects, describing anatomical structures. The third HRA release (v1.2) covers spatial reference...

Motivation: Knowledge graphs (KG) are being adopted in industry, commerce, and academia. Biomedical KG present a challenge due to the complexity, size, and heterogeneity of the underlying information. Results: In this work we present the Scalable Precision Medicine Open Knowledge Engine (SPOKE), a biomedical KG connecting millions of concepts vi...

It is challenging to determine whether datasets are findable, accessible, interoperable, and reusable (FAIR) because the FAIR Guiding Principles refer to highly idiosyncratic criteria regarding the metadata used to annotate datasets. Specifically, the FAIR principles require metadata to be “rich” and to adhere to “domain-relevant” community standar...

The Human Reference Atlas (HRA) is defined as a comprehensive, three-dimensional (3D) atlas of all the cells in the healthy human body. It is compiled by an international team of experts that develop standard terminologies linked to 3D reference objects describing anatomical structures. The third HRA release (v1.2) covers spatial reference data and...

Funders and investigators must demand appropriate metadata standards to take data from foul to FAIR. Funders and investigators must demand appropriate metadata standards to take data from foul to FAIR. Portrait of Mark A. Musen Portrait of Mark A. Musen

Sharing experimental data and making data findable, accessible, interoperable, and reusable (FAIR) are of growing importance to funders, publishers, and to scientists themselves. Evaluating whether datasets are FAIR is challenging because the FAIR Guiding Principles include highly idiosyncratic criteria regarding the metadata used to annotate datas...

Knowledge graphs are developed and used in academia and industry to tackle complex challenges in healthcare and biomedical research. Elsevier's Healthcare Knowledge Graph (HG) is developed by extracting and integrating medical knowledge from several heterogeneous sources such as clinical guidelines, medical textbooks, and legacy databases. The HG p...

Knowledge representation and reasoning (KR&R) has been successfully implemented in many fields to enable computers to solve complex problems with AI methods. However, its application to biomedicine has been lagging in part due to the daunting complexity of molecular and cellular pathways that govern human physiology and pathology. In this article,...

Knowledge representation and reasoning (KR&R) has been successfully implemented in many fields to enable computers to solve complex problems with AI methods. However, its application to biomedicine has been lagging in part due to the daunting complexity of molecular and cellular pathways that govern human physiology and pathology. In this article,...

When applying ontologies in practice, human and machine agents need to ensure that their provenance is trustworthy and it can be relied upon the contained concepts. This is particularly crucial for sensitive tasks such as in medical diagnostics or for safety-critical applications. In this paper, we propose an architecture for the decentralized atte...

Ontologies are shared, formal conceptualizations of a domain that are consumed by human and machine agents alike. Trust in ontolo-gies is a central issue for their application. For example, machine learning algorithms for medical diagnosis may rely on the correctness of ontolo-gies and could potentially deliver false results. For enhancing trust, w...

Objective Although social and environmental factors are central to provider–patient interactions, the data that reflect these factors can be incomplete, vague, and subjective. We sought to create a conceptual framework to describe and classify data about presence, the domain of interpersonal connection in medicine. Methods Our top-down approach fo...

The limited volume of COVID-19 data from Africa raises concerns for global genome research, which requires a diversity of genotypes for accurate disease prediction, including on the provenance of the new SARS-CoV-2 mutations. The Virus OutbreakData Network (VODAN)-Africa studied the possibility of increasing the production of clinical data, finding...

This chapter discusses information technology that provides health-care workers and patients with situation-specific advice that can inform their decision making. The intricacies of the clinical environment, new legislative mandates, and the increasing complexity of medical practice all escalate the demand for clinical decision-support systems (CDS...

Objective Although social and environmental factors are central to provider patient interactions, the data that reflect these factors can be incomplete, vague, and subjective. We sought to create a conceptual framework to describe and classify data about presence, the domain of interpersonal connection in medicine. Methods Our top down approach for...

While the biomedical community has published several “open data” sources in the last decade, most researchers still endure severe logistical and technical challenges to discover, query, and integrate heterogeneous data and knowledge from multiple sources. To tackle these challenges, the community has experimented with Semantic Web and linked data t...

Metadata that are structured using principled schemas and that use terms from ontologies are essential to making biomedical data findable and reusable for downstream analyses. The largest source of metadata that describes the experimental protocol, funding, and scientific leadership of clinical studies is ClinicalTrials.gov. We evaluated whether va...

An overarching WHO-FIC Content Model will allow uniform modeling of classifications in the WHO Family of International Classifications (WHO-FIC). It will facilitate the development of a unified Foundation to generate variants of ICD, ICF, and ICHI as linearizations and will promote their joint use. We describe a conceptualization and formalization...

Objective: To assess usability and usefulness of a machine learning-based order recommender system applied to simulated clinical cases. Materials and methods: 43 physicians entered orders for 5 simulated clinical cases using a clinical order entry interface with or without access to a previously developed automated order recommender system. Case...

The National Institutes of Health's (NIH) Human Biomolecular Atlas Program (HuBMAP) aims to create a comprehensive high-resolution atlas of all the cells in the healthy human body. Multiple laboratories across the United States are collecting tissue specimens from different organs of donors who vary in sex, age, and body size. Integrating and harmo...

An overarching WHO-FIC Content Model will allow uniform modeling of classifications in the WHO Family of International Classifications (WHO-FIC) and promote their joint use. We provide an initial conceptualization of such a model.

While the biomedical community has published several "open data" sources in the last decade, most researchers still endure severe logistical and technical challenges to discover, query, and integrate heterogeneous data and knowledge from multiple sources. To tackle these challenges, the community has experimented with Semantic Web and linked data t...

Clinical decision support tools that automatically disseminate patterns of clinical orders have the potential to improve patient care by reducing errors of omission and streamlining physician workflows. However, it is unknown if physicians will accept such tools or how their behavior will be affected. In this randomized controlled study, we exposed...

Developing promising treatments in biomedicine often requires aggregation and analysis of data from disparate sources across the healthcare and research spectrum. To facilitate these approaches, there is a growing focus on supporting interoperation of datasets by standardizing data-capture and reporting requirements. Common Data Elements (CDEs)-pre...

Objective: To determine whether clinicians will use machine learned clinical order recommender systems for electronic order entry for simulated inpatient cases, and whether such recommendations impact the clinical appropriateness of the orders being placed. Materials and Methods: 43 physicians used a clinical order entry interface for five simulate...

Objective: ClinicalTrials.gov is a registry of clinical-trial metadata whose use is required by many funding agencies and scientific publishers. Metadata are essential to the reuse of data, but issues such as heterogenous metadata schemas, inconsistent values, and usage of free text instead of controlled terms pervade many metadata repositories. Ou...

The FAIR principles articulate the behaviors expected from digital artifacts that are Findable, Accessible, Interoperable and Reusable by machines and by people. Although by now widely accepted, the FAIR Principles by design do not explicitly consider actual implementation choices enabling FAIR behaviors. As different communities have their own, of...

Pinterest is a popular Web application that has over 250 million active users. It is a visual discovery engine for finding ideas for recipes, fashion, weddings, home decoration, and much more. In the last year, the company adopted Semantic Web technologies to create a knowledge graph that aims to represent the vast amount of content and users on Pi...

In this deliberately provocative position paper, we claim that more than ten years into Linked Data there are still (too?) many unresolved challenges towards arriving at a truly machine-readable and decentralized Web of data. We take a deeper look at key challenges in usage and adoption of Linked Data from the ever-present "LOD cloud" diagram. Here...

The biomedical data landscape is fragmented with several isolated, heterogeneous data and knowledge sources, which use varying formats, syntaxes, schemas, and entity notations, existing on the Web. Biomedical researchers face severe logistical and technical challenges to query, integrate, analyze, and visualize data from multiple diverse sources in...

Pinterest is a popular Web application that has over 250 million active users. It is a visual discovery engine for finding ideas for recipes, fashion, weddings, home decoration, and much more. In the last year, the company adopted Semantic Web technologies to create a knowledge graph that aims to represent the vast amount of content and users on Pi...

The metadata about scientific experiments published in online repositories have been shown to suffer from a high degree of representational heterogeneity—there are often many ways to represent the same type of information, such as a geographical location via its latitude and longitude. To harness the potential that metadata have for discovering sci...

The Center for Expanded Data Annotation and Retrieval (CEDAR) aims to revolutionize the way that metadata describing scientific experiments are authored. The software we have developed--the CEDAR Workbench--is a suite of Web-based tools and REST APIs that allows users to construct metadata templates, to fill in templates to generate high-quality me...

We present WebProtégé, a tool to develop ontologies represented in the Web Ontology Language (OWL). WebProtégé is a cloud-based application that allows users to collaboratively edit OWL ontologies, and it is available for use at https://webprotege.stanford.edu. WebProtégé currently hosts more than 68,000 OWL ontology projects and has over 50,000 us...

Metadata-the machine-readable descriptions of the data-are increasingly seen as crucial for describing the vast array of biomedical datasets that are currently being deposited in public repositories. While most public repositories have firm requirements that metadata must accompany submitted datasets, the quality of those metadata is generally very...

The metadata about scientific experiments published in online repositories have been shown to suffer from a high degree of representational heterogeneity---there are often many ways to represent the same type of information, such as a geographical location via its latitude and longitude. To harness the potential that metadata have for discovering s...

This paper introduces HopRank, an algorithm for modeling human navigation on semantic networks. HopRank leverages the assumption that users know or can see the whole structure of the network. Therefore, besides following links, they also follow nodes at certain distances (i.e., k-hop neighborhoods), and not at random as suggested by PageRank, which...

There is a growing acknowledgement in the scientific community of the importance of making experimental data machine findable, accessible, interoperable, and reusable (FAIR). Recognizing that high quality metadata are essential to make datasets FAIR, members of the GO FAIR Initiative and the Research Data Alliance (RDA) have initiated a series of w...

We present an analytical study of the quality of metadata about samples used in biomedical experiments. The metadata under analysis are stored in two well-known databases: BioSample—a repository managed by the National Center for Biotechnology Information (NCBI), and BioSamples—a repository managed by the European Bioinformatics Institute (EBI). We...

We present the WebProtégé application to develop ontologies represented in the Web Ontology Language (OWL). WebProtégé is a cloud-based application that allows users to collaboratively edit OWL ontologies, and it is available for use at https://webprotege.stanford.edu. WebProtégé currently hosts more than 66,000 OWL ontology projects and has over 5...

BioPortal is widely regarded to be the world's most comprehensive repository of biomedical ontologies. With a coverage of many biomedical subfields by 716 ontologies (June 27, 2018), BioPortal is an extremely diverse repository. BioPortal maintains easily accessible information about the ontologies submitted by ontology curators. This includes size...

We present an analytical study of the quality of metadata about samples used in biomedical experiments. The metadata under analysis are stored in two well- known databases: BioSample---a repository managed by the National Center for Biotechnology Information (NCBI), and BioSamples---a repository managed by the European Bioinformatics Institute (EBI...

The adaptation of high-throughput sequencing to the B cell receptor and T cell receptor has made it possible to characterize the adaptive immune receptor repertoire (AIRR) at unprecedented depth. These AIRR sequencing (AIRR-seq) studies offer tremendous potential to increase the understanding of adaptive immune responses in vaccinology, infectious...

Background Public biomedical data repositories often provide web-based interfaces to collect experimental metadata. However, these interfaces typically reflect the ad hoc metadata specification practices of the associated repositories, leading to a lack of standardization in the collected metadata. This lack of standardization limits the ability of...

There is an expectation that scientists will archive their experimental data online in public repositories to enable other investigators to verify their work and to re-explore their data in search of new discoveries. When left to their own devices, however, scientists do a poor job creating the metadata that describe their datasets. A lack of stand...

In biomedicine, high-quality metadata are crucial for finding experimental datasets, for understanding how experiments were performed, and for reproducing those experiments. Despite the recent focus on metadata, the quality of metadata available in public repositories continues to be extremely poor. A key difficulty is that the typical metadata acq...

Adverse drug reactions (ADR) result in significant morbidity and mortality in patients, and a substantial proportion of these ADRs are caused by drug-drug interactions (DDIs). Pharmacovigilance methods are used to detect unanticipated DDIs and ADRs by mining Spontaneous Reporting Systems, such as the US FDA Adverse Event Reporting System (FAERS). H...

Gene Ontology (GO) enrichment analysis is ubiquitously used for interpreting high throughput molecular data and generating hypotheses about underlying biological phenomena of experiments. However, the two building blocks of this analysis — the ontology and the annotations — evolve rapidly. We used gene signatures derived from 104 disease analyses t...

Biomedical ontologies are large: Several ontologies in the BioPortal repository contain thousands or even hundreds of thousands of entities. The development and maintenance of such large ontologies is difficult. To support ontology authors and repository developers in their work, it is crucial to improve our understanding of how these ontologies ar...

Gene Ontology (GO) enrichment analysis is ubiquitously used for interpreting high throughput molecular data and generating hypotheses about underlying biological phenomena of experiments. However, the two building blocks of this analysis - the ontology and the annotations - evolve rapidly. We used gene signatures derived from 104 disease analyses t...

Many vocabularies and ontologies are produced to represent and annotate agronomic data. However, those ontologies are spread out, in different formats, of different size, with different structures and from overlapping domains. Therefore, there is need for a common platform to receive and host them, align them, and enabling their use in agro-informa...

Adverse drug reactions (ADR) result in significant morbidity and mortality in patients, and a substantial proportion of these ADRs are caused by drug-drug interactions (DDIs). Pharmacovigilance methods are used to detect unan-ticipated DDIs and ADRs by mining Spontaneous Reporting Systems, such as the US FDA Adverse Event Reporting System (FAERS)....

The Center for Expanded Data Annotation and Retrieval (CEDAR) aims to revolutionize the way that metadata describing scientific experiments are authored. The software we have developed—the CEDAR Workbench—is a suite of Web-based tools and REST APIs that allows users to construct metadata templates, to fill in templates to generate high-quality meta...

BiOnIC is a catalog of aggregated statistics of user clicks, queries, and reuse counts for access to over 200 biomedical ontologies. BiOnIC also provides anonymized sequences of classes accessed by users over a period of four years. To generate the statistics, we processed the access logs of BioPortal, a large open biomedical ontology repository. W...

The Gene Expression Omnibus (GEO) contains more than two million digital samples from functional genomics experiments amassed over almost two decades. However, individual sample meta-data remains poorly described by unstructured free text attributes preventing its largescale reanalysis. We introduce the Search Tag Analyze Resource for GEO as a web...

The metadata about scientific experiments are crucial for finding, reproducing, and reusing the data that the metadata describe. We present a study of the quality of the metadata stored in BioSample--a repository of metadata about samples used in biomedical experiments managed by the U.S. National Center for Biomedical Technology Information (NCBI)...

Background Structured data acquisition is a common task that is widely performed in biomedicine. However, current solutions for this task are far from providing a means to structure data in such a way that it can be automatically employed in decision making (e.g., in our example application domain of clinical functional assessment, for determining...

Clinicians and clinical decision-support systems often follow pharmacotherapy recommendations for patients based on clinical practice guidelines (CPGs). In multimorbid patients, these recommendations can potentially have clinically significant drug–drug interactions (DDIs). In this study, we describe and validate a method for programmatically detec...

This proposal is a response to NIH's call for creation of a Data Commons (RM-17-026). The Commons must support use cases of many stakeholders who need access to scholarly process, content, and outcomes in pursuit of knowledge. Moreover, the Commons must be flexible enough to respect researchers’ idiosyncratic workflows, yet specific enough to solve...

Background Ontologies and controlled terminologies have become increasingly important in biomedical research. Researchers use ontologies to annotate their data with ontology terms, enabling better data integration and interoperability across disparate datasets. However, the number, variety and complexity of current biomedical ontologies make it cum...

Biomedical ontologies often reuse content (i.e., classes and properties) from other ontologies. Content reuse enables a consistent representation of a domain and reusing content can save an ontology author significant time and effort. Prior studies have investigated the existence of reused terms among the ontologies in the NCBO BioPortal, but as of...