Search Results for author: Mark A. Musen

Found 10 papers, 1 papers with code

An Empirical Meta-analysis of the Life Sciences (Linked?) Open Data on the Web

1 code implementation7 Jun 2020 Maulik R. Kamdar, Mark A. Musen

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.

Use of OWL and Semantic Web Technologies at Pinterest

no code implementations3 Jul 2019 Rafael S. Gonçalves, Matthew Horridge, Rui Li, Yu Liu, Mark A. Musen, Csongor I. Nyulas, Evelyn Obamos, Dhananjay Shrouty, David Temple

In this paper, we present the engineering of an OWL ontology---the Pinterest Taxonomy---that forms the core of Pinterest's knowledge graph, the Pinterest Taste Graph.

Using association rule mining and ontologies to generate metadata recommendations from multiple biomedical databases

no code implementations21 Mar 2019 Marcos Martínez-Romero, Martin J. O'Connor, Attila L. Egyedi, Debra Willrett, Josef Hardi, John Graybeal, Mark A. Musen

The results show that our approach is able to use analyses of previous entered metadata coupled with ontology-based mappings to present users with accurate recommendations when authoring metadata.

Aligning Biomedical Metadata with Ontologies Using Clustering and Embeddings

no code implementations19 Mar 2019 Rafael S. Gonçalves, Maulik R. Kamdar, Mark A. Musen

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.

WebProtégé: A Cloud-Based Ontology Editor

no code implementations21 Feb 2019 Matthew Horridge, Rafael S. Gonçalves, Csongor I. Nyulas, Tania Tudorache, Mark A. Musen

We present WebProt\'eg\'e, a tool to develop ontologies represented in the Web Ontology Language (OWL).

The variable quality of metadata about biological samples used in biomedical experiments

no code implementations17 Aug 2018 Rafael S. Gonçalves, Mark A. Musen

By clustering metadata field names, we discovered there are often many distinct ways to represent the same aspect of a sample.

Metadata in the BioSample Online Repository are Impaired by Numerous Anomalies

no code implementations3 Aug 2017 Rafael S. Gonçalves, Martin J. O'Connor, Marcos Martínez-Romero, John Graybeal, Mark A. Musen

Only 9 out of 452 BioSample-specified fields ordinarily require ontology terms as values, and the quality of these controlled fields is better than that of uncontrolled ones, as even simple binary or numeric fields are often populated with inadequate values of different data types (e. g., only 27% of Boolean values are valid).


NCBO Ontology Recommender 2.0: An Enhanced Approach for Biomedical Ontology Recommendation

no code implementations18 Nov 2016 Marcos Martinez-Romero, Clement Jonquet, Martin J. O'Connor, John Graybeal, Alejandro Pazos, Mark A. Musen

To overcome this problem, in 2010 the National Center for Biomedical Ontology (NCBO) released the Ontology Recommender, which is a service that receives a biomedical text corpus or a list of keywords and suggests ontologies appropriate for referencing the indicated terms.

Discovering Beaten Paths in Collaborative Ontology-Engineering Projects using Markov Chains

no code implementations8 Jul 2014 Simon Walk, Philipp Singer, Markus Strohmaier, Tania Tudorache, Mark A. Musen, Natalya F. Noy

For example, the 11th revision of the ICD, which is currently under active development by the WHO contains nearly 50, 000 classes representing a vast variety of different diseases and causes of death.

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