ArticleJMIR medical informatics2020
Visualization Environment for Federated Knowledge Graphs: Development of an Interactive Biomedical Query Language and Web Application Interface.
Article in JMIR medical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Interactive network visualization of opioid crisis research: a tool for reinforcing data linkage skills for public health policy researchers.Frontiers in artificial intelligence · 2024Pooled it
- The ROBOKOP v1.0 knowledge graph system for exploring relationships between biomedical entities.Scientific reports · 2026Article
- Meeting report of the 37th International Conference on Antiviral Research in Gold Coast, Australia, May 20-24, 2024, organized by the International Society for Antiviral Research.Antiviral research · 2024Article
- Natural Language Processing and Graph Theory: Making Sense of Imaging Records in a Novel Representation Frame.JMIR medical informatics · 2022Article
- Dug: a semantic search engine leveraging peer-reviewed knowledge to query biomedical data repositories.Bioinformatics (Oxford, England) · 2022Article
- Demonstrating a systems approach for integrating disparate data streams to inform decisions on children's environmental health.BMC public health · 2022Article
- An approach for open multivariate analysis of integrated clinical and environmental exposures data.Informatics in medicine unlocked · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
backgroundEfforts are underway to semantically integrate large biomedical knowledge graphs using common upper-level ontologies to federate graph-oriented application programming interfaces (APIs) to the data. However, federation poses several challenges, including query routing to appropriate knowledge sources, generation and evaluation of answer subsets, semantic merger of those answer subsets, and visualization and exploration of results.
objectiveWe aimed to develop an interactive environment for query, visualization, and deep exploration of federated knowledge graphs.
methodsWe developed a biomedical query language and web application interphase-termed as Translator Query Language (TranQL)-to query semantically federated knowledge graphs and explore query results. TranQL uses the Biolink data model as an upper-level biomedical ontology and an API standard that has been adopted by the Biomedical Data Translator Consortium to specify a protocol for expressing a query as a graph of Biolink data elements compiled from statements in the TranQL query language. Queries are mapped to federated knowledge sources, and answers are merged into a knowledge graph, with mappings between the knowledge graph and specific elements of the query. The TranQL interactive web application includes a user interface to support user exploration of the federated knowledge graph.
resultsWe developed 2 real-world use cases to validate TranQL and address biomedical questions of relevance to translational science. The use cases posed questions that traversed 2 federated Translator API endpoints: Integrated Clinical and Environmental Exposures Service (ICEES) and Reasoning Over Biomedical Objects linked in Knowledge Oriented Pathways (ROBOKOP). ICEES provides open access to observational clinical and environmental data, and ROBOKOP provides access to linked biomedical entities, such as "gene," "chemical substance," and "disease," that are derived largely from curated public data sources. We successfully posed queries to TranQL that traversed these endpoints and retrieved answers that we visualized and evaluated.
conclusionsTranQL can be used to ask questions of relevance to translational science, rapidly obtain answers that require assertions from a federation of knowledge sources, and provide valuable insights for translational research and clinical practice.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.