Institute for Data Intensive Engineering and Science, Johns Hopkins University
E354129
The Institute for Data Intensive Engineering and Science at Johns Hopkins University is a research center focused on advancing data-driven discovery and computational methods across science and engineering disciplines.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Institute for Data Intensive Engineering and Science, Johns Hopkins University canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T3372168 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Institute for Data Intensive Engineering and Science, Johns Hopkins University Context triple: [Charles Meneveau, affiliation, Institute for Data Intensive Engineering and Science, Johns Hopkins University]
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A.
MIT Institute for Data, Systems, and Society
The MIT Institute for Data, Systems, and Society is an interdisciplinary research and education institute at the Massachusetts Institute of Technology focused on data science, systems engineering, and social science to address complex societal challenges.
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B.
Berkeley Institute for Data Science
The Berkeley Institute for Data Science is an interdisciplinary research and education center at UC Berkeley that advances data-intensive discovery across the sciences, engineering, and the humanities.
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C.
Institute for Software Research, Carnegie Mellon University
The Institute for Software Research at Carnegie Mellon University is a leading academic center focused on research and education in software engineering, cybersecurity, privacy, and socio-technical systems.
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D.
Computation Institute
The Computation Institute is a research organization focused on advancing computational science and high-performance computing to support interdisciplinary scientific and engineering research.
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E.
Institute for Systems Research
The Institute for Systems Research is an interdisciplinary research center at the University of Maryland focused on advancing systems engineering, control, communications, and related technologies.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Institute for Data Intensive Engineering and Science, Johns Hopkins University Target entity description: The Institute for Data Intensive Engineering and Science at Johns Hopkins University is a research center focused on advancing data-driven discovery and computational methods across science and engineering disciplines.
-
A.
MIT Institute for Data, Systems, and Society
The MIT Institute for Data, Systems, and Society is an interdisciplinary research and education institute at the Massachusetts Institute of Technology focused on data science, systems engineering, and social science to address complex societal challenges.
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B.
Berkeley Institute for Data Science
The Berkeley Institute for Data Science is an interdisciplinary research and education center at UC Berkeley that advances data-intensive discovery across the sciences, engineering, and the humanities.
-
C.
Institute for Software Research, Carnegie Mellon University
The Institute for Software Research at Carnegie Mellon University is a leading academic center focused on research and education in software engineering, cybersecurity, privacy, and socio-technical systems.
-
D.
Computation Institute
The Computation Institute is a research organization focused on advancing computational science and high-performance computing to support interdisciplinary scientific and engineering research.
-
E.
Institute for Systems Research
The Institute for Systems Research is an interdisciplinary research center at the University of Maryland focused on advancing systems engineering, control, communications, and related technologies.
- F. None of above. chosen
Statements (42)
| Predicate | Object |
|---|---|
| instanceOf |
academic unit
ⓘ
research center ⓘ research institute ⓘ |
| affiliatedWith |
Johns Hopkins University Applied Physics Laboratory
ⓘ
surface form:
Applied Physics Laboratory, Johns Hopkins University
Krieger School of Arts and Sciences ⓘ
surface form:
Krieger School of Arts and Sciences, Johns Hopkins University
Whiting School of Engineering ⓘ
surface form:
Whiting School of Engineering, Johns Hopkins University
|
| country |
United States of America
ⓘ
surface form:
United States
|
| discipline |
applied mathematics
ⓘ
computer science ⓘ data science ⓘ engineering ⓘ statistics ⓘ |
| focusesOn |
big data analytics
ⓘ
computational methods ⓘ data science applications in astronomy ⓘ data science applications in astrophysics ⓘ data science applications in biomedical engineering ⓘ data science applications in earth sciences ⓘ data science applications in engineering ⓘ data science applications in physical sciences ⓘ data-driven discovery ⓘ data-intensive science ⓘ scientific computing ⓘ |
| hasResearchArea |
computational astrophysics
ⓘ
computational earth and environmental science ⓘ computational medicine ⓘ data visualization ⓘ data-intensive engineering ⓘ large-scale data management ⓘ machine learning for scientific discovery ⓘ |
| language | English ⓘ |
| locatedIn |
Baltimore, Maryland, United States
ⓘ
surface form:
Baltimore, Maryland
|
| mission |
advance data-driven discovery across science and engineering
ⓘ
develop computational methods for large-scale scientific data ⓘ enable cross-disciplinary collaboration in data-intensive research ⓘ |
| operatedBy | Johns Hopkins University ⓘ |
| partOf | Johns Hopkins University ⓘ |
| sector | higher education ⓘ |
| supports |
collaborative research projects
ⓘ
computational infrastructure for research ⓘ high-performance computing for science ⓘ interdisciplinary research ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Institute for Data Intensive Engineering and Science, Johns Hopkins University Description of subject: The Institute for Data Intensive Engineering and Science at Johns Hopkins University is a research center focused on advancing data-driven discovery and computational methods across science and engineering disciplines.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.
Charles Meneveau
→
affiliation
→
Institute for Data Intensive Engineering and Science, Johns Hopkins University
ⓘ