The Harvard Faculty Finder (HFF) website creates an institution-wide view of the breadth and depth of Harvard faculty and scholarship, and it helps students, faculty, administrators, and the general public locate Harvard faculty according to research and teaching expertise. More information about the HFF website and the data it contains can be found on the Harvard University Faculty Development & Diversity website. HFF is a Semantic Web application, which means its content can be read and understood by other computer programs. This enables the data associated with a person, such as titles, contact information, and publications to be shared with other institutions and appear on other websites. Below are the technical details for building a computer program that can export data from HFF.
As a Semantic Web application, HFF uses the Resource Description Framework (RDF) data model. In RDF, every entity (e.g., person, publication, concept) is given a unique URI. (A URI is similar to a URL that you would enter into a web browser.) Entities are linked together using "triples" that contain three URIs--a subject, predicate, and object. For example, the URI of a Person can be connected to the URI of a Concept through a predicate URI of hasResearchArea. HFF contains millions of URIs and triples. Semantic Web applications use an ontology, which describes the classes and properties used to define entities and link them together. HFF uses the VIVO Ontology, which was developed as part of an NIH-funded grant to be a standard for academic and research institutions. A growing number of sites around the world are adopting research networking platforms that use the VIVO Ontology. Because RDF can link different triple-stores that use the same ontology, software developers are able to create tools that span multiple institutions and data sources. When RDF data is shared with the public, as it is in HFF, it is called Linked Open Data (LOD).
There are four types of application programming interfaces (APIs) in HFF.
HFF is based on the open source Profiles Research Networking Software (RNS) platform. Below are links to the API documentation files for Profiles RNS. Make sure you use the API URLs listed in the above section rather than the defaults listed in the documentation.
HFF contains 2,636,517 RDF nodes and 11,570,908 triples. Though, these numbers are continually increasing as we import new data sources into HFF and faculty edit their pages. Below are counts for selected classes in HFF.
|Class Name||Class URI||Items|
|Web of Science Article||http://profiles.catalyst.harvard.edu/ontology/prns#WebOfScienceArticle||244,505|