Functional Requirements for Information Resource Provenance on the Web

Printer-friendly version


HTTP transactions have semantics that can be interpreted in many ways. At a low level, a physical stream of bits is transmitted from server to client. Higher up, those bits resolve into a message with a specific bit pattern. More abstractly, information, regardless of the physical representation, has been transferred. While the mechanisms as- sociated with these abstractions, such as content negotiation, are well established, the semantics behind these abstractions are not. We extend the library science resource model Functional Requirements for Bibli- ographic Resources (FRBR) with cryptographic message and content digests to create a Functional Requirements for Information Resources (FRIR) ontology that is integrated with the W3C Provenance Ontology (PROV-O) to model HTTP transactions in a way that clarifies the many relationships between a given URL and all representations received from its request. Use of this model provides fine-grained provenance explana- tions that are complementary to existing explanations of web resources. Furthermore, we provide a formal explanation of the relationship between HTTP URLs and their representations that conforms with the existing World Wide Web architecture. This establishes the semiotic relationships between different information abstractions, their symbols, and the things they represent.


DateCreated ByLink
February 12, 2013
James McCuskerDownload
February 12, 2013
James McCuskerDownload

Related Projects:

Inference Web Project LogoInference Web
Principal Investigator: Deborah L. McGuinness
Description: The Inference Web is a Semantic Web based knowledge provenance infrastructure that supports interoperable explanations of sources, assumptions, learned information, and answers as an enabler for trust. Provenance - if users (humans and agents) are to use and integrate data from unknown, uncertain, or multiple sources, they need provenance metadata for evaluation Interoperability - more systems are using varied sources and multiple information manipulation engines, thus increasing interoperability requirements Explanation/Justification - if information has been manipulated (i.e., by sound deduction or by heuristic processes), information manipulation trace information should be available Trust - if some sources are more trustworthy than others, trust ratings are desired The Inference Web consists of two important components: Proof Markup Language (PML) Ontology - Semantic Web based representation for exchanging explanations including provenance information - annotating the sources of knowledge justification information - annotating the steps for deriving the conclusions or executing workflows trust information - annotating trustworthiness assertions about knowledge and sources IW Toolkit - Web-based and standalone tools that facilitate human users to browse, debug, explain, and abstract the knowledge encoded in PML.
DCO-DS LogoLinking Open Government Data (LOGD)
Principal Investigator: Deborah L. McGuinness and Jim Hendler
Description: The LOGD project investigates the role of Semantic Web technologies, especially Linked Data, in producing, enhancing and utilizing government data published on and other websites.

Related Research Areas:

Knowledge Provenance
Lead Professor: Deborah L. McGuinness
Description: Knowledge Provenance
Concepts: Provenance,