This subproject is one of many research subprojects utilizing theresources provided by a Center grant funded by NIH/NCRR. The subproject andinvestigator (PI) may have received primary funding from another NIH source,and thus could be represented in other CRISP entries. The institution listed isfor the Center, which is not necessarily the institution for the investigator.Provenance, which refers to the origin or source of an object or concept, is an important aspect of any data obtained as a result of high-throughput analysis. Provenance information can include the history of both the sample (e.g., the biological source, chemical modification, and isolation method) and the data obtained from the sample (e.g., acquisition method, digital format, processing parameters and processing algorithms). Provenance thus constitutes the fundamental information that enables scientists to repeat experiments and justifies the comparison of different datasets. However, syntactic data provenance (i.e., merely listing this information without reference to commonly accepted concepts) is often inadequate, as it can lead to ambiguous conclusions. To solve these challenges we are developing a semantic Universal Resource Identifier (SemURI) scheme. The current version is implemented as an integral part of the ProPreO ontology, but could be incorporated into any ontology. By semantic URI we mean an URI that lexically incorporates semantic description by succinctly representing a chronologically ordered list of concepts that are part of ProPreO. These concepts include both (physical and computational) tasks and the (physical and digital) objects that these tasks use and generate. Thus, each task or object class is assigned a general SemURI, which is incorporated into the specific SemURI that identifies a specific instance of that task or object. Thus, the SemURI constitutes a very succinct representation of the entire provenance of an object, including all of the tasks and intermediate objects in its history.
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