| Title |
PAV ontology: provenance, authoring and versioning
|
|---|---|
| Published in |
Journal of Biomedical Semantics, November 2013
|
| DOI | 10.1186/2041-1480-4-37 |
| Pubmed ID | |
| Authors | |
| Abstract |
Provenance is a critical ingredient for establishing trust of published scientific content. This is true whether we are considering a data set, a computational workflow, a peer-reviewed publication or a simple scientific claim with supportive evidence. Existing vocabularies such as Dublin Core Terms (DC Terms) and the W3C Provenance Ontology (PROV-O) are domain-independent and general-purpose and they allow and encourage for extensions to cover more specific needs. In particular, to track authoring and versioning information of web resources, PROV-O provides a basic methodology but not any specific classes and properties for identifying or distinguishing between the various roles assumed by agents manipulating digital artifacts, such as author, contributor and curator. |
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X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Russia | 1 | 17% |
| Netherlands | 1 | 17% |
| United Kingdom | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 50% |
| Scientists | 2 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 17% |
Mendeley demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 2 | 2% |
| United Kingdom | 2 | 2% |
| Spain | 2 | 2% |
| United States | 1 | <1% |
| Poland | 1 | <1% |
| Mexico | 1 | <1% |
| Japan | 1 | <1% |
| France | 1 | <1% |
| Germany | 1 | <1% |
| Other | 2 | 2% |
| Unknown | 88 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 23 | 23% |
| Student > Master | 16 | 16% |
| Student > Ph. D. Student | 15 | 15% |
| Student > Bachelor | 8 | 8% |
| Professor > Associate Professor | 6 | 6% |
| Other | 18 | 18% |
| Unknown | 16 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 47 | 46% |
| Agricultural and Biological Sciences | 15 | 15% |
| Social Sciences | 4 | 4% |
| Engineering | 4 | 4% |
| Business, Management and Accounting | 2 | 2% |
| Other | 9 | 9% |
| Unknown | 21 | 21% |