An Identity Crisis in the Life Sciences

Zhao, Jun; Goble, Carole; Stevens, Robert

doi:10.1007/11890850_26

Cited by 16 publications

(20 citation statements)

References 16 publications

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“…Previous work has shown ProQA supports aggregating the multi-and mega-graphs [4]. The following shows ProQA supports presenting an abstraction over Ouzo, and reasoning about the knowledge provenance (either internally specified or gathered from external sources).…”

Section: Mining Ouzo With Proqamentioning

confidence: 94%

“…This identity is also used to store the RDF provenance metadata of this data product in the metadata store, KAVE [6]. If the data product is gathered from external sources, its external identity is kept along with its Taverna LSID in KAVE [4].…”

Section: Collecting the Challenge Provenancementioning

confidence: 99%

“…This volatility causes repetitive experiment effort. Scientists need to repeat their workflows in case an updated data product could be gathered or computed [4]. Varying the settings of repeated runs might lead to completely different or completely identical outcomes.…”

Section: Linking Together the Multi-and Mega-graphs Collected In Diffmentioning

confidence: 99%

“…The previous work [4] has analysed and showed how we managed to achieve the graph aggregation by reconciliating the polyonymous identities given to the same data product that appears in the multi-graphs. …”

Section: Linking Together the Multi-and Mega-graphs Collected In Diffmentioning

confidence: 99%

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Mining Taverna's semantic web of provenance

Zhao

Goble

Stevens

et al. 2007

Concurrency and Computation

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SUMMARYTaverna is a workflow workbench developed as part of the UK's my Grid project. Taverna's provenance model captures both internal provenance locally generated in Taverna and external provenance gathered from third-party data providers. This model also supports overlaying secondary provenance over the primary logs and lineage. This design is motivated by the particular properties of bioinformatics data and services used in Taverna. A Semantic Web of provenance, Ouzo, is built to combine the above different provenance by means of semantic annotations. This paper shows how Ouzo can be mined by a provenance usage component, Provenance Query and Answer (ProQA). ProQA supports provenance retrievals as well as provenance abstraction, aggregation, and semantic reasoning. ProQA is implemented as a suite APIs which can be deployed as provenance services to compose system provenance workflows that analyse experiment results using the provenance records. We show how these features of Taverna's provenance support us in answering the questions from the provenance challenge workshop and a set of additional provenance queries.

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Section: Mining Ouzo With Proqamentioning

confidence: 94%

Section: Collecting the Challenge Provenancementioning

confidence: 99%

Section: Linking Together the Multi-and Mega-graphs Collected In Diffmentioning

confidence: 99%

Section: Linking Together the Multi-and Mega-graphs Collected In Diffmentioning

confidence: 99%

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Mining Taverna's semantic web of provenance

Zhao

Goble

Stevens

et al. 2007

Concurrency and Computation

Self Cite

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“…Today, human activity is becoming increasingly automated with the aid of computational systems, which perform part or, in some cases, all of processes previously undertaken solely by humans. Interestingly, this means that activities in scientific [2], governmental [4] and commercial [12] settings are increasingly represented in computational systems, which presents an opportunity: it becomes possible to capture what happens in these settings both accurately and comprehensively.…”

Section: Motivationmentioning

confidence: 99%

Principles of High Quality Documentation for Provenance: A Philosophical Discussion

Groth

Miles

Munroe

2006

Provenance and Annotation of Data

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Abstract.Computer technology enables the creation of detailed documentation about the processes that create or affect entities (data, objects, etc.). Such documentation of the past can be used to answer various kinds of questions regarding the processes that led to the creation or modification of a particular entity. The answer to such questions are known as an entity's provenance. In this paper, we derive a number of principles for documenting the past, grounded in work from philosophy and history, which allow for provenance questions to be answered within a computational context. These principles lead us to argue that an interaction-based model is particularly suited for representing high quality documentation of the past.History is important: in order to make progress in the future, it is important to learn the lessons of the past. History, therefore, becomes a vital resource for progressive societies. History is based on evidence or documentation of events that occurred in the past. Computer technology enables documentation to be produced that is more accurate and comprehensive than previously possible. Given the quantity of documentation that can be generated by computer systems (for example those running e-Science applications), what kind of documentation should be created that enables historians and users to most effectively answer questions they have about the past. To answer these questions, we argue for two principles for the creation of, what we term, high quality documentation of the past. One principle guarantees that users of documentation of the past have a precise semantics for it. The other principle guarantees that there exists a link between documentation and its creators. Together these principles are the first contribution of this paper.A question that is often posed by historians and users regards the provenance of an entity (object, data item, etc..): what was the process that led to the entity in question? To enable the answering of provenance questions in a manner that conforms with the aforementioned principles, we introduce a model of documentation based on the exchange of messages between actors. The justification of this model is the second contribution of this paper.The rest of this paper is organised as follows. We begin with a more detailed motivation of our work. After which, three assumptions about the world are

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