A provenance-based approach to manage long term preservation of scientific data

Sousa, Renato Beserra; Cugler, Daniel Cintra; Malaverri, Joana E. Gonzales; Medeiros, Cláudia Bauzer

doi:10.1109/icdew.2014.6818316

Cited by 8 publications

(13 citation statements)

References 21 publications

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“…The implementation uses a Model-View-Controller (MVC) architecture implemented using the PHP language and the Symfony Framework 3 , a well established framework for web development. Among some of the tools and ontologies reused and/or extended in our software architecture are: YesWorkflow [McPhillips et al 2015], Quality Flow [Sousa 2015, Sousa et al 2014] and the WRO model ontologies [Belhajjame et al 2015]. We also created an ontology for annotating data quality information (see section 2.3).…”

Section: Overviewmentioning

confidence: 99%

“…In [Carvalho et al 2016a], we state that there is a need to check the quality of the actual script-to-workflow conversion, and to assess the quality of the resulting workflow. In our solution, we adopt Quality Flow [Sousa et al 2014] to allow scientists to annotate the elements that make up the workflow with quality information. By doing this, scientists are able to compute quality metrics related to data, processes, and overall execution, and request evaluation of specific quality metrics based on combining quality dimensions with provenance information generated at each run of the workflow.…”

Section: Quality Flowmentioning

confidence: 99%

“…The prototype is available at http://w3id.org/w2share. It incorporates our work on Quality Flow, [Sousa 2015, Sousa et al 2014] -a workflowbased computational framework for data quality assessment of scientific experiments. Our solution can be used in different situations such as: (i) publishing procedures and datasets related to an experiment; (ii) training members in a research group to gain skills in computational scientific procedures; and (iii) dynamically assessing the quality of experiments.…”

Section: Introductionmentioning

confidence: 99%

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Implementing W2Share: Supporting Reproducibility and Quality Assessment in eScience

Carvalho¹,

Malaverri²,

Medeiros³

2017

Anais Do XI Brazilian E-Science Workshop (BRESCI 2017)

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An open problem in scientific community is that of supporting reproducibility and quality assessment of scientific experiments. Solutions need to be able to help scientists to reproduce experimental procedures in a reliable manner and, at the same time, to provide mechanisms for documenting the experiments to enhance integrity and transparency. Moreover, solutions need to incorporate features that allow the assessment of procedures, data used and results of those experiments. In this context, we designed W2Share, a framework to meet these requirements. This paper introduces our first implementation of W2Share, which moreover guides scientists in step-by-step process to ensure reproducibility based on a script-to-workflow conversion strategy. W2Share also incorporates features that allow annotating experiments with quality information. We validate our prototype using a real-world scenario in Bioinformatics.

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Section: Overviewmentioning

confidence: 99%

Section: Quality Flowmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Implementing W2Share: Supporting Reproducibility and Quality Assessment in eScience

Carvalho¹,

Malaverri²,

Medeiros³

2017

Anais Do XI Brazilian E-Science Workshop (BRESCI 2017)

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“…Beserra et al [8] propose a provenance-based approach to manage long term preservation of scientific data. This approach uses a case study related to the long term preservation of the animal sound collection at the Fonoteca Neotropical Jacques Vielliard (FNJV) 8 .…”

Section: Related Workmentioning

confidence: 99%

“…This approach uses a case study related to the long term preservation of the animal sound collection at the Fonoteca Neotropical Jacques Vielliard (FNJV) 8 . Their approach is based on the Open Provenance Model (OPM) [9].…”

Section: Related Workmentioning

confidence: 99%

A Model of Provenance Applied to Biodiversity Datasets

Amanqui

Nies

Dimou

et al. 2016

2016 IEEE 25th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)

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Abstract-Nowadays, the Web has become one of the main sources of biodiversity information. An increasing number of biodiversity research institutions add new specimens and their related information to their biological collections and make this information available on the Web. However, mechanisms which are currently available provide insufficient provenance of biodiversity information. In this paper, we propose a new biodiversity provenance model extending the W3C PROV Data Model. Biodiversity data is mapped to terms from relevant ontologies, such as Dublin Core and GeoSPARQL, stored in triple stores and queried using SPARQL endpoints. Additionally, we provide a use case using our provenance model to enrich collection data.

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