Using Schema Transformation Pathways for Data Lineage Tracing

Fan, Hao; Poulovassilis, Alexandra

doi:10.1007/11511854_11

Cited by 9 publications

(3 citation statements)

References 12 publications

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“…In [4], we present a DLT approach which is to use the individual steps of these pathways to compute the lineage data of the tracing data by traversing the pathways in reverse order one step at a time. In particular, suppose a data source LD with schema LS is transformed into a global database GD with schema GS, and the transformation pathway LS → GS is ts 1 , ..., ts n .…”

Section: ) Tracing Data Lineagementioning

confidence: 99%

Study on Proteomics Data Integration in Web Environments

Fan

Liu

2008

2008 2nd International Conference on Bioinformatics and Biomedical Engineering

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In web environments, proteomics data integration in the life sciences needs to handle the problem of data conflicts arising from the heterogeneity of data resources and from incompatibilities between the inputs and outputs of services used in the analysis of the resources. This paper presents an approach addressing the data conflict problems of proteomics data integration. We describe a proposed proteomics data integration architecture, in which a heterogeneous data integration system interoperates with Web Services and query processing tools for the virtual and materialised integration of a number of proteomics resources, either locally or remotely. Finally, we discuss how the architecture can be further used for supporting data maintenance and analysis activities.

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Section: ) Tracing Data Lineagementioning

confidence: 99%

Study on Proteomics Data Integration in Web Environments

Fan

Liu

2008

2008 2nd International Conference on Bioinformatics and Biomedical Engineering

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“…In [5], we present a DLT approach which is to use the individual steps of these pathways to compute the lineage data of the tracing data by traversing the pathways in reverse order one step at a time. In particular, suppose a data source LD with schema LS is transformed into a global database GD with schema GS, and the transformation pathway LS → GS is ts 1 ,…, ts n .…”

Section: ) Tracing Data Lineagementioning

confidence: 99%

Using schema transforation pathways for biological data integration

Fan¹,

Wang

2008

JBiSE

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In web environments, proteomics data integrationin the life sciences needs to handle the problem of data conflicts arising from the heterogeneity of data resources and from incompatibilities between the inputs and outputs of services used in the analysis of the resources. The integration of complex, fast changing biological data repositories can be potentially supported by Grid computing to enable distributed data analysis. This paper presents an approach addressing the data conflict problems of proteomics data integration. We describe a proposed proteomics data integration architecture, in which a heterogeneous data integration system interoperates with Web Services and query processing tools for the virtual and materialised integration of a number of proteomics resources, either locally or remotely. Finally, we discuss how the architecture can be further used for supporting data maintenance and analysis activities.

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“…A number of studies have been conducted in the database community on data lineage or provenance [17,18,19]. Data Lineage concerns tracing how the data aggregated into a data warehouse has been derived from the data sources.…”

Section: Related Workmentioning

confidence: 99%

A Labelling System for Derived Data Control

Scalavino

Gowadia

Lupu

2010

Lecture Notes in Computer Science

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Abstract. Existing ERM/DRM systems and more generally usage control systems aim to control who accesses data and the usage data is subject to even after the data has been disseminated to recipients. However, once the data has been used, no control or protection is applied to the information created as result of the usage. We propose a solution to derive protection requirements for derived data that makes use of Multi-Level Security (MLS) labels to associate data with its protection level and usage functions (transformations) with the protection requirements of the data they can derive. Users are also associated with clearance labels according to their roles. Clearance and data labels are used to determine whether a user can access data as in traditional Mandatory Access Control systems, while labels associated with transformations are used to derive labels for derived data. The solution assumes that the amount of sensitive information flowing from the input to the output of a transformation can be deduced from the input data and the transformation itself, so that adequate protection can be associated with the derived output.

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Using Schema Transformation Pathways for Data Lineage Tracing

Cited by 9 publications

References 12 publications

Study on Proteomics Data Integration in Web Environments

Study on Proteomics Data Integration in Web Environments

Using schema transforation pathways for biological data integration

A Labelling System for Derived Data Control

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