Schema exchange: Generic mappings for transforming data and metadata

Papotti, Paolo; Torlone, Riccardo

doi:10.1016/j.datak.2009.02.005

Cited by 18 publications

(14 citation statements)

References 24 publications

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“…In particular, schema and instance matching techniques have been thoroughly investigated in the past (e.g., see refs. [34][35][36][37][38]. Some use advanced background knowledge to improve matching results, such as ontologies.…”

Section: Comparison With Related Researchmentioning

confidence: 99%

Pan-European Data Harmonization for Biobanks in ADOPT BBMRI-ERIC

et al. 2019

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Background High-quality clinical data and biological specimens are key for medical research and personalized medicine. The Biobanking and Biomolecular Resources Research Infrastructure-European Research Infrastructure Consortium (BBMRI-ERIC) aims to facilitate access to such biological resources. The accompanying ADOPT BBMRI-ERIC project kick-started BBMRI-ERIC by collecting colorectal cancer data from European biobanks. Objectives To transform these data into a common representation, a uniform approach for data integration and harmonization had to be developed. This article describes the design and the implementation of a toolset for this task. Methods Based on the semantics of a metadata repository, we developed a lexical bag-of-words matcher, capable of semiautomatically mapping local biobank terms to the central ADOPT BBMRI-ERIC terminology. Its algorithm supports fuzzy matching, utilization of synonyms, and sentiment tagging. To process the anonymized instance data based on these mappings, we also developed a data transformation application. Results The implementation was used to process the data from 10 European biobanks. The lexical matcher automatically and correctly mapped 78.48% of the 1,492 local biobank terms, and human experts were able to complete the remaining mappings. We used the expert-curated mappings to successfully process 147,608 data records from 3,415 patients. Conclusion A generic harmonization approach was created and successfully used for cross-institutional data harmonization across 10 European biobanks. The software tools were made available as open source.

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Section: Comparison With Related Researchmentioning

confidence: 99%

Pan-European Data Harmonization for Biobanks in ADOPT BBMRI-ERIC

et al. 2019

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“…In this section we recall the notion of schema mapping [15] and introduce that of meta-mapping. While the former notion is used to model specific data trations, the latter introduces an abstraction over mappings [23,29] and allows us to model generic mappings between schemas. Building on these notions, we also clarify the goals of this paper.…”

Section: Background and Goalmentioning

confidence: 99%

Meta-mappings for schema mapping reuse

Atzeni

Bellomarini²,

Papotti

et al. 2019

Proc. VLDB Endow.

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The definition of mappings between heterogeneous schemas is a critical activity of any database application. Existing tools provide high level interfaces for the discovery of correspondences between elements of schemas, but schema mappings need to be manually specified every time from scratch, even if the scenario at hand is similar to one that has already been addressed. The problem is that schema mappings are precisely defined over a pair of schemas and cannot directly be reused on different scenarios. We tackle this challenge by generalizing schema mappings as meta-mappings: formalisms that describe transformations between generic data structures called meta-schemas. We formally characterize schema mapping reuse and explain how meta-mappings are able to: (i) capture enterprise knowledge from previously defined schema mappings and (ii) use this knowledge to suggest new mappings. We develop techniques to infer metamappings from existing mappings, to organize them into a searchable repository, and to leverage the repository to propose to users mappings suitable for their needs. We study effectiveness and efficiency in an extensive evaluation over real-world scenarios and show that our system can infer, store, and search millions of meta-mappings in seconds.

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“…The author of the third reference article pointed out that the data integration faced a main problem is the correct matching of data between heterogeneous data sources (4). Papotti, the author of the five reference article， proposed data migration is achieved through by the establishment of a universal model (5). P.Ziegler in the 2006 meeting article mentioned that the data integration project list had a total of 183 items which including had been finished project or are studying project (6).…”

Section: Introductionmentioning

confidence: 99%

A kind of bidirectional mapping strategy of heterogeneous data model based on metadata-driven

Huang

2012

Proceedings of 2012 2nd International Conference on Computer Science and Network Technology

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This paper focuses on the research of the mapping between heterogeneous data models. And using ETL framework as references, it designs a bidirectional mapping strategy combining heterogeneous data model data mapping, conversion and loading. It analyzes and defines the mapping relations and mapping rules among the data models. Based on the metadata driven theory method, it designs the data mapping element model, and classifies the mapping relations to simple mapping and compound mapping according to the different complexities, with clearly giving the classification principle. This article also describes the bidirectional mapping relations, and analyzes the problems occurring in the bidirectional mapping.

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Schema exchange: Generic mappings for transforming data and metadata

Cited by 18 publications

References 24 publications

Pan-European Data Harmonization for Biobanks in ADOPT BBMRI-ERIC

Pan-European Data Harmonization for Biobanks in ADOPT BBMRI-ERIC

Meta-mappings for schema mapping reuse

A kind of bidirectional mapping strategy of heterogeneous data model based on metadata-driven

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