In recent years,implementations enabling Distributed Analytics(DA)have gained considerable attention due to their ability to perform complex analysis tasks on decentralised data by bringing the analysis to the data.Th...In recent years,implementations enabling Distributed Analytics(DA)have gained considerable attention due to their ability to perform complex analysis tasks on decentralised data by bringing the analysis to the data.These concepts propose privacy-enhancing alternatives to data centralisation approaches,which have restricted applicability in case of sensitive data due to ethical,legal or social aspects.Nevertheless,the immanent problem of DA-enabling architectures is the black-box-alike behaviour of the highly distributed components originating from the lack of semantically enriched descriptions,particularly the absence of basic metadata for data sets or analysis tasks.To approach the mentioned problems,we propose a metadata schema for DA infrastructures,which provides a vocabulary to enrich the involved entities with descriptive semantics.We initially perform a requirement analysis with domain experts to reveal necessary metadata items,which represents the foundation of our schema.Afterwards,we transform the obtained domain expert knowledge into user stories and derive the most significant semantic content.In the final step,we enable machine-readability via RDF(S)and SHACL serialisations.We deploy our schema in a proof-of-concept monitoring dashboard to validate its contribution to the transparency of DA architectures.Additionally,we evaluate the schema’s compliance with the FAIR principles.The evaluation shows that the schema succeeds in increasing transparency while being compliant with most of the FAIR principles.Because a common metadata model is critical for enhancing the compatibility between multiple DA infrastructures,our work lowers data access and analysis barriers.It represents an initial and infrastructure-independent foundation for the FAIRification of DA and the underlying scientific data management.展开更多
Enterprise application integration （EAI） focuses on the collaboration and interconnection of various information systems, so the basic problem to be solved is how EAI guarantees that the applications will produce co...Enterprise application integration （EAI） focuses on the collaboration and interconnection of various information systems, so the basic problem to be solved is how EAI guarantees that the applications will produce consistent presentation of data, message and transaction. The metadata methodology may give us certain good ideas. First, the metadata description method of manufacturing information resource, transaction process and message delivery is put forward on the basis of operation analysis of manufacturing-oriented EAI, and then the tree-structured XML schema of corresponding object is built and a framework of metadata application in the discrete Manufacturing-Oriented EAI is established. Finally, a practical enterprise information integration system in Shanghai Tobacco Machine Co., Ltd. is presented as an example to show how it functions.展开更多
基金this work was supported by the German Ministry for Research and Education(BMBF)as part of the SMITH consortium(SW,LN,YUY,SD and OB,grant no.01ZZ1803K)
文摘In recent years,implementations enabling Distributed Analytics(DA)have gained considerable attention due to their ability to perform complex analysis tasks on decentralised data by bringing the analysis to the data.These concepts propose privacy-enhancing alternatives to data centralisation approaches,which have restricted applicability in case of sensitive data due to ethical,legal or social aspects.Nevertheless,the immanent problem of DA-enabling architectures is the black-box-alike behaviour of the highly distributed components originating from the lack of semantically enriched descriptions,particularly the absence of basic metadata for data sets or analysis tasks.To approach the mentioned problems,we propose a metadata schema for DA infrastructures,which provides a vocabulary to enrich the involved entities with descriptive semantics.We initially perform a requirement analysis with domain experts to reveal necessary metadata items,which represents the foundation of our schema.Afterwards,we transform the obtained domain expert knowledge into user stories and derive the most significant semantic content.In the final step,we enable machine-readability via RDF(S)and SHACL serialisations.We deploy our schema in a proof-of-concept monitoring dashboard to validate its contribution to the transparency of DA architectures.Additionally,we evaluate the schema’s compliance with the FAIR principles.The evaluation shows that the schema succeeds in increasing transparency while being compliant with most of the FAIR principles.Because a common metadata model is critical for enhancing the compatibility between multiple DA infrastructures,our work lowers data access and analysis barriers.It represents an initial and infrastructure-independent foundation for the FAIRification of DA and the underlying scientific data management.
文摘Enterprise application integration （EAI） focuses on the collaboration and interconnection of various information systems, so the basic problem to be solved is how EAI guarantees that the applications will produce consistent presentation of data, message and transaction. The metadata methodology may give us certain good ideas. First, the metadata description method of manufacturing information resource, transaction process and message delivery is put forward on the basis of operation analysis of manufacturing-oriented EAI, and then the tree-structured XML schema of corresponding object is built and a framework of metadata application in the discrete Manufacturing-Oriented EAI is established. Finally, a practical enterprise information integration system in Shanghai Tobacco Machine Co., Ltd. is presented as an example to show how it functions.
