A pragmatic approach to XML interoperability – the Component Metadata Infrastructure (CMDI)

Broeder, Daan; Schonefeld, Oliver; Trippel, Thorsten; Uytvanck, Dieter Van; Witt, Andreas

doi:10.4242/balisagevol7.broeder01

Cited by 16 publications

(15 citation statements)

References 3 publications

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“…A CMDI component brackets elementary data descriptors or other, simpler components into a single unit. We obtain, thus, a hierarchical metadata system (Broeder et al 2011). Figure 6.1 shows a profile that can be used to describe text corpora.…”

Section: Component Metadata Infrastructure (Cmdi)mentioning

confidence: 99%

Development of Linguistic Linked Open Data Resources for Collaborative Data-Intensive Research in the Language Sciences

2020

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We thank William J. Badecker, NSF Linguistics Program director, whose advice has been invaluable during all stages of this project, and Marc Lowenthal and Anthony Zannino at MIT Press, who guided us to publication. We thank Amy Brand, director of MIT Press, whose pursuit of the development of scholarly communication in the digital age provided support for our project. The Cornell University Library, through Oya Rieger, provided continual advice and support, as well as a critical dimension of library-researcher relations, continuing the early vision of previous Mann Library director, Janet McCue. Emily Bernardski provided key support and coordination for the workshop, as did Carissa Kang and Jonathan Masci, our student support team. Our editors Michelle Melanson and Rebecca Rich Goldweber provided invaluable assistance in volume publication. James Gair provided continual support throughout.

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Section: Component Metadata Infrastructure (Cmdi)mentioning

confidence: 99%

Development of Linguistic Linked Open Data Resources for Collaborative Data-Intensive Research in the Language Sciences

2020

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“…Finally, considering the information provenance and the development of research infrastructures that gather and integrate heterogeneous datasets, a mapping between the CLARIN's (European Research Infrastructure for Language Resources and Technology) underlying metadata model (CMDI-Component Metadata Infrastructure) [41] and the CRMpe extension of the CIDOC CRM, developed during the PARTHENOS Project [14], has been proposed in [42] and is currently under development. CMDI is not just one schema, but a framework for creating and reusing self-defined metadata schemas in order to meet the various needs of data providers.…”

Section: Merging and Mapping Approachesmentioning

confidence: 99%

Semantic Bridging of Cultural Heritage Disciplines and Tasks

et al. 2019

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The Cultural Heritage (CH) domain encompasses a wide range of different disciplines, serving the study, interpretation, curation, and preservation of objects, collections, archives, sites, and the dissemination of related knowledge. In this context, stakeholders generate, retrieve, and share a vast amount of diverse information. Therefore, information interoperability has been considered a crucial task, especially in terms of semantics. In this way, the CIDOC CRM (International Committee for Documentation Conceptual Reference Model) has been widely used as an underlying model that offers interoperability between CH domain metadata standards and ontologies. To the best of our knowledge, an overall review of mapping, merging, and extending this core ontology, as well as an aggregate table which classifies and correlates those ontologies and standards, has not yet been presented. Our study conducts an aggregate review of relevant published efforts and outlines the various associations between them, encapsulating the CIDOC CRM and its specialized models, as well. This work aims to further clarify the field and scope of the different works, identify their methods, and highlight the semantic overlap, or differences, between them.

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“…title. Alternatively, a component can recursively contain other components [4]. The benefits of this approach are reusability and extensibility as well as providing guidelines for data structuring.…”

Section: This Research Was Funded By Science Foundation Ireland Awardmentioning

confidence: 99%

A Method for Automated Transformation and Validation of Online Datasets

McCarthy

McCarren

Roantree

2019

2019 IEEE 23rd International Enterprise Distributed Object Computing Conference (EDOC)

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While using online datasets for machine learning is commonplace today, the quality of these datasets impacts on the performance of prediction algorithms. One method for improving the semantics of new data sources is to map these sources to a common data model or ontology. While semantic and structural heterogeneities must still be resolved, this provides a well established approach to providing clean datasets, suitable for machine learning and analysis. However, when there is a requirement for a close to real time usage of online data, a method for dynamic Extract-Transform-Load of new sources data must be developed. In this work, we present a framework for integrating online and enterprise data sources, in close to real time, to provide datasets for machine learning and predictive algorithms. An exhaustive evaluation compares a human built data transformation process with our system's machine generated ETL process, with very favourable results, illustrating the value and impact of an automated approach.

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A pragmatic approach to XML interoperability – the Component Metadata Infrastructure (CMDI)

Cited by 16 publications

References 3 publications

Development of Linguistic Linked Open Data Resources for Collaborative Data-Intensive Research in the Language Sciences

Development of Linguistic Linked Open Data Resources for Collaborative Data-Intensive Research in the Language Sciences

Semantic Bridging of Cultural Heritage Disciplines and Tasks

A Method for Automated Transformation and Validation of Online Datasets

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