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Special Issue on Cyberinfrastructure, Machine Learning, and Digital Library

between machine learning, cyberinfrastructure and digital library is an important step to achieve smart data and information management. However, there is lack of mediums and forums that bring together researchers and practitioners to share visions, questions, latest advances in methodology, application experiences, and best practices. Library and archival professionals are often unfamiliar with cyberinfrastructure. In turn, cyberinfrastructure experts lack experience in traditional digital library and archives practices such as metadata, provenance, publishing

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Identifier Services: Modeling and Implementing Distributed Data Management in Cyberinfrastructure

functions create a representation of a dataset’s provenance and evolution. IDS can be used by researchers to track data stored at multiple locations, and vice versa, by repositories and data stores to continue tracking the evolution of the datasets. This paper is organized as follows. In the Related Work section, we discuss authenticity as the conceptual framework for IDS, and review how different repository and data management projects support identity functions and implement data models. Along with each point, we clarify the novel contributions brought by IDS. In the

Open access