This page provides pointers to the materials (vocabularies, dataset, software and queries) used in a paper currently under review (more details about the publication will be announced at a later stage)
Summary (extracted from the paper): This paper proposes a framework for automatically describing software images in a machine-readable manner by i) creating a vocabulary to describe software images; ii) developing an annotation framework designed to automatically document the underlying environment of software images and iii) creating DockerPedia, a Knowledge Graph with over 150,000 annotated software images, automatically described using our framework. We illustrate the usefulness of our approach in finding images with required software dependencies, comparing similar software images, addressing versioning problems when running computational experiments and flagging problems with vulnerable software dependencies.
Permanent URL of this page: https://w3id.org/dgarijo/ro/dockerpedia
Research Programmer
Computer Scientist at the Information Sciences Institute of the University of Southern California.
Lecturer
Lecturer at DSC department, at ULPGC on sensor data for light pollution and medical image processing. Idafen is also interested in topics related to Open Science and Linked Data in general.
Lecturer
Lecturer at the Universidad Técnica Federico de Santa María, In Chile. Carlos work focuses on (graph) databases, Semantic Web and Knowledge Graphs.
Researcher
Researcher at the Ontology Engineering Group of the Universidad Politécnica de Madrid. Daniel's research activities focus on e-Science and the Semantic web, specifically on how to increase the understandability of software and scientific workflows using provenance, metadata, intermediate results and Linked Data.
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