Five ways RO-Crate data packages are important for repositories

Research Object Crate is a linked data metadata packaging standard which has been widely adopted in research contexts. In this presentation we will briefly explain what RO-Crate is, how it is being adopted worldwide, then go on to list ways that RO-Crate is growing in importance in the repository world:1. Uploading of complex multi-file objects means RO-Crate is compatible with any general purpose repository that can accept a zip file (with some coding, repository services can do more with RO-Crates).2. Download for well-described data objects complete with metadata from a repository rather than just a zip or file with no metadata3. Using RO-Crate metadata reduces the amount of customisation that is required in repository software, as ALL the metadata is described using the same simple, self-documenting linked-data structures, so generic display templates4. Sufficiently well-described RO-Crates can be used to make data FAIR compliant, aiding in Findability, Accessibility, Interoperability and Reusability thanks to standardised metadata and mature tooling5. And if you’re looking for a sustainable repository solution, there are tools which can run a repository from a set of static files on a storage service, in line with the ideas put forward by Suleman in the closing keynote for OR2023<br/

The Archive and Package (arcp) URI scheme

The arcp URI scheme is introduced for location-independent identifiers to consume or reference hypermedia and linked data resources bundled inside a file archive, as well as to resolve archived resources within programmatic frameworks for Research Objects. Research Object: http://s11.no/2018/arcp.html#ro Cite as: Stian Soiland-Reyes, Marcos Cáceres (2018): The Archive and Package (arcp) URI Scheme. 2018 IEEE 14th International Conference on e-Science (e-Science). https://doi.org/10.1109/eScience.2018.00018Author-prepared preprint. Web version: http://s11.no/2018/arcp.html Publisher version: https://doi.org/10.1109/eScience.2018.0001

Evaluating FAIR Digital Object and Linked Data as distributed object systems

FAIR Digital Object (FDO) is an emerging concept that is highlighted by European Open Science Cloud (EOSC) as a potential candidate for building a ecosystem of machine-actionable research outputs. In this work we systematically evaluate FDO and its implementations as a global distributed object system, by using five different conceptual frameworks that cover interoperability, middleware, FAIR principles, EOSC requirements and FDO guidelines themself. We compare the FDO approach with established Linked Data practices and the existing Web architecture, and provide a brief history of the Semantic Web while discussing why these technologies may have been difficult to adopt for FDO purposes. We conclude with recommendations for both Linked Data and FDO communities to further their adaptation and alignment.Comment: 40 pages, submitted to PeerJ C

Tracking workflow execution with TavernaProv

Apache Taverna is a scientific workflow system for combining web services and local tools. Taverna records provenance of workflow runs, intermediate values and user interactions, both as an aid for debugging while designing the workflow, but also as a record for later reproducibility and comparison. Taverna also records provenance of the evolution of the workflow definition (including a chain of wasDerivedFrom relations), attributions and annotations; for brevity we here focus on how Taverna's workflow run provenance extends PROV and is embedded with Research Objects.Document id: https://github.com/stain/2016-provweek-tavernaprov

ORE User Guide - Resource Map Implementation in JSON-LD 0.9

Open Archives Initiative Object Reuse and Exchange (OAI-ORE) defines standards for the description and exchange of aggregations of Web resources. OAI-ORE introduces the notion of a Resource Map, an RDF Graph which describes the Aggregation, the aggregated Resources of which it is composed, and the relationships between them (and/or the relationships between these and other resources). Since a Resource Map is an RDF Graph, it can be serialized using any RDF syntax. This document outlines the use of one such syntax for the serialization of Resource Maps: JSON-LD. This document is intended for implementers who have an understanding of ORE concepts and are responsible for the development of applications which generate or process Resource Maps using JSON-LD.This document is available at http://www.openarchives.org/ore/0.9/jsonl

PAV ontology: provenance, authoring and versioning

Provenance is a critical ingredient for establishing trust of published scientific content. This is true whether we are considering a data set, a computational workflow, a peer-reviewed publication or a simple scientific claim with supportive evidence. Existing vocabularies such as DC Terms and the W3C PROV-O are domain-independent and general-purpose and they allow and encourage for extensions to cover more specific needs. We identify the specific need for identifying or distinguishing between the various roles assumed by agents manipulating digital artifacts, such as author, contributor and curator. We present the Provenance, Authoring and Versioning ontology (PAV): a lightweight ontology for capturing just enough descriptions essential for tracking the provenance, authoring and versioning of web resources. We argue that such descriptions are essential for digital scientific content. PAV distinguishes between contributors, authors and curators of content and creators of representations in addition to the provenance of originating resources that have been accessed, transformed and consumed. We explore five projects (and communities) that have adopted PAV illustrating their usage through concrete examples. Moreover, we present mappings that show how PAV extends the PROV-O ontology to support broader interoperability. The authors strived to keep PAV lightweight and compact by including only those terms that have demonstrated to be pragmatically useful in existing applications, and by recommending terms from existing ontologies when plausible. We analyze and compare PAV with related approaches, namely Provenance Vocabulary, DC Terms and BIBFRAME. We identify similarities and analyze their differences with PAV, outlining strengths and weaknesses of our proposed model. We specify SKOS mappings that align PAV with DC Terms.Comment: 22 pages (incl 5 tables and 19 figures). Submitted to Journal of Biomedical Semantics 2013-04-26 (#1858276535979415). Revised article submitted 2013-08-30. Second revised article submitted 2013-10-06. Accepted 2013-10-07. Author proofs sent 2013-10-09 and 2013-10-16. Published 2013-11-22. Final version 2013-12-06. http://www.jbiomedsem.com/content/4/1/3