Amy Nurnberger

Key components of data publishing: using current best practices to develop a reference model for data publishing

The availability of workflows for data publishing could have an enormous impact on researchers, research practices and publishing paradigms, as well as on funding strategies and career and research evaluations. We present the generic components of such workflows to provide a reference model for these stakeholders. The RDA-WDS Data Publishing Workflows group set out to study the current data-publishing workflow landscape across disciplines and institutions. A diverse set of workflows were examined to identify common components and standard practices, including basic self-publishing services, institutional data repositories, long-term projects, curated data repositories, and joint data journal and repository arrangements. The results of this examination have been used to derive a data-publishing reference model comprising generic components. From an assessment of the current data-publishing landscape, we highlight important gaps and challenges to consider, especially when dealing with more complex workflows and their integration into wider community frameworks. It is clear that the data-publishing landscape is varied and dynamic and that there are important gaps and challenges. The different components of a data-publishing system need to work, to the greatest extent possible, in a seamless and integrated way to support the evolution of commonly understood and utilized standards and—eventually—to increased reproducibility. We therefore advocate the implementation of existing standards for repositories and all parts of the data-publishing process, and the development of new standards where necessary. Effective and trustworthy data publishing should be embedded in documented workflows. As more research communities seek to publish the data associated with their research, they can build on one or more of the components identified in this reference model.

Improving Discovery of and Access to Digital Repository Contents Using Semantic Web Standards: Columbia University's Academic Commons

This article describes the progress made towards developing Academic Commons (AC), Columbia Universitys digital repository, as an interoperable repository, through the use of RDF and non-RDF Semantic Web technologies. Approaches taken include the implementation of microdata to add semantic markup to HTML content; a collaboration with Oregon State Universitys (OSU) digital repository, ScholarsArchive@OSU (SA@OSU), to implement an application that indexes RDF data from OSU for use in AC; as well as an exploration of the recently released MODS RDF.

What are the Usage Dimensions of Open

What are the usage-related challenges currently faced by open efforts? For instance, open data is intriguing in principle, but in reality, making underlying data open can be problematic, conflicting with the need for research secrecy (whether driven by the desire to be first to publish, or the desire of funders to hold onto data to protect future discovery potential), the potential for misinterpretation by other researchers, and so on. Publishing clinical trial data in open formats is also intriguing but would run afoul of many current consent agreements, particularly older consents. Open access is similarly challenged in some instances by a conflict between which version of papers is allowed appear in open repositories. What is the value of archiving non-final versions? What are the range of issues here, what are the perspectives, and what might be some possible solutions?

Making MODS to Linked Open Data: A Collaborative Effort for Developing MODS/RDF

Publishing library catalog records as Linked Open Data is a challenge to many libraries because there is no community-driven best practice that each individual library can easily follow and implement into its workflow. Publishing library data as Linked Open Data is common practice for many national libraries, notably the British Library, French National Library, and the German National Library as well as for metadata aggregators and service providers, such as Europeana and the Online Computer Library Center (OCLC). However, the ways in which these institutions execute