International Journal of Digital Curation
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Complexities of Digital Preservation in a Virtual Reality Environment, the Case of Virtual Bethel
Full text linkThe complexity of preserving virtual reality environments combines the challenges of preserving singular digital objects, the relationships among those objects, and the processes involved in creating those relationships. A case study involving the preservation of the Virtual Bethel environment is presented. This case is active and ongoing. The paper provides a brief history of the Bethel AME Church of Indianapolis and its importance, then describes the unique preservation challenges of the Virtual Bethel project, and finally provides guidance and preservation recommendations for Virtual Bethel, using the National Digital Stewardship Alliance Levels of Preservation. Discussion of limitations of the guidance and recommendations follow
Participatory Prototype Design: Developing a Sustainable Metadata Curation Workflow for Maternal Child Health Research
Full text linkThis paper describes the findings from a participatory prototype design project, where the authors worked with maternal and child health (MCH) researchers and stakeholders to develop a MCH metadata profile and sustainable curation workflow. This work led to the development of three prototypes: 1) a study catalogue hosted in Dataverse, 2) a metadata and research records repository hosted in REDCap and 3) a metadata harvesting tool/dashboard hosted within the Shiny RStudio environment. We present a brief overview of the methods used to develop the metadata profile, curation workflow and prototypes. Researchers and other stakeholders were participant-collaborators throughout the project. The participatory process involved a number of steps, including but not limited to: initial project design and grant writing; scoping and mapping existing practices, workflows and relevant metadata standards; creating the metadata profile; developing semi-automated and manual techniques to harvest and transform metadata; and end project sustainability/future planning. In this paper, we discuss the design process and project outcomes, limitations and benefits of the approach, and implications for researcher-oriented metadata and data curation initiatives
Data Stewardship Addressing Disciplinary Data Management Needs
Full text linkOne of the biggest challenges for multidisciplinary research institutions which provide data management support to researchers is addressing disciplinary differences (Akers and Doty,2013). Centralised services need to be general enough to cater for all the different flavours of research conducted in an institution. At the same time, focusing on the common denominator means that subject-specific differences and needs may not be effectively addressed. In 2017, Delft University of Technology (TU Delft) embarked on an ambitious Data Stewardship project, aiming to comprehensively address data management needs across a multi-disciplinary campus. In this article we describe the principles behind the Data Stewardship project at TU Delft, the progress so far, identify the key challenges and explain our plans for the future
Giving Datasets Context: a Comparison Study of Institutional Repositories that Apply Varying Degrees of Curation
Full text linkThis research study compared four academic libraries’ approaches to curating the metadata of dataset submissions in their institutional repositories and classified them in one of four categories: no curation, pre-ingest curation, selective curation, and post-ingest curation. The goal is to understand the impact that curation may have on the quality of user-submitted metadata. The findings were 1) the metadata elements varied greatly between institutions, 2) repositories with more options for authors to contribute metadata did not result in more metadata contributed, 3) pre- or post-ingest curation process could have a measurable impact on the metadata but are difficult to separate from other factors, and 4) datasets submitted to a repository with pre- or post-ingest curation more often included documentation
Are the FAIR Data Principles fair?
Full text linkThis practice paper describes an ongoing research project to test the effectiveness and relevance of the FAIR Data Principles. Simultaneously, it will analyse how easy it is for data archives to adhere to the principles. The research took place from November 2016 to January 2017, and will be underpinned with feedback from the repositories.
The FAIR Data Principles feature 15 facets corresponding to the four letters of FAIR - Findable, Accessible, Interoperable, Reusable. These principles have already gained traction within the research world. The European Commission has recently expanded its demand for research to produce open data. The relevant guidelines1are explicitly written in the context of the FAIR Data Principles. Given an increasing number of researchers will have exposure to the guidelines, understanding their viability and suggesting where there may be room for modification and adjustment is of vital importance.
This practice paper is connected to a dataset(Dunning et al.,2017) containing the original overview of the sample group statistics and graphs, in an Excel spreadsheet. Over the course of two months, the web-interfaces, help-pages and metadata-records of over 40 data repositories have been examined, to score the individual data repository against the FAIR principles and facets. The traffic-light rating system enables colour-coding according to compliance and vagueness. The statistical analysis provides overall, categorised, on the principles focussing, and on the facet focussing results.
The analysis includes the statistical and descriptive evaluation, followed by elaborations on Elements of the FAIR Data Principles, the subject specific or repository specific differences, and subsequently what repositories can do to improve their information architecture.
(1) H2020 Guidelines on FAIR Data Management:http://ec.europa.eu/research/participants/data/ref/h2020/grants_manual/hi/oa_pilot/h2020-hi-oa-data-mgt_en.pd
Integration of an Active Research Data System with a Data Repository to Streamline the Research Data Lifecyle: Pure-NOMAD Case Study
Full text linkResearch funders have introduced requirements that expect researchers to properly manage and publicly share their research data, and expect institutions to put in place services to support researchers in meeting these requirements. So far the general focus of these services and systems has been on addressing the final stages of the research data lifecycle (archive, share and re-use), rather than stages related to the active phase of the cycle (collect/create and analyse). As a result, full integration of active data management systems with data repositories is not yet the norm, making the streamlined transition of data from an active to a published and archived status an important challenge. In this paper we present the integration between an active data management system developed in-house (NOMAD) and Elsevier’s Pure data repository used at our institution, with the aim of offering a simple workflow to facilitate and promote the data deposit process. The integration results in a new data management and publication workflow that helps researchers to save time, minimize human errors related to manually handling files, and further promote data deposit together with collaboration across the institution
How Valid is your Validation? A Closer Look Behind the Curtain of JHOVE
Full text linkValidation is a key task of any preservation workflow and often JHOVE is the first tool of choice for characterizing and validating common file formats. Due to the tool’s maturity and high adoption, decisions if a file is indeed fit for long-term availability are often made based on JHOVE output. But can we trust a tool simply based on its wide adoption and maturity by age? How does JHOVE determine the validity and well-formedness of a file? Does a module really support all versions of a file format family? How much of the file formats’ standards do we need to know and understand in order to interpret the output correctly? Are there options to verify JHOVE-based decisions within preservation workflows? While the software has been a long-standing favourite within the digital curation domain for many years, a recent look at JHOVE as a vital decision supporting tool is currently missing. This paper presents a practice report which aims to close this gap
Measuring FAIR Principles to Inform Fitness for Use
Full text linkFor open science to flourish, data and any related digital outputs should be discoverable and re-usable by a variety of potential consumers. The recent FAIR Data Principles produced by the Future of Research Communication and e-Scholarship (FORCE11) collective provide a compilation of considerations for making data findable, accessible, interoperable, and re-usable. The principles serve as guideposts to ‘good’ data management and stewardship for data and/or metadata. On a conceptual level, the principles codify best practices that managers and stewards would find agreement with, exist in other data quality metrics, and already implement. This paper reports on a secondary purpose of the principles: to inform assessment of data’s FAIR-ness or, put another way, data’s fitness for use. Assessment of FAIR-ness likely requires more stratification across data types and among various consumer communities, as how data are found, accessed, interoperated, and re-used differs depending on types and purposes. This paper’s purpose is to present a method for qualitatively measuring the FAIR Data Principles through operationalizing findability, accessibility, interoperability, and re- usability from a re-user’s perspective. The findings may inform assessments that could also be used to develop situationally-relevant fitness for use frameworks
Archiving Large-Scale Legacy Multimedia Research Data: A Case Study
Full text linkIn this paper we provide a case study of the creation of the DCAL Research Data Archive at University College London. In doing so, we assess the various challenges associated with archiving large-scale legacy multimedia research data, given the lack of literature on archiving such datasets. We address issues such as the anonymisation of video research data, the ethical challenges of managing legacy data and historic consent, ownership considerations, the handling of large-size multimedia data, as well as the complexity of multi-project data from a number of researchers and legacy data from eleven years of research