International Journal of Digital Curation
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Connecting Data Publication to the Research Workflow: A Preliminary Analysis
Get PDFThe data curation community has long encouraged researchers to document collected research data during active stages of the research workflow, to provide robust metadata earlier, and support research data publication and preservation. Data documentation with robust metadata is one of a number of steps in effective data publication. Data publication is the process of making digital research objects ‘FAIR’, i.e. findable, accessible, interoperable, and reusable; attributes increasingly expected by research communities, funders and society. Research data publishing workflows are the means to that end. Currently, however, much published research data remains inconsistently and inadequately documented by researchers. Documentation of data closer in time to data collection would help mitigate the high cost that repositories associate with the ingest process. More effective data publication and sharing should in principle result from early interactions between researchers and their selected data repository. This paper describes a short study undertaken by members of the Research Data Alliance (RDA) and World Data System (WDS) working group on Publishing Data Workflows. We present a collection of recent examples of data publication workflows that connect data repositories and publishing platforms with research activity ‘upstream’ of the ingest process. We re-articulate previous recommendations of the working group, to account for the varied upstream service components and platforms that support the flow of contextual and provenance information downstream. These workflows should be open and loosely coupled to support interoperability, including with preservation and publication environments. Our recommendations aim to stimulate further work on researchers’ views of data publishing and the extent to which available services and infrastructure facilitate the publication of FAIR data. We also aim to stimulate further dialogue about, and definition of, the roles and responsibilities of research data services and platform providers for the ‘FAIRness’ of research data publication workflows themselves
Recognizing the Diversity of Contributions: A Case Study for Framing Attribution and Acknowledgement for Scientific Data
Get PDFAs scientific data volumes, format types, and sources increase rapidly with the invention and improvement of scientific capabilities, the resulting datasets are becoming more complex to manage as well. One of the significant management challenges is pulling apart the individual contributions of specific people and organizations within large, complex projects. This is important for two aspects: 1) assigning responsibility and accountability for scientific work, and 2) giving professional credit to individuals (e.g. hiring, promotion, and tenure) who work within such large projects. This paper aims to review the extant practice of data attribution and how it may be improved. Through a case study of creating a detailed attribution record for a climate model dataset, the paper evaluates the strengths and weaknesses of the current data attribution method and proposes an alternative attribution framework accordingly. The paper concludes by demonstrating that, analogous to acknowledging the different roles and responsibilities shown in movie credits, the methodology developed in the study could be used in general to identify and map out the relationships among the organizations and individuals who had contributed to a dataset. As a result, the framework could be applied to create data attribution for other dataset types beyond climate model datasets. Â
The Digitized Archival Document Trustworthiness Scale
Get PDFDesignated communities are central to validation of preservation. If a designated community is able to understand and use information found within a digital repository, the assumption is that the information has been properly preserved. As judging the trustworthiness of information requires at least some level of understanding of that information, this paper presents results of a study aimed at developing a tool for measuring designated community members’ perceptions of trustworthiness for preserved information found within a digital repository. The study focuses on genealogists at the Washington State Digital Archives who routinely interact with digitized genealogical records, including digitized marriage, death, and birth records. Results of the study include construction of an original Digitized Archival Document Trustworthiness Scale (DADTS). DADTS is a ready-made tool for digital curators to use to measure the trustworthiness perceptions of their designated community members. Implications of this study include the feasibility of engaging members of a designated community in the construction of a scale for measuring trustworthiness perception, thereby providing deeper insight into the understandability and usability of preserved information by that designated community.Â
Factors Influencing Research Data Reuse in the Social Sciences: An Exploratory Study
Get PDFThe development of e-Research infrastructure has enabled data to be shared and accessed more openly. Policy mandates for data sharing have contributed to the increasing availability of research data through data repositories, which create favourable conditions for the re-use of data for purposes not always anticipated by original collectors. Despite the current efforts to promote transparency and reproducibility in science, data re-use cannot be assumed, nor merely considered a ‘thrifting’ activity where scientists shop around in data repositories considering only the ease of access to data. The lack of an integrated view of individual, social and technological influential factors to intentional and actual data re-use behaviour was the key motivator for this study. Interviews with 13 social scientists produced 25 factors that were found to influence their perceptions and experiences, including both their unsuccessful and successful attempts to re-use data. These factors were grouped into six theoretical variables: perceived benefits, perceived risks, perceived effort, social influence, facilitating conditions, and perceived re-usability. These research findings provide an in-depth understanding about the re-use of research data in the context of open science, which can be valuable in terms of theory and practice to help leverage data re-use and make publicly available data more actionable.Â
Establishing a Research Data Management Service at Loughborough University
Get PDFIn common with most UK universities Loughborough University needed to be compliant with the EPSRC Data Expectations by May 2015. This paper explains the process the University went through to meet these expectations. The paper also demonstratea how University senior management took the opportunity to look beyond compliance with EPSRC requirements. Project staff were challenged to identify a solution which would help to increase the University’s research visibility and reach. The solution to all of these challenges is an innovative and ground-breaking relationship between the University and three external partners. Investment has also been made in professional services staff to help manage and oversee the service. This paper explores the ways in which each element of Loughborough’s research data service helps to reduce the burden on researchers, how much of the infrastructure is invisible to the research community, and how the service is being embedded in existing infrastructure and workflows.Â
Towards a Collaborative National Research Data Management Network
Get PDFThis paper describes the plans and strategies to develop Portage, a national network of sustainable, shared services for research data management (RDM) in Canada. A description of the RDM context in Canada is provided. This environment has heightened expectations around the Government of Canada’s Open Science plans and includes deliverables aimed at improving access to publications and data resulting from federally funded scientific activities. At the same time, a recent environmental scan published by Canada’s three federal research granting councils reveals significant gaps in services, infrastructure, and funding mechanisms to support RDM. In addition, Canada’s RDM environment consists of stakeholders from a variety of communities with minimal ongoing coordination or cooperation. The Portage network was conceived as a collaborative network model based on libraries’ strong connections with researchers across the disciplines, an ethos of curation and preservation, and experience with systems for managing data in all its forms. A pilot project provided Portage with a vision and set of principles, and identified several objectives as the small wins that would build the trust and shared understanding required for a successful network. Current services and activities of Portage, including a data management planning tool and an infrastructure project, are described in this paper. Portage now faces the challenge of moving from project to operational network, and the challenge of establishing a sustainable governance model. CARL appointed a Steering Committee that will be proposing a full governance model at the conclusion of this transition period. Using a framework of factors identified in the literature, several relevant collaborative and network governance models are being explored.This paper outlines experience to date with Portage and matters under consideration for long-term sustainability, with a goal of engaging international colleagues in discussion and furthering the concepts for the benefit of RDM networks everywhere.Â
Provenance in support of ANDS\u27 four transformations
No full textThis article introduces the provenance activities that are being carried out at the Australia National Data Services (ANDS). Since its beginning, ANDS has been promoting four data transformations so that Australia’s research data become more valuable and reusable by researchers. Among many other activities that enable the four transformations, ANDS has been encouraging ANDS partners to capture and describe rich context at the time when a data collection is created. In 2015, ANDS funded a number of external projects that had provenance components. In addition, ANDS is working on the interoperability between the schema that is used by the ANDS research data registration and discovery service – Research Data Australia (RDA) – and the W3C recommended provenance standard, Provenance Ontology (PROV-O), and investigating how to enrich the schema to access provenance information. The article concludes by discussing the lessons we learnt and our future planned activity
Metadata and Reproducibility: A Case Study of Gravitational Wave Research Data Management
No full textThe complexity of computationally-intensive scientific research poses great challenges for both research data management and research reproducibility. What metadata needs to be captured for tracking, reproducing, and reusing computational results is the starting point in developing metadata models to fulfil these functions of data management. This paper reports the findings from interviews with gravitational wave (GW) researchers, which were designed to gather user requirements to develop a metadata model. Motivations for keeping documentation of data and analysis results include trust, accountability and continuity of work. Research reproducibility relies on metadata that represents code dependencies and versions and has good documentation for verification. Metadata specific to GW data, workflows and outputs tend to differ from those currently available in metadata standards. The paper also discusses the challenges in representing code dependencies and workflows.
Data Management in the Long Tail: Science, Software, and Service
Get PDFScientists in all fields face challenges in managing and sustaining access to their research data. The larger and longer term the research project, the more likely that scientists are to have resources and dedicated staff to manage their technology and data, leaving those scientists whose work is based on smaller and shorter term projects at a disadvantage. The volume and variety of data to be managed varies by many factors, only two of which are the number of collaborators and length of the project. As part of an NSF project to conceptualize the Institute for Empowering Long Tail Research, we explored opportunities offered by Software as a Service (SaaS). These cloud-based services are popular in business because they reduce costs and labor for technology management, and are gaining ground in scientific environments for similar reasons. We studied three settings where scientists conduct research in small and medium-sized laboratories. Two were NSF Science and Technology Centers (CENS and C-DEBI) and the third was a workshop of natural reserve scientists and managers. These laboratories have highly diverse data and practices, make minimal use of standards for data or metadata, and lack resources for data management or sustaining access to their data, despite recognizing the need. We found that SaaS could address technical needs for basic document creation, analysis, and storage, but did not support the diverse and rapidly changing needs for sophisticated domain-specific tools and services. These are much more challenging knowledge infrastructure requirements that require long-term investments by multiple stakeholders.Â
Dash: Data Sharing Made Easy at the University of California
Get PDFScholars at the ten campuses of the University of California system, like their academic peers elsewhere, increasingly are being asked to ensure that data resulting from their research and teaching activities are subject to effective long-term management, public discovery, and retrieval. The new academic imperative for research data management (RDM) stems from mandates from public and private funding agencies, pre-publication requirements, institutional policies, and evolving norms of scholarly discourse. In order to meet these new obligations, scholars need access to appropriate disciplinary and institutional tools, services, and guidance. When providing help in these areas, it is important that service providers recognize the disparity in scholarly familiarity with data curation concepts and practices. While the UC Curation Center (UC3) at the California Digital Library supports a growing roster of innovative curation services for University use, most were intended originally to meet the needs of institutional information professionals, such as librarians, archivists, and curators. In order to address the new curation concerns of individual scholars, UC3 realized that it needed to deploy new systems and services optimized for stakeholders with widely divergent experiences, expertise, and expectations. This led to the development of Dash, an online data publication service making campus data sharing easy. While Dash gives the appearance of being a full-fledged repository, in actuality it is only a lightweight overlay layer that sits on top of standards-compliant repositories, such as UC3’s existing Merritt curation repository. The Dash service offers intuitive, easy-to-use interfaces for dataset submission, description, publication, and discovery. By imposing minimal prescriptive eligibility and submission requirements; automating and hiding the mechanical details of DOI assignment, data packaging, and repository deposit; and featuring a streamlined, self-service user experience that can be integrated easily into scholarly workflows, Dash is an important new service offering with which UC scholars can meet their RDM obligations.Â