International Journal of Digital Curation
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Project to Production: Digital Preservation at the Houses of Parliament, 2010–2020
Get PDFThe Parliamentary Archives is responsible for preserving and providing access to the historical records of the UK Parliament, a collection of national, and indeed international, importance which encompasses a wide range of digital content, created and used in an ever changing environment. Since 2010 a staged project has led to the successful implementation of an operational digital repository. The transition from project to production allows the Parliamentary Archives to reflect on the organisation’s progress in digital preservation. However, the deployment of a production digital repository also allows the Parliamentary Archives to outline future goals. The project has demonstrated the viability of implementing digital preservation infrastructure. The challenge remains to embed digital preservation as a business as usual activity
Assessing Perceived Usability of the Data Curation Profile Toolkit Using the Technology Acceptance Model
Get PDFThe Data Curation Profiles Toolkit (DCPT) emerged out of a Purdue University Libraries’ 2004 initiative to engage in multidisciplinary research. It is a tool developed to assist librarians and other information professionals to conduct data interviews and identify the needs of researchers when managing, sharing, or curating their data. The DCPT has been widely adopted and applied in various contexts but its usability as a tool has not been formally assessed. To address this need, we have conducted a survey of users of the DCPT. The survey included quantitative measures of potential influencing factors of using the DCPT and its perceived usability (its usefulness as a tool and its ease of use). Open-ended questions about users’ experiences with the DCPT were also included to better understand the strengths and weaknesses of the tool, as well as areas that could be improved. Factor analysis of the quantitative results and subsequent regression models revealed several underlying factors that affect the perceived usability of the DCPT. Responses to the open-ended questions revealed several themes of users’ concerns: the amount of time required to use the DCPT, the structure and format of the DCPT, alignment of the DCPT with particular contexts, and the use of the DCPT to engage faculty and the library community. By correlating themes identified from the open-ended questions with the analysis of quantitative data, this paper provides the first empirical assessment of the DCPT that could help further improve the toolkit’s usability based on user needs and expectations. The methodology used in the study could readily be applied to assess and improve the utility of other tools used by data and information professional
Data Carpentry: Workshops to Increase Data Literacy for Researchers
Get PDFIn many domains the rapid generation of large amounts of data is fundamentally changing how research is done. The deluge of data presents great opportunities, but also many challenges in managing, analyzing and sharing data. However, good training resources for researchers looking to develop skills that will enable them to be more effective and productive researchers are scarce and there is little space in the existing curriculum for courses or additional lectures. To address this need we have developed an introductory two-day intensive workshop, Data Carpentry, designed to teach basic concepts, skills, and tools for working more effectively and reproducibly with data. These workshops are based on Software Carpentry: two-day, hands-on, bootcamp style workshops teaching best practices in software development, that have demonstrated the success of short workshops to teach foundational research skills. Data Carpentry focuses on data literacy in particular, with the objective of teaching skills to researchers to enable them to retrieve, view, manipulate, analyze and store their and other’s data in an open and reproducible way in order to extract knowledge from data
Content Curation for Research: A Framework for Building a “Data Museum”
Get PDFIn the current digital age, data are everywhere and are continually being created, collected and otherwise captured by a range of users for a variety of applications. Curating digital content is a growing concern both for business users and academic researchers. Selecting, collecting, preserving and archiving digital assets, especially research data sets, are important steps in the research life cycle and can help expand the boundaries of research by allowing data to be reused. Creating research data sets often starts with selecting input data sources; in this age of new or “big” data, that choice set keeps expanding, thereby making it more difficult and time consuming to discover and understand the vast data landscape when beginning an empirical research project. This paper proposes an approach to make finding and learning about data easier and less time-consuming for researchers. While cognizant of the role of digital curation for research data sets, we focus on the traditional “museum” definition of curation to outline how data-oriented content curation can support research. The process of selecting, evaluating and presenting information about potential data inputs can help researchers more easily understand how certain data sets are used and better determine which data sources might be fit for their purposes. Although the paper draws on examples from economics citing U.S. data, the techniques could be used across disciplines and countries
MOLES3: Implementing an ISO standards driven data catalogue
Get PDFISO19156 Observations and Measurements (O&M) provides a standardised framework for organising information about the collection of information about the environment. Here we describe the implementation of a specialisation of O&M for environmental data, the Metadata Objects for Linking Environmental Sciences (MOLES3).MOLES3 provides support for organising information about data, and for user navigation around data holdings. The implementation described here, “CEDA-MOLES”, also supports data management functions for the Centre for Environmental Data Archival, CEDA. The previous iteration of MOLES (MOLES2) saw active use over five years, being replaced by CEDA-MOLES in late 2014. During that period important lessons were learnt both about the information needed, as well as how to design and maintain the necessary information systems. In this paper we review the problems encountered in MOLES2; how and why CEDA-MOLES was developed and engineered; the migration of information holdings from MOLES2 to CEDA-MOLES; and, finally, provide an early assessment of MOLES3 (as implemented in CEDA-MOLES) and its limitations.Key drivers for the MOLES3 development included the necessity for improved data provenance, for further structured information to support ISO19115 discovery metadata export (for EU INSPIRE compliance), and to provide appropriate fixed landing pages for Digital Object Identifiers (DOIs) in the presence of evolving datasets. Key lessons learned included the importance of minimising information structure in free text fields, and the necessity to support as much agility in the information infrastructure as possible without compromising on maintainability both by those using the systems internally and externally (e.g. citing in to the information infrastructure), and those responsible for the systems themselves. The migration itself needed to ensure continuity of service and traceability of archived assets
Harmonizing the Metadata Among Diverse Climate Change Datasets
Get PDFOne of the critical problems in the curation of research data is the harmonization of its internal metadata schemata. The value of harmonizing such data is well illustrated by the Berkeley Earth project, which successfully integrated into one metadata schema the raw climate datasets from a wide variety geographical sources and time periods (250 years). Doing this enabled climate scientists to calculate a more accurate estimate of the recent changes in Earth’s average land surface temperatures and to ascertain the extent to which climate change is anthropogenic. This paper surveys some of the approaches that have been taken to the integration of data schemata in general and examines some of the specific metadata features of the source surface temperature datasets that were harmonized by Berkeley Earth. The conclusion drawn from this analysis is that the original source data and the Berkeley Earth common format provides a promising training set on which to apply machine learning methods for replicating the human data integration process. This paper describes research in progress on a domain-independent approach to the metadata harmonization problem that could be applied to other fields of study and be incorporated into a data portal to enhance the discoverability and reuse of data from a broad range of data sources
Research Data Management in a Developing Country: A Personal Journey
Get PDFThis paper explores our own journey to get to grips with research data management (RDM). It also mentions the overlap between our own ‘journeys’ and that of the country. We share the lessons that we learnt along the way – the most important lesson being that you can learn many wonderful and valuable RDM lessons from the international trend setters, but in the end you need to get your hands dirty and get the work done yourself. You must, within the set parameters, implement the RDM practice that is both appropriate and acceptable for and to your own set of researchers – who may be conducting research in a context that may be very dissimilar to that of international peers
Cross-Linking Between Journal Publications and Data Repositories: A Selection of Examples
Get PDFThis article provides a selection of examples of the many ways that a link can be made between a journal article (whether in a data journal or otherwise) and a dataset held in a data repository. In some cases the method of linking is well established, while in others, they have yet to be rolled out uniformly across the journal landscape. We explore ways in which these examples might be implemented in a data journal, such as Geoscience Data Journal, as explored by the PREPARDE project
Building Support for Research Data Management: Biographies of Eight Research Universities
Get PDFAcademic research libraries are quickly developing support for research data management (RDM), including both new services and infrastructure. Here, we tell the stories of how eight different universities have developed programs of RDM support, focusing on the prominent role of the library in educating and assisting researchers with managing their data throughout the research lifecycle. Based on these stories, we construct timelines for each university depicting key steps in building support for RDM, and we discuss similarities and dissimilarities among universities in motivation to provide RDM support, collaborations among campus units, assessment of needs and services, and changes in staffing
The Front Office–Back Office Model: Supporting Research Data Management in the Netherlands
Get PDFHigh quality and timely data management and secure storage of data, both during and after completion of research, are an essential prerequisite for sharing that data. It is therefore crucial that universities and research institutions themselves formulate a clear policy on data management within their organization. For the implementation of this data management policy, high quality support for researchers and an adequate technical infrastructure are indispensable. This practice paper will present an overview of the merging federated data infrastructure in the Netherlands with its front office – back office model, as a use case of an efficient and effective national support infrastructure for researchers. We will elaborate on the stakeholders involved, on the services they offer each other, and on the benefits of this model not only for the front and back offices themselves, but also for the researchers. We will also pay attention to a number of challenges that we are facing, like the implementation of a technical infrastructure for automatic data ingest and integrating access to research data