Here, KAPTUR This! Identifying and Selecting the Infrastructure Required to Support the Curation and Preservation of Visual Arts Research Data

Research data is increasingly perceived as a valuable resource and, with appropriate curation and preservation, it has much to offer learning, teaching, research, knowledge transfer and consultancy activities in the visual arts. However, very little is known about the curation and preservation of this data: none of the specialist arts institutions have research data management policies or infrastructure and anecdotal evidence suggests that practice is ad hoc, left to individual researchers and teams with little support or guidance. In addition, the curation and preservation of such diverse and complex digital resources as found in the visual arts is, in itself, challenging. Led by the Visual Arts Data Service, a research centre of the University for the Creative Arts, in collaboration with the Glasgow School of Art; Goldsmiths College, University of London; and University of the Arts London, and funded by JISC, the KAPTUR project (2011-2013) seeks to address the lack of awareness and explore the potential of research data management systems in the arts by discovering the nature of research data in the visual arts, investigating the current state of research data management, developing a model of best practice applicable to both specialist arts institutions and arts departments in multidisciplinary institutions, and by applying, testing and piloting the model with the four institutional partners. Utilising the findings of the KAPTUR user requirement and technical review, this paper will outline the method and selection of an appropriate research data management system for the visual arts and the issues the team encountered along the way

Disciplinary differences in faculty research data management practices and perspectives

Academic librarians are increasingly engaging in data curation by providing infrastructure (e.g., institutional repositories) and offering services (e.g., data management plan consultations) to support the management of research data on their campuses. Efforts to develop these resources may benefit from a greater understanding of disciplinary differences in research data management needs. After conducting a survey of data management practices and perspectives at our research university, we categorized faculty members into four research domains—arts and humanities, social sciences, medical sciences, and basic sciences—and analyzed variations in their patterns of survey responses. We found statistically significant differences among the four research domains for nearly every survey item, revealing important disciplinary distinctions in data management actions, attitudes, and interest in support services. Serious consideration of both the similarities and dissimilarities among disciplines will help guide academic librarians and other data curation professionals in developing a range of data-management services that can be tailored to the unique needs of different scholarly researchers

Towards Standardization: A Participatory Framework for Scientific Standard-Making

In contemporary scientific research, standard-making and standardization are key processes for the sharing and reuse of data. The goals of this paper are twofold: 1) to stress that collaboration is crucial to standard-making, and 2) to urge recognition of metadata standardization as part of the scientific process. To achieve these goals, a participatory framework for developing and implementing scientific metadata standards is presented. We highlight the need for ongoing, open dialogue within and among research communities at multiple levels. Using the Long Term Ecological Research network adoption of the Ecological Metadata Language as a case example in the natural sciences, we illustrate how a participatory framework addresses the need for active coordination of the evolution of scientific metadata standards. The participatory framework is contrasted with a hierarchical framework to underscore how the development of scientific standards is a dynamic and continuing process. The roles played by ‘best practices’ and ‘working standards’ are identified in relation to the process of standardization

Defining What Matters When Preserving Web-Based Personal Digital Collections: Listening to Bloggers

User-generated content (UGC) has become a part of personal digital collections on the Web, as such collections often contain personal memories, activities, thoughts and even profiles. With the increase in the creation of personal materials on the Web, the needs for archiving and preserving these materials are increasing, not only for the purpose of developing personal archives but also for the purpose of capturing social memory and tracking human traces in this era. Using both survey and interview methods, this study investigated blogs, one popular type of UGC, and analyzed travel bloggers’ perceptions of the value of blogs and the elements of blogs that are important for preservation. The study respondents found personal and sentimental value (e.g., a way to express themselves, a way to keep personal memories and thoughts, and a way to maintain a record for their family) to be the most important reason for preserving blogs, followed by informational value and cultural/historical value. Sharing also appeared as one of the values that respondents found in their blogs. The respondents reported that self-created blog posts (content) and information related to the blog posts (context) are more important to preserve than some other elements (behavior and appearance). Integrating what bloggers consider as most valuable and what archivists think are worth preserving may be an important step when collecting personal blogs

Developing an Approach for Data Management Education: A Report from the Data Information Literacy Project

This paper describes the initial results from the Data Information Literacy (DIL) project designed to identify the educational needs of graduate students across a variety of science disciplines and respond with effective educational interventions to meet those needs. The DIL project consists of five teams in disparate disciplines from four academic institutions in the United States. The project teams include a data librarian, a subject-specialist or information literacy librarian, and a faculty member representing a disciplinary group of students. Interviews with the students and faculty members present a detailed snapshot of graduate student needs in data management education. Following our study, educational programs addressing identified needs will be delivered in the fall of 2012 and spring of 2013. Our findings from the project interviews are analyzed here, with a preview of the training approaches that will be taken by the five teams