Empowering Students to Use Metadata for Information Searches

The use of metadata tends to be regarded as a skill for librarians only, but some metadata knowledge can benefit students in any course when seeking sources for research. This article discusses how a library workshop was designed for undergraduate students to use metadata in their research process

Infrastructure, Standards, and Policies for Research Data Management

This paper discusses the needs and importance of research data management and introduces the concept of research data management as an infrastructure service. Although many resources have been made available for research data management, most of them are developed as “islands” and lack linking mechanisms. The lack of integrated and interconnected resources has contributed to high cost and duplicated efforts in data management operations. The vision of research data management as an infrastructure service is not only to improve the efficiency of research data management but also the productivity of the research enterprise. Each of the three dimensions—infrastructure, standards, and policies— addresses a critical aspect of research data managementto make the data infrastructure services work

Exploring data practices of the earthquake engineering community

There is a need to compare and contrast data practices of different disciplines and groups. This study explores data practices in earthquake engineering (EE), an interdisciplinary field with a variety of research activities and dynamic data types and forms. Findings identify the activities of typical EE research projects, the types and forms of data produced and used in those activities, the project roles played by EE researchers in connection with data practices, the tools used to manage data in those activities, the types and sources of data quality problems in EE, and the perceptions of data quality in EE. A strong relation exists among these factors, with a stronger role for test specimens and high quality documentation and more blurring of project roles than in other fields. Suggestions are provided for resolving contradictions impeding EE researchers’ curation and archiving activities and for future research on data practices

Organizational needs for managing and preserving geospatial data and related electronic records

Government agencies and other organizations are required to manage and preserve records that they create and use to facilitate future access and reuse. The increasing use of geospatial data and related electronic records presents new challenges for these organizations, which have relied on traditional practices for managing and preserving records in printed form. This article reports on an investigation of current and future needs for managing and preserving geospatial electronic records on the part of localand state-level organizations in the New York City metropolitan region. It introduces the study and describes organizational needs observed, including needs for organizational coordination and interorganizational cooperation throughout the entire data lifecycle

Metadata Workflows Across Research Domains: Challenges and Opportunities for Supporting the DFC Cyberinfrastructure

Metadata is necessary for finding, using, and properly managing scientific data. This master's paper presents results from a survey studying metadata workflows. A metadata workflow is a workflow that generates metadata for a data collection. A questionnaire was distributed to DataNet Federation Consortium researchers and collaborators. There were fourteen participants representing the following domains: hydrology, biology, climatology, ecology, library sciences, computer science, engineering, social sciences, and information sciences. Data management best practices recommend that data documentation, including metadata planning, occur prior to the data collection activity. However, the results of this survey indicate that in the scientific domains explored, more metadata is created during and after the data collection process than when the activity commences. Results also show that few researchers take advantage of automated metadata generation workflows. In addition, 9% of respondents did not know whether or not a standardized metadata scheme is used in their institution, and 20% did not know whether or not they provide metadata along with their data to repositories. Lastly, impediments to research data sharing and reproducibility were explored, including the need for highly specialized knowledge, software, or equipment. Data curators, librarians, and archivists, along with automated systems, can assist researchers by intervening earlier in the data life cycle in order to produce higher-quality metadata and ensure long-term data preservation.Master of Science in Information Scienc

Some challenges and issues in managing, and preserving access to, long-lived collections of digital scientific and technical data

One goal of the Committee on Data for Science and Technology is to solicit information about, promote discussion of, and support action on the many issues related to scientific and technical data preservation, archiving, and access. This brief paper describes four broad categories of issues that help to organize discussion, learning, and action regarding the work needed to support the long-term preservation of, and access to, scientific and technical data. In each category, some specific issues and areas of concern are described

Digital Curation and Preservation Bibliography 2010

This selective bibliography includes over 500 articles, books, and technical reports that are useful in understanding digital curation and preservation. The Digital Curation and Preservation Bibliography includes published articles, books, and technical reports. All included works are in English. The bibliography does not cover conference papers, digital media works (such as MP3 files), editorials, e-mail messages, letters to the editor, presentation slides or transcripts, unpublished e-prints, or weblog postings. Most sources have been published between 2000 and the present; however, a limited number of key sources published prior to 2000 are also included

A Proposal on Using Reuse Readiness Levels to Measure Software Reusability

The use of scientific data is becoming increasingly dependent on the software that fosters such use. As the ability to reuse software contributes to capabilities for reusing software-dependent data, instruments for measuring software reusability contribute to the reuse of software and related data. The development and current state of a proposed set of Reuse Readiness Levels (RRLs) are summarized, and potential uses of the software reusability measures are described, along with proposed use cases to support sponsorship of software projects, software production, software adoption, and data stewardship during the systems development lifecycle and the data lifecycle

Connecting Researchers to Repositories IMLS Project Report

Abstract: Despite a general consensus that making research data available is beneficial to many stakeholders, data sharing/curation is still not performed as an integrated step in most research lifecycles or common practice in the academic setting. Given many efforts over the last several years, why aren’t repositories used more by researchers? This question was explored in two workshops meant to consider the next steps in developing the Data Curation Profiles (DCP) Toolkit. It identifies a unique approach to help efforts to increase data deposits in research data repositories from an entrepreneurial perspective

An Epidemiology of Big Data

Federal legislation designed to transform the U.S. healthcare system and the emergence of mobile technology are among the common drivers that have contributed to a data explosion, with industry analysts and stakeholders proclaiming this decade the big data decade in healthcare (Horowitz, 2012). But a precise definition of big data is hazy (Dumbill, 2013). Instead, the healthcare industry mainly relies on metaphors, buzzwords, and slogans that fail to provide information about big data\u27s content, value, or purposes for existence (Burns, 2011). Bollier and Firestone (2010) even suggests big data does not really exist in healthcare (p. 29). While federal policymakers and other healthcare stakeholders struggle with the adoption of Meaningful Use Standards, International Classification of Diseases-10 (ICD-10), and electronic health record interoperability standards, big data in healthcare remains a widely misunderstood phenomenon. Borgman (2012) found by studying how data are created, handled, and managed in multi-disciplinary collaborations, we can inform science policy and practice (p. 12). Through the narratives of nine leaders representing three key stakeholder classes in the healthcare ecosystem: government, providers and consumers, this phenomenological research study explored a fundamental question: Within and across the narratives of three key healthcare stakeholder classes, what are the important categories of meaning or current themes about big data in healthcare? This research is significant because it: (1) produces new thematic insights about the meaning of big data in healthcare through narrative inquiry; (2) offers an agile framework of big data that can be deployed across all industries; and, (3) makes a unique contribution to scholarly qualitative literature about the phenomena of big data in healthcare for future research on topics including the diffusion and spread of health information across networks, mixed methods studies about big data, standards development, and health policy