Building Digital Libraries for Scientific Data: An Exploratory Study of Data Practices in Habitat Ecology

2006 ◽  
pp. 170-183 ◽  
Author(s):  
Christine Borgman ◽  
Jillian C. Wallis ◽  
Noel Enyedy
Keyword(s):  
Digital Libraries ◽  
Exploratory Study ◽  
Scientific Data ◽  
Habitat Ecology ◽  
Data Practices

An exploratory study of health scientists’ data reuse behaviors

2017 ◽  
Vol 69 (4) ◽  
pp. 389-407 ◽  
Author(s):  
Soohyung Joo ◽  
Sujin Kim ◽  
Youngseek Kim
Keyword(s):  
Organizational Support ◽  
Exploratory Study ◽  
Scientific Data ◽  
Perceived Usefulness ◽  
Data Reuse ◽  
Health Science ◽  
Equation Modeling ◽  
Survey Method ◽  
Research Model ◽  
Content Type

Purpose The purpose of this paper is to examine how health scientists’ attitudinal, social, and resource factors affect their data reuse behaviors. Design/methodology/approach A survey method was utilized to investigate to what extent attitudinal, social, and resource factors influence health scientists’ data reuse behaviors. The health scientists’ data reuse research model was validated by using partial least squares (PLS) based structural equation modeling technique with a total of 161 health scientists in the USA. Findings The analysis results showed that health scientists’ data reuse intentions are driven by attitude toward data reuse, community norm of data reuse, disciplinary research climate, and organizational support factors. This research also found that both perceived usefulness of data reuse and perceived concern involved in data reuse have significant influences on health scientists’ attitude toward data reuse. Research limitations/implications This research evaluated its newly proposed research model based on the theory of planned behavior using a sample from the community of scientists’ scholar database. This research showed an overall picture of how attitudinal, social, and resource factors influence health scientists’ data reuse behaviors. This research is limited due to its sample size and low response rate, so this study is considered as an exploratory study rather than a confirmatory study. Practical implications This research suggested for health science research communities, academic institutions, and libraries that diverse strategies need to be utilized to promote health scientists’ data reuse behaviors. Originality/value This research is one of initial studies in scientific data reuse which provided a holistic map about health scientists’ data sharing behaviors. The findings of this study provide the groundwork for strategies to facilitate data reuse practice in health science areas.

Accessibility and Usability Evaluation of Digital Library Article Pages

2022 ◽  
pp. 58-76
Author(s):  
Gonca Gokce Menekse Dalveren ◽  
Serhat Peker
Keyword(s):  
Digital Library ◽  
Digital Libraries ◽  
Exploratory Study ◽  
Usability Evaluation ◽  
Web Interfaces ◽  
Second Stage ◽  
Computing Machinery ◽  
Electronic Engineering ◽  
Usability Problems ◽  
Web Developers

This study aims to present an exploratory study about the accessibility and usability evaluation of digital library article pages. For this purpose, four widely known digital libraries (DLs), namely Science Direct, Institute of Electric and Electronic Engineering Xplore, Association for Computing Machinery, and SpringerLink, were examined. In the first stage, article web interfaces of these selected DLs were analyzed based on standard web guidelines using automatic evaluation tools to assess their accessibility. In the second stage, to evaluate the usability of these web interfaces, eye-tracking experiments with 30 participants were conducted. Obtained results of the analysis show that article pages of digital libraries are not of free of accessibility and usability problems. Overall, this study highlights accessibility and usability problems of digital library article interfaces, and these findings can provide the feedback to web developers in making their article pages more accessible and usable for their users.

Using Digital Libraries to Support Undergraduate Learning in Geomorphology

2010 ◽  
pp. 76-99
Author(s):  
Stephen Darby ◽  
Sally J. Priest ◽  
Karen Fill ◽  
Samuel Leung
Keyword(s):  
Online Learning ◽  
Spatial Data ◽  
Digital Libraries ◽  
Drainage Basin ◽  
Numerical Models ◽  
Scientific Data ◽  
Virtual Learning Environment ◽  
Global Perspective ◽  
Library Resources ◽  
Traditional Lectures

In this chapter we outline the issues involved in developing, delivering, and evaluating a Level 2 undergraduate module in fluvial geomorphology. The central concept of the module, which was designed to be delivered in a “blended” mode, involving a combination of traditional lectures and online learning activities, was the use of online digital library resources, comprising both data and numerical models, to foster an appreciation of physical processes influencing the evolution of drainage basins. The aim of the module was to develop the learners’ knowledge and understanding of drainage basin geomorphology, while simultaneously developing their abilities to (i) access spatial data resources and (ii) provide a focus for developing skills in scientific data analysis and modeling. The module adopts a global perspective, drawing on examples from around the world. We discuss the process of course and assessment design, explaining the pedagogy underlying the decision to adopt blended delivery. We share our teaching experiences, involving a particular combination of “face-to-face” lectures and online sessions, complemented by independent online learning, and supported by the associated virtual learning environment. Finally, we discuss the issues highlighted by a comprehensive module evaluation.

scholarly journals Scientific Publication Packages – A Selective Approach to the Communication and Archival of Scientific Output

2008 ◽  
Vol 1 ◽  
pp. 33-52 ◽  
Author(s):  
Jane Hunter
Keyword(s):  
Digital Libraries ◽  
Expert Knowledge ◽  
Research Output ◽  
Scientific Publication ◽  
Scientific Output ◽  
Scientific Data ◽  
Raw Data ◽  
Selective Approach ◽  
Technological Advances ◽  
Open Archives

The use of digital technologies within research has led to a proliferation of data, many new forms of research output and new modes of presentation and analysis. Many scientific communities are struggling with the challenge of how to manage the terabytes of data and new forms of output, they are producing. They are also under increasing pressure from funding organizations to publish their raw data, in addition to their traditional publications, in open archives. In this paper I describe an approach that involves the selective encapsulation of raw data, derived products, algorithms, software and textual publications within “scientific publication packages”. Such packages provide an ideal method for: encapsulating expert knowledge; for publishing and sharing scientific process and results; for teaching complex scientific concepts; and for the selective archival, curation and preservation of scientific data and output. They also provide a bridge between technological advances in the Digital Libraries and eScience domains. In particular, I describe the RDF-based architecture that we are adopting to enable scientists to construct, publish and manage “scientific publication packages” - compound digital objects that encapsulate and relate the raw data to its derived products, publications and the associated contextual, provenance and administrative metadata.

scholarly journals A Measure of Open Data: A Metric and Analysis of Reusable Data Practices in Biomedical Data Resources

2018 ◽  
Author(s):  
Seth Carbon ◽  
Robin Champieux ◽  
Julie McMurry ◽  
Lilly Winfree ◽  
Letisha R. Wyat ◽  
...  
Keyword(s):  
Scientific Community ◽  
Open Data ◽  
Scientific Data ◽  
Free Software ◽  
Biomedical Data ◽  
Drug Selection ◽  
Research Support ◽  
Creative Commons ◽  
Data Practices ◽  
Collective Data

ABSTRACTData is the foundation of science, and there is an increasing focus on how data can be reused and enhanced to drive scientific discoveries. However, most seemingly “open data” do not provide legal permissions for reuse and redistribution. Not being able to integrate and redistribute our collective data resources blocks innovation, and stymies the creation of life-improving diagnostic and drug selection tools. To help the biomedical research and research support communities (e.g. libraries, funders, repositories, etc.) understand and navigate the data licensing landscape, the (Re)usable Data Project (RDP) (http://reusabledata.org) assesses the licensing characteristics of data resources and how licensing behaviors impact reuse. We have created a ruleset to determine the reusability of data resources and have applied it to 56 scientific data resources (i.e. databases) to date. The results show significant reuse and interoperability barriers. Inspired by game-changing projects like Creative Commons, the Wikipedia Foundation, and the Free Software movement, we hope to engage the scientific community in the discussion regarding the legal use and reuse of scientific data, including the balance of openness and how to create sustainable data resources in an increasingly competitive environment.

scholarly journals Little science confronts the data deluge: habitat ecology, embedded sensor networks, and digital libraries

2007 ◽  
Vol 7 (1-2) ◽  
pp. 17-30 ◽  
Author(s):  
Christine L. Borgman ◽  
Jillian C. Wallis ◽  
Noel Enyedy
Keyword(s):  
Sensor Networks ◽  
Digital Libraries ◽  
Habitat Ecology
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