36,005 research outputs found
Searching Data: A Review of Observational Data Retrieval Practices in Selected Disciplines
A cross-disciplinary examination of the user behaviours involved in seeking
and evaluating data is surprisingly absent from the research data discussion.
This review explores the data retrieval literature to identify commonalities in
how users search for and evaluate observational research data. Two analytical
frameworks rooted in information retrieval and science technology studies are
used to identify key similarities in practices as a first step toward
developing a model describing data retrieval
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Location-based and contextual mobile learning. A STELLAR Small-Scale Study
This study starts from several inputs that the partners have collected from previous and current running research projects and a workshop organised at the STELLAR Alpine Rendevous 2010. In the study, several steps have been taken, firstly a literature review and analysis of existing systems; secondly, mobile learning experts have been involved in a concept mapping study to identify the main challenges that can be solved via mobile learning; and thirdly, an identification of educational patterns based on these examples has been done.
Out of this study the partners aim to develop an educational framework for contextual learning as a unifying approach in the field. Therefore one of our central research questions is: how can we investigate, theorise, model and support contextual learning
To share or not to share: Publication and quality assurance of research data outputs. A report commissioned by the Research Information Network
A study on current practices with respect to data creation, use, sharing and publication in eight research disciplines (systems biology, genomics, astronomy, chemical crystallography, rural economy and land use, classics, climate science and social and public health science). The study looked at data creation and care, motivations for sharing data, discovery, access and usability of datasets and quality assurance of data in each discipline
From Artifacts to Aggregations: Modeling Scientific Life Cycles on the Semantic Web
In the process of scientific research, many information objects are
generated, all of which may remain valuable indefinitely. However, artifacts
such as instrument data and associated calibration information may have little
value in isolation; their meaning is derived from their relationships to each
other. Individual artifacts are best represented as components of a life cycle
that is specific to a scientific research domain or project. Current cataloging
practices do not describe objects at a sufficient level of granularity nor do
they offer the globally persistent identifiers necessary to discover and manage
scholarly products with World Wide Web standards. The Open Archives
Initiative's Object Reuse and Exchange data model (OAI-ORE) meets these
requirements. We demonstrate a conceptual implementation of OAI-ORE to
represent the scientific life cycles of embedded networked sensor applications
in seismology and environmental sciences. By establishing relationships between
publications, data, and contextual research information, we illustrate how to
obtain a richer and more realistic view of scientific practices. That view can
facilitate new forms of scientific research and learning. Our analysis is
framed by studies of scientific practices in a large, multi-disciplinary,
multi-university science and engineering research center, the Center for
Embedded Networked Sensing (CENS).Comment: 28 pages. To appear in the Journal of the American Society for
Information Science and Technology (JASIST
Developing information architecture through records management classification techniques
Purpose – This work aims to draw attention to information retrieval philosophies and techniques allied to the records management profession, advocating a wider professional consideration of a functional approach to information management, in this instance in the development of information architecture. Design/methodology/approach – The paper draws from a hypothesis originally presented by the author that advocated a viewpoint whereby the application of records management techniques, traditionally applied to develop business classification schemes, was offered as an additional solution to organising information resources and services (within a university intranet), where earlier approaches, notably subject- and administrative-based arrangements, were found to be lacking. The hypothesis was tested via work-based action learning and is presented here as an extended case study. The paper also draws on evidence submitted to the Joint Information Systems Committee in support of the Abertay University's application for consideration for the JISC award for innovation in records and information management. Findings – The original hypothesis has been tested in the workplace. Information retrieval techniques, allied to records management (functional classification), were the main influence in the development of pre- and post-coordinate information retrieval systems to support a wider information architecture, where the subject approach was found to be lacking. Their use within the workplace has since been extended. Originality/value – The paper advocates that the development of information retrieval as a discipline should include a wider consideration of functional classification, as this alternative to the subject approach is largely ignored in mainstream IR works
Preliminary Recommendations for Shareable Metadata Best Practices
A primary goal of the IMLS Digital Collections and Content project has been to encourage sharing of metadata and participation in aggregating projects. Benefits realized through these activities include increased visibility of the collection, an environment of complimentary
resources, and enhanced discoverability of individual resources. In order for these benefits to be achieved, metadata from each repository must be interoperable with existing metadata in the aggregation. Although metadata may be quality metadata in the local context, the records must
have certain characteristics in order to be relevant in the aggregated environment.IMLS National Leadership Grant LG-02-02-0281unpublishednot peer reviewe
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