Metadata and Cataloging Practices

Metadata standards existing today range from very complex to very simple. Relative simplicity or complexity of metadata standards depends in large part on the resources for which they were created and the depth of description that is deemed necessary to make these resources accessible. This paper reviews the differences between metadata standards and current cataloging practices, and discusses how the various metadata standards are applied in libraries. In addressing these issues, the authors introduce definitions of key concepts of metadata and cataloging standards and provide an overview of the most common metadata schemes. The discussion of current cataloging practices includes an overview of the most commonly used cataloging practices and standards, the impact of metadata on library practice and the role of librarians related to metadata. The authors will discuss the OHIOLINK Electronic Thesis and Dissertations (ETD) as an example of how Anglo-American Cataloging Rules 2nd (AACR2) and Machine Readable Cataloging (MARC21) are used as metadata to store, describe and access this unique information resource

DRIVER Technology Watch Report

This report is part of the Discovery Workpackage (WP4) and is the third report out of four deliverables. The objective of this report is to give an overview of the latest technical developments in the world of digital repositories, digital libraries and beyond, in order to serve as theoretical and practical input for the technical DRIVER developments, especially those focused on enhanced publications. This report consists of two main parts, one part focuses on interoperability standards for enhanced publications, the other part consists of three subchapters, which give a landscape picture of current and surfacing technologies and communities crucial to DRIVER. These three subchapters contain the GRID, CRIS and LTP communities and technologies. Every chapter contains a theoretical explanation, followed by case studies and the outcomes and opportunities for DRIVER in this field

ATEE Spring Conference 2020-2021

This book collects some of the works presented at ATEE Florence Spring Conference 2020-2021. The Conference, originally planned for May 2020, was forcefully postponed due to the dramatic insurgence of the pandemic. Despite the difficulties in this period, the Organising Committee decided anyway to keep it, although online and more than one year later, not to disperse the huge work of authors, mainly teachers, who had to face one of the hardest challenges in the last decades, in a historic period where the promotion of social justice and equal opportunities – through digital technologies and beyond – is a key factor for democratic citizenship in our societies. The Organising Committee, the University of Florence, and ATEE wish to warmly thank all the authors for their commitment and understanding, which ensured the success of the Conference. We hope this book could be, not only a witness of these pandemic times, but a hopeful sign for an equal and inclusive education in all countries

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

AAPOR Report on Big Data

In recent years we have seen an increase in the amount of statistics in society describing different phenomena based on so called Big Data. The term Big Data is used for a variety of data as explained in the report, many of them characterized not just by their large volume, but also by their variety and velocity, the organic way in which they are created, and the new types of processes needed to analyze them and make inference from them. The change in the nature of the new types of data, their availability, the way in which they are collected, and disseminated are fundamental. The change constitutes a paradigm shift for survey research.There is a great potential in Big Data but there are some fundamental challenges that have to be resolved before its full potential can be realized. In this report we give examples of different types of Big Data and their potential for survey research. We also describe the Big Data process and discuss its main challenges

Education alignment

This essay reviews recent developments in embedding data management and curation skills into information technology, library and information science, and research-based postgraduate courses in various national contexts. The essay also investigates means of joining up formal education with professional development training opportunities more coherently. The potential for using professional internships as a means of improving communication and understanding between disciplines is also explored. A key aim of this essay is to identify what level of complementarity is needed across various disciplines to most effectively and efficiently support the entire data curation lifecycle

The Darwin Core extension for genebanks opens up new opportunities for sharing genebank datasets

Darwin Core (DwC) defines a standard set of terms to describe the primary biodiversity data. Primary biodiversity data are data records derived from direct observation of species occurrences in nature or describing specimens in biological collections. The Darwin Core terms can be seen as an extension to the standard Dublin Core metadata terms. The new Darwin Core extension for genebanks declares the additional terms required for describing genebank datasets, and is based on established standards from the plant genetic resources community. The Global Biodiversity Information Facility (GBIF) provides an information infrastructure for biodiversity data including a suite of software tools for data publishing, distributed data access, and the capture of biodiversity data. The Darwin Core extension for genebanks is a key component that provides access for the genebanks and the plant genetic resources community to the GBIF informatics infrastructure including the new toolkits for data exchange. This paper provides one of the first examples and guidelines for how to create extensions to the Darwin Core standard

A Study on the Use of Ontologies to Represent Collective Knowledge

The development of ontologies has become an area of considerable research interest over the past number of years. Domain ontologies are often developed to represent a shared understanding that in turn indicates cooperative effort by a user community. However, the structure and form that an ontology takes is predicated both on the approach of the developer and the cooperation of the user community. A shift has taken place in recent years from the use of highly specialised and expressive ontologies to simpler knowledge models, progressively developed by community contribution. It is within this context that this thesis investigates the use of ontologies as a means to representing collective knowledge. It investigates the impact of the community on the approach to and outcome of knowledge representation and compares the use of simple terminological ontologies with highly structured expressive ontologies in community-based narrative environments