LC Subject Headings, FAST Headings, and Apps: Diversity Can Be Problematic In the 21st Century

In this chapter, the author discusses and evaluates the effort to study and update relevant ethnic, racial, and other diverse subject headings. This discussion includes the work of the Library of Congress and software vendors. The author encourages for the technical services community to develop, use, and change subject headings to accurately reflect society

Capitalizing on Information Organization and Information Visualization for a New-Generation Catalogue

Subject searching is difficult with traditional text-based online public access library catalogues (OPACs), and the next-generation discovery layers are keyword searching and result filtering tools that offer little support for subject browsing. Next-generation OPACs ignore the rich network of relations offered by controlled subject vocabulary, which can facilitate subject browsing. A new generation of OPACs could leverage existing information-organization investments and offer online searchers a novel browsing and searching environment. This is a case study of the design and development of a virtual reality subject browsing and information retrieval tool. The functional prototype shows that the Library of Congress subject headings (LCSH) can be shaped into a useful and usable tree structure serving as a visual metaphor that contains a real world collection from the domain of science and engineering. Formative tests show that users can effectively browse the LCSH tree and carve it up based on their keyword search queries. This study uses a complex information-organization structure as a defining characteristic of an OPAC that goes beyond the standard keyword search model, toward the cutting edge of online search tools.published or submitted for publicatio

Content Analysis of Social Tags on Intersectionality for Works on Asian Women: An Exploratory Study of LibraryThing

This study explores how the social tags are employed by users of LibraryThing, a popular web 2.0 social networking site for cataloging books, to describe works on Asian women in representing themes within the context of intersectionality. Background literature in the domain of subject description of works has focused on race and gender representation within traditional controlled vocabularies such as the Library of Congress Subject Headings (LCSH). This study explores themes related to intersectionality in order to analyze how users construct meaning in their social tags. The collection of works used to search for social tags came from the Association of College and Research Libraries’ list on East Asian, South and Southeast Asian, and Middle Eastern women. A pilot study was conducted comprising of a limited sample in each of the three domains, which helped generate a framework of analysis that was used in application for the larger sample of works on Asian women. The full study analyzed 1231 social tags collected from 122 works on Asian women. Findings from this study showed that users construct a variety of intersections relating to gender and ethnicity for works on Asian women. Overall findings from this showed that gender and gender-related constructs were the most common subject of tags employed for works on Asian women. Users more often referred to geography rather than ethnicity when describing the materials on Asian women. Interesting themes to emerge involved how gender and other constructs differed among the three domains. Tags describing the majority of East Asia, such as Chinese and Japanese were most common in the East Asian dataset. Countries not considered the “majority” in South and Southeast Asia were often used, such as Indonesia and the Philippines. Themes of sexuality and religion were much more prevalent in the Middle Eastern set of tags. Social tags act as a mechanism for social commentary. Researchers have access to a plethora of constructions available to them through these social tags; such abundance of information is a valuable resource to understanding how the general populace understands intersections and constructs identity

Classifying for Diversity

This paper argues that a new approach to classification best supports and celebrates social diversity. It maintains that we should want a classification that both facilitates within-group communication and cross-group communication. This is best accomplished through a truly universal classification that classifies works in terms of authorial perspective. Strategies for classifying perspective are discussed. The paper then addresses issues of classification structure. It follows a feminist approach to classification, and shows how a web-of-relations approach can be instantiated in a classification. Finally the paper turns to classificatory process. The key argument here is that much (perhaps all) of the concern regarding the possibility that classes can be subdivided into subclasses in multiple ways (each favored by different groups or individuals) simply vanishes within a web-of-relations approach. The reason is that most of these supposed ways of subdividing a class are in fact ways of subdividing different relationships among classes

Review of the State of the Art of the Digital Curation of Research Data

The digital curation of research data is best understood in the context of the data lifecycle, and specifically in the context of data repositories. Disciplinary data centres have established requirements for deposited data, and these requirements are increasingly reflected in requirements and guidance issued by research funding bodies. The digital curation community is active in helping researchers and institutions meet these requirements, producing not only further guidance but a suite of useful standards, technologies and tools. Collectively, these provide a wealth of resources on which the ERIM Project may draw

Similarity Models in Distributional Semantics using Task Specific Information

In distributional semantics, the unsupervised learning approach has been widely used for a large number of tasks. On the other hand, supervised learning has less coverage. In this dissertation, we investigate the supervised learning approach for semantic relatedness tasks in distributional semantics. The investigation considers mainly semantic similarity and semantic classification tasks. Existing and newly-constructed datasets are used as an input for the experiments. The new datasets are constructed from thesauruses like Eurovoc. The Eurovoc thesaurus is a multilingual thesaurus maintained by the Publications Office of the European Union. The meaning of the words in the dataset is represented by using a distributional semantic approach. The distributional semantic approach collects co-occurrence information from large texts and represents the words in high-dimensional vectors. The English words are represented by using UkWaK corpus while German words are represented by using DeWaC corpus. After representing each word by the high dimensional vector, different supervised machine learning methods are used on the selected tasks. The outputs from the supervised machine learning methods are evaluated by comparing the tasks performance and accuracy with the state of the art unsupervised machine learning methods’ results. In addition, multi-relational matrix factorization is introduced as one supervised learning method in distributional semantics. This dissertation shows the multi-relational matrix factorization method as a good alternative method to integrate different sources of information of words in distributional semantics. In the dissertation, some new applications are also introduced. One of the applications is an application which analyzes a German company’s website text, and provides information about the company with a concept cloud visualization. The other applications are automatic recognition/disambiguation of the library of congress subject headings and automatic identification of synonym relations in the Dutch Parliament thesaurus applications

Theories of Informetrics and Scholarly Communication

Scientometrics have become an essential element in the practice and evaluation of science and research, including both the evaluation of individuals and national assessment exercises. Yet, researchers and practitioners in this field have lacked clear theories to guide their work. As early as 1981, then doctoral student Blaise Cronin published The need for a theory of citing - a call to arms for the fledgling scientometric community to produce foundational theories upon which the work of the field could be based. More than three decades later, the time has come to reach out the field again and ask how they have responded to this call. This book compiles the foundational theories that guide informetrics and scholarly communication research. It is a much needed compilation by leading scholars in the field that gathers together the theories that guide our understanding of authorship, citing, and impact

Theories of Informetrics and Scholarly Communication

Scientometrics have become an essential element in the practice and evaluation of science and research, including both the evaluation of individuals and national assessment exercises. Yet, researchers and practitioners in this field have lacked clear theories to guide their work. As early as 1981, then doctoral student Blaise Cronin published "The need for a theory of citing" —a call to arms for the fledgling scientometric community to produce foundational theories upon which the work of the field could be based. More than three decades later, the time has come to reach out the field again and ask how they have responded to this call. This book compiles the foundational theories that guide informetrics and scholarly communication research. It is a much needed compilation by leading scholars in the field that gathers together the theories that guide our understanding of authorship, citing, and impact