4,187 research outputs found
A Conceptual Model for Scholarly Research Activity
This paper presents a conceptual model for scholarly research
activity, developed as part of the conceptual modelling work
within the ???Preparing DARIAH??? European e-Infrastructures
project. It is inspired by cultural-historical activity theory,
and is expressed in terms of the CIDOC Conceptual Reference
Model, extending its notion of activity so as to also
account, apart from historical practice, for scholarly research
planning. It is intended as a framework for structuring and
analyzing the results of empirical research on scholarly practice
and information requirements, encompassing the full
research lifecycle of information work and involving both
primary evidence and scholarly objects; also, as a framework
for producing clear and pertinent information requirements,
and specifications of digital infrastructures, tools and services
for scholarly research. We plan to use the model to tag interview
transcripts from an empirical study on scholarly information
work, and thus validate its soundness and fitness for
purpose
Ariadne's Thread - Interactive Navigation in a World of Networked Information
This work-in-progress paper introduces an interface for the interactive
visual exploration of the context of queries using the ArticleFirst database, a
product of OCLC. We describe a workflow which allows the user to browse live
entities associated with 65 million articles. In the on-line interface, each
query leads to a specific network representation of the most prevailing
entities: topics (words), authors, journals and Dewey decimal classes linked to
the set of terms in the query. This network represents the context of a query.
Each of the network nodes is clickable: by clicking through, a user traverses a
large space of articles along dimensions of authors, journals, Dewey classes
and words simultaneously. We present different use cases of such an interface.
This paper provides a link between the quest for maps of science and on-going
debates in HCI about the use of interactive information visualisation to
empower users in their search.Comment: CHI'15 Extended Abstracts, April 18-23, 2015, Seoul, Republic of
Korea. ACM 978-1-4503-3146-3/15/0
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Toward a Conceptual Framework for Scholarly Information Seeking
This article reviews literature on information seeking theories and discusses the relevance of those theories to the information seeking habits of faculty with research expectations. A new model is constructed to depict the factors influencing scholarly information needs. The model incorporates career advancement factors, the influence of discovery tools, and the influence of interpersonal networks. Theoretical frameworks from T.D. Wilson and James Krikelas play important roles in building the model to describe scholarly information needs. This model can be of use to librarians, discovery tool designers, and university administrators supporting the information seeking, research, and teaching of faculty
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Seshat: The Global History Databank
The vast amount of knowledge about past human societies has not been systematically organized and, therefore, remains inaccessible for empirically testing theories about cultural evolution and historical dynamics. For example, what evolutionary mechanisms were involved in the transition from the small-scale, uncentralized societies, in which humans lived 10,000 years ago, to the large-scale societies with an extensive division of labor, great differentials in wealth and power, and elaborate governance structures of today? Why do modern states sometimes fail to meet the basic needs of their populations? Why do economies decline, or fail to grow? In this article, we describe the structure and uses of a massive databank of historical and archaeological information, Seshat: The Global History Databank. The data that we are currently entering in Seshat will allow us and others to test theories explaining how modern societies evolved from ancestral ones, and why modern societies vary so much in their capacity to satisfy their members’ basic human needsPeer reviewedFinal Published versio
Toward a Theoretical Model for Scientific Information Seeking
According to the literature reviewed in this article, faculty members who are involved in research have a variety of information-seeking behaviours. Scholarly information needs are represented in a new way by a new model. Career advancement, discovery tools, and interpersonal networks all play a role in the model\u27s design. TD Wilson and James Krikelas\u27 theoretical frameworks play a significant role in constructing the model for describing scientific information needs. University administrators and librarians can use this model to help faculty with their information-seeking, research, and teaching endeavors
Electronic resource discovery systems: from user behaviour to design.
Information seeking is a central part of academic development for both students and researchers. However, this is often hindered by complex and highly complicated electronic resource discovery systems. One approach to improving these resources is to understand the difficulties and likely causes of problems when using current systems and how people develop their searching, retrieval and storage strategies. These might provide useful information about the requirements for future design. In this paper we present our findings from UBiRD, a project investigating user search behaviour in electronic resource discovery systems based on a qualitative study of 34 users from three UK universities. We then describe how the information gathered during the study helped inform the design of INVISQUE, a novel non-conventional interface for searching and querying on-line scholarly information. In addition, the theories and design principles used during the INVISQUE design are discussed
The Semantic Reader Project: Augmenting Scholarly Documents through AI-Powered Interactive Reading Interfaces
Scholarly publications are key to the transfer of knowledge from scholars to
others. However, research papers are information-dense, and as the volume of
the scientific literature grows, the need for new technology to support the
reading process grows. In contrast to the process of finding papers, which has
been transformed by Internet technology, the experience of reading research
papers has changed little in decades. The PDF format for sharing research
papers is widely used due to its portability, but it has significant downsides
including: static content, poor accessibility for low-vision readers, and
difficulty reading on mobile devices. This paper explores the question "Can
recent advances in AI and HCI power intelligent, interactive, and accessible
reading interfaces -- even for legacy PDFs?" We describe the Semantic Reader
Project, a collaborative effort across multiple institutions to explore
automatic creation of dynamic reading interfaces for research papers. Through
this project, we've developed ten research prototype interfaces and conducted
usability studies with more than 300 participants and real-world users showing
improved reading experiences for scholars. We've also released a production
reading interface for research papers that will incorporate the best features
as they mature. We structure this paper around challenges scholars and the
public face when reading research papers -- Discovery, Efficiency,
Comprehension, Synthesis, and Accessibility -- and present an overview of our
progress and remaining open challenges
An improved bees algorithm local search mechanism for numerical dataset
Bees Algorithm (BA), a heuristic optimization procedure, represents one of the fundamental search techniques is based on the food foraging activities of bees. This algorithm performs a kind of exploitative neighbourhoods search combined with random explorative search. However, the main issue of BA is that it requires long computational time as well as numerous computational processes to obtain a good solution, especially in more complicated issues. This approach does not guarantee any
optimum solutions for the problem mainly because of lack of accuracy. To solve this
issue, the local search in the BA is investigated by Simple swap, 2-Opt and 3-Opt were proposed as Massudi methods for Bees Algorithm Feature Selection (BAFS). In this
study, the proposed extension methods is 4-Opt as search neighbourhood is presented. This proposal was implemented and comprehensively compares and analyse their performances with respect to accuracy and time. Furthermore, in this study the feature selection algorithm is implemented and tested using most popular dataset from Machine Learning Repository (UCI). The obtained results from experimental work confirmed that the proposed extension of the search neighbourhood including 4-Opt approach has provided better accuracy with suitable time than the Massudi methods
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