Scholarly output: print and digital - in teaching and research

Purpose – The purpose of this paper is to report the outcomes of a Joint Information Systems Committee (JISC)-sponsored study to determine the current state and trends in different forms of scholarly output used in teaching and research; and the nature and extent of problems associated with their use. Design/methodology/approach – A total of 60 UK HE institutions were chosen at random and a selection of departments within these was contacted. An online questionnaire was distributed to the selected departments; resulting in responses from 304 academics across a broad range of subjects and institution types. Findings – The study showed that printed output was still the preferred option in both teaching and research, although electronic journals now have a well-established presence. Web-based material is increasingly provided in teaching and used in research but this includes primarily traditional tools such as reading lists and links to scholarly resources. Some content creation was evident. Use of web 2.0 was not extensive, although respondents were making use of Institutional Learning Environments. Academics were aware of Intellectual Property Rights (IPR) issues but not always clear about their responsibilities in this area. Research limitations/implications – The study revealed an essentially conservative approach to the developments in digital information. This may have been due to the sample size which was relatively small, and the age profile which clustered around the 45-65 years range. In the case of research the influence of the Research Assessment Exercise (RAE) was clear. Originality/value – No equivalent study has been reported on the transition between traditional and new forms of scholarly output used in teaching and research. In this fast developing area this research provides a benchmark for future studies

Effect of direct-to-consumer genetic tests on health behaviour and anxiety: a survey of consumers and potential consumers

Direct-to-consumer (DTC) genetic tests can be purchased over the internet. Some companies claim to provide relative genetic risks for various diseases and thus encourage healthy behaviour. There are concerns that exposure to such information may actually discourage healthy behaviour or increase health anxiety. An online survey was conducted (n = 275). Respondents were composed of individuals who had purchased a DTC genetic test and received their results (consumers, n = 189), as well as individuals who were either awaiting test results or considering purchasing a test (potential consumers, n = 86). Consumers were asked if their health behaviour or health anxiety had changed after receiving their results. Respondents’ current health behaviour and health anxiety were queried and compared. In total, 27.3 % of consumers claimed a change in health behaviour, all either positive or neutral, with no reported cessation of any existing health behaviour. A change in health anxiety was claimed by 24.6 % of consumers, 85.3 % of which were a reduction. Consumers had significantly better health behaviour scores than potential consumers (p = 0.02), with no significant difference in health anxiety. This study points towards an association between receipt of DTC genetic test results and increased adoption of healthy behaviours for a minority of consumers based on self-report, with more mixed results in relation to health anxiety

Identification of tacit knowledge associated with experience: a Chinese software industry study

This paper reports on a research project that aimed at identifying the professional and personal experience from individuals in the SMEs in the Software (SW) industry sector in China. This study employed an inductive qualitative approach based on a single case study and grounded theory (GT) data analysis. The SW company is a SME that specialises in multimedia SW research and development and is located in Xiamen City (Fujian Province, South of China). Six participants, selected on the basis of their role in SW design and development, were interviewed using a semi‐structured interview script. These in‐depth interviews ranged from 100 to 120 minutes in length. After completing the open coding of the six interview transcripts, the researcher obtained 121 codes and 215 quotations from the interview data. These codes were grouped and organized into a category hierarchy that included 6 main structured categories as the result of axial coding. The results of the study enabled the development of a taxonomy and classification of tacit knowledge related to experience in the different stages of the SW development process. The study also showed that each identified category of tacit knowledge is not necessarily confined to one specific SW development stage or even to a specific role in the process. This emergent theory challenges traditional perceptions that each stage requires very precise types of skills, experience and even types of individuals

Integration of distributed terminology resources to facilitate subject cross-browsing for library portal systems

Purpose – The paper aims to develop a prototype middleware framework between different terminology resources in order to provide a subject cross-browsing service for library portal systems. Design/methodology/approach – Nine terminology experts were interviewed to collect appropriate knowledge to support the development of a theoretical framework for the research. Based on this, a simplified software-based prototype system was constructed incorporating the knowledge acquired. The prototype involved mappings between the computer science schedule of the Dewey Decimal Classification (which acted as a spine) and two controlled vocabularies, UKAT and ACM Computing Classification. Subsequently, six further experts in the field were invited to evaluate the prototype system and provide feedback to improve the framework. Findings – The major findings showed that, given the large variety of terminology resources distributed throughout the web, the proposed middleware service is essential to integrate technically and semantically the different terminology resources in order to facilitate subject cross-browsing. A set of recommendations are also made, outlining the important approaches and features that support such a cross-browsing middleware service. Originality/value – Cross-browsing features are lacking in current library portal meta-search systems. Users are therefore deprived of this valuable retrieval provision. This research investigated the case for such a system and developed a prototype to fill this gap

National security and social media monitoring: a presentation of the emotive and related systems

Today social media streams, such as Twitter, represent vast amounts of 'real-time' daily streaming data. Topics on these streams cover every range of human communication, ranging from banal banter, to serious reactions to events and information sharing regarding any imaginable product, item or entity. It has now become the norm for publicly visible events to break news over social media streams first, and only then followed by main stream media picking up on the news. It has been suggested in literature that social-media are a valid, valuable and effective real-time tool for gauging public subjective reactions to events and entities. Due to the vast big-data that is generated on a daily basis on social media streams, monitoring and gauging public reactions has to be automated and most of all scalable - i.e. human, expert monitoring is generally unfeasible. In this paper the EMOTIVE system, a project funded jointly by the DSTL (Defence Science and Technology Laboratory) and EPSRC, which focuses on monitoring fine-grained emotional responses relating to events of national security importance, will be presented. Similar systems for monitoring national security events are also presented and the primary traits of such national security social media monitoring systems are introduced and discussed

Emotive ontology: extracting fine-grained emotions from terse, informal messages

With the uptake of social media, such as Facebook and Twitter, there is now a vast amount of new user generated content on a daily basis, much of it in the form of short, informal free-form text. Businesses, institutions, governments and law enforcement organisations are now actively seeking ways to monitor and more generally analyse public response to various events, products and services. Our primary aim in this project was the development of an approach for capturing a wide and comprehensive range of emotions from sparse, text based messages in social-media, such as Twitter, to help monitor emotional responses to events. Prior work has focused mostly on negative / positive sentiment classification tasks, and although numerous approaches employ highly elaborate and effective techniques with some success, the sentiment or emotion granularity is generally limiting and arguably not always most appropriate for real-world problems. In this paper we employ an ontology engineering approach to the problem of fine-grained emotion detection in sparse messages. Messages are also processed using a custom NLP pipeline, which is appropriate for the sparse and informal nature of text encountered on micro-blogs. Our approach detects a range of eight high-level emotions; anger, confusion, disgust, fear, happiness, sadness, shame and surprise. We report f-measures (recall and precision) and compare our approach to two related approaches from recent literature. © 2013 IADIS

Emotive ontology: extracting fine-grained emotions from terse, informal messages

A range of new biphenylazepinium salt organocatalysts effective for asymmetric epoxidation has been developed incorporating an additional substituted oxazolidine ring, and providing improved enantiocontrol in alkene epoxidation over the parent structure. Starting from enantiomerically pure amino-alcohols, tetracyclic iminium salts were obtained as single diastereoisomers through an atroposelective oxazolidine formation

Impact of library discovery technologies: a report for UKSG

The primary objective of this research commissioned by UKSG, with JISC support, was to provide an evaluation of the impact of library discovery technologies on the usage of academic content. [Continues.

The role of visualisations in social media monitoring systems

Social-Media streams are constantly supplying vast volumes of real-time User Generated Content through platforms such as Twitter, Facebook, and Instagram, which makes it a challenge to monitor and understand. Understanding social conversations has now become a major interest for businesses, PR and advertising agencies, as well as law enforcement and government bodies. Monitoring of social-media allows us to observe large numbers of spontaneous, real-time interactions and varied expression of opinion, often fleeting and private. However, human, expert monitoring is generally unfeasible due to the high volumes of data. This has been a major reason for recent research and development work looking at automated social-media monitoring systems. Such systems often keep the human "out of the loop" as an NLP (Natural Language Processing) pipeline and other data-mining algorithms deal with analysing and extracting features and meaning from the data. This is plagued by a variety of problems, mostly due to the heterogenic, inconsistent and context-poor nature of social-media data, where as a result the accuracy and efficacy of such systems suffers. Nevertheless, automated social-media monitoring systems provide for a scalable, streamlined and often efficient way of dealing with big-data streams. The integration of processing outputs from automated systems and feedback to human experts is a challenge and deserves to be addressed in research literature. This paper will establish the role of the human in the social-media monitoring loop, based on prior systems work in this area. The focus of our investigation will be on use of visualisations for effective feedback to human experts. A specific, custom built system’s case-study in a social-media monitoring scenario will be considered and suggestions on how to bring back the human “into the loop” will be provided. Also some related ethical questions will be briefly considered. It is hoped that this work will inform and provide valuable insight to help improve development of automated social-media monitoring systems

National Security and Social Media Monitoring: A Presentation of the EMOTIVE and Related Systems

Today social media streams, such as Twitter, represent vast amounts of 'real-time' daily streaming data. Topics on these streams cover every range of human communication, ranging from banal banter, to serious reactions to events and information sharing regarding any imaginable product, item or entity. It has now become the norm for publicly visible events to break news over social media streams first, and only then followed by main stream media picking up on the news. It has been suggested in literature that social-media are a valid, valuable and effective real-time tool for gauging public subjective reactions to events and entities. Due to the vast big-data that is generated on a daily basis on social media streams, monitoring and gauging public reactions has to be automated and most of all scalable - i.e. human, expert monitoring is generally unfeasible. In this paper the EMOTIVE system, a project funded jointly by the DSTL (Defence Science and Technology Laboratory) and EPSRC, which focuses on monitoring fine-grained emotional responses relating to events of national security importance, will be presented. Similar systems for monitoring national security events are also presented and the primary traits of such national security social media monitoring systems are introduced and discussed