The aim of the research was to identify novel similarity measures for similarity-based virtual screening. Similarity-based virtual screening is at the lead identification stage of drug discovery process and normally requires explorations in large scale databases. Thus, the improvement of accuracy of the methods employed could result in a significant enhancement of effectiveness of the whole process of drug discovery. There are three key components involved in similarity-based virtual screening, i.e., structural representations, similarity coefficients and weighting schemes. The research focuses on the choice of similarity coefficient and weighting scheme. Three investigations have been conducted: investigation of interactions between weighting schemes and similarity coefficients; comparison of binary coefficients and evaluation of similarity coefficients using weighted fingerprints. Four chemical databases were used, i.e., MDDR, WOMBAT, MUV and ChEMBL. The results show that there are strong, and often quite subtle, interactions between the similarity coefficient and the weighting scheme comprising a similarity measure. They also exhibit that, although the Tanimoto coefficient remains one of the most practical coefficients for use in similarity-based virtual screening on binary representations, it may not be the coefficient of choice when weighting schemes are applied. In addition, other coefficients were identified as favorable for similarity-based virtual screening when weighted fingerprints are available. The findings indicate that the study of the combinations of weighting schemes and similarity coefficients could make a significant contribution to similarity-based virtual screening.

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The aim of this thesis is to develop a holistic framework that depicts key categories of influences that shape individual perceptions of knowledge sharing within an organisational setting. This aim stems from a systematic literature review that indicates that despite the large volume of literature in regards to knowledge sharing, the field has not yet arrived at a consensus as to the key categories of influences, defined at a high level, that shape individuals’ knowledge sharing perceptions. In order to uncover the key categories of influences, an exploratory and qualitative case study strategy was executed. Empirical data were gathered from a total of 24 interviewees that were based in four different country branches (i.e. China, the Netherlands, the UK and the US) of a single IT services organisation. Using constant comparison, findings point towards a holistic framework that depicts four key categories of influences that shape knowledge sharing from an individual perspective. The first key influence revolves around institutions which act as a united entity on individual perceptions of knowledge sharing. The second key influence fundamentally different in nature concentrates on relations between individuals sharing knowledge. The third key influence focuses on the individuals themselves (called sharers) and how their attitudes and characteristics can shape their knowledge sharing perceptions. The fourth and final key influence centres on knowledge itself and how this can shape individual perceptions of knowledge sharing. In addition, findings suggest that the four key influences not only shape knowledge sharing independently but that all four key influences are intertwined and together form a holistic framework. Combined, these two sets of findings indicate that knowledge sharing from an individual-level perspective is a more complex phenomenon than currently portrayed in the literature, which has focused on some of the key influences or depicted some of the interrelationships. Yet to better understand the knowledge sharing phenomenon from an individual perspective all four key influences, each being fundamentally different in nature, and their relationships should be taken into account.

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Microblogging tools, such as Twitter and Yammer, are examples of social media that allow users to share messages about personal activities, share opinions and to receive quick notifications. They have become very popular, for both personal and professional pursuits, with millions of users worldwide. Some authors have claimed that social media can radically transform organisations. However, there is a lack of empirical research that evaluates that claim. Not much is known about internal organisational uses of microblogs, in comparison to their public uses, for example for marketing. Also, less research has been devoted to microblogging adoption and use in small and medium enterprises (SMEs), organisation with less than 250 employees. Yet, SMEs are recognised to be key to the economy. Accordingly, this thesis investigates the uses and perceptions of risks of microblogging in UK based SMEs. The research adopts a qualitative, interpretive methodology because of the intention to explore how participants understand microblogging themselves. 21 semi-structured, face-to-face and phone interviews were conducted with managers, directors and employees in SMEs in IT/software, Sports and Consultancy organisations based in South Yorkshire, UK. A thematic approach was taken to analysing the interview data. Most organisations in the study had adopted microblogs by a process of trial and error. Microblogging was mostly used by the manager or director. Smaller organisations did not make much use of the platforms for direct advertising i.e. selling products to others through the tools. The participants focused more on other types of uses, such as internal communication, knowledge and sharing data, as well as customer relations. Internally, microblogs such as Yammer was chiefly used by individuals to collaborate remotely with their co-workers and to ask or respond to questions. Externally, Twitter was mainly used to enable users to exchange information such as details about events, to communicate more with customers and potential customers and to build relationships with clients. A visual representation was developed to illustrate the uses of microblogging in SMEs. The participants in the study particularly valued microblogging for its limited functionality, its cost effectiveness and because it could be used via mobile phones. Perceptions of risk emerged as a stronger theme in the analysis than expected. Most participants perceived microblogs to be highly risky i.e. to expose the organisation and employees to danger, though not too risky to use. The commonest type of risk was seen to be the danger of damaging the reputation of the business. Leaking confidential information to the public, negative media coverage, too much noise, misleading information, computer security, bullying, loss of personal privacy and losing valuable information were also identified as risks. Most organisations took specific action to manage and mitigate such perceived risks. The majority of participants talked about controlling what types of information should be shared on the tools. They had a policy on appropriate content. Other types of actions mentioned were controlling who should engage with microblogging, training, having review procedures and complaint procedures to deal with the consequences of mistakes such as providing people with incorrect information. To illustrate such feelings around risks, two visual representations were developed. This research is the first in-depth study about the uses of microblogging in UK based SMEs. It was found that microblogging did not radically transform organisations. It was seen as a useful form of communication for SMEs, but no more than that. The limited financial resources and professional expertise that SMEs have, was key to how they adopted the technology. As regards practical implications, something could be done to address the trial and error approach to using microblogs found to be typical of smaller organisations. For example, managers could be given training courses and guidance on how to best adopt and use microblogging. To improve management of risks, more concrete expert advice could be developed and organisations would benefit from sharing of model policies.

This collaborative research project, supported by the British Library, used a case study of the library collection for social enterprise to develop a conceptual approach to the library collection in the digital world, exploring stakeholder perceptions of collections, terminology and collection development and management processes. A mixed-methods multiphase case study design was used to address the research questions. Three strands of data collection are described: a case study of the British Library’s collections and content for social enterprise, searches for relevant material on 88 publicly accessible UK library catalogues, and an exploratory sequential study involving stakeholder interviews (19 interviews with 18 people) followed by two surveys of a larger stakeholder population (149 completed responses in total). Findings from each strand are described and three core concepts of collection are identified: “collection-as-thing”, “collection-as-process” and “collection-as-access”. Conventional views of library collections may tend to focus more on the idea of “collection -as-thing”; this research emphasises the importance of taking a more dynamic view of collection. Three models of collection are described: a revised collection development hierarchy which suggests links to different levels of strategic management; a model of interrelationships between the three concepts of collection; and a model which examines how collection adds value to content by providing context. This research demonstrates that the concept of collection remains highly relevant in the digital world, although the onus is on libraries to embrace all dimensions of these three concepts of collection if they wish to add maximum value to the content they identify, select, hold, make accessible and to which they connect.

This thesis reports the process and findings of a case study research which aimed at understanding how E-learning implementation was undertaken in higher education institutions in the context of Vietnamese universities. A case study research using semi-structured interviews was employed to generate qualitative data from three cases of E-learning implementation theoretically chosen from Vietnamese universities. A new configuration analysis approach was created to analyze and interpret the problematic issues embedded in the context of organization, technology and teaching and learning influencing the three sequenced stage process of implementation. The research identified influential factors of contexts which are characterised by the organization, technology and teaching and learning shape of the E-learning implementation process in pre-implementation, implementation and post-implementation stages. The findings illustrate that E-learning implementation was driven and constrained by contextual factors interacting and interplaying with a process of implementation. Based on the findings, an implementation framework for continuous E-learning implementation as part of blended learning in Vietnamese universities was developed. This implementation framework proposes a way in which E-learning implementation will be reached at an equilibrium point, where a sustainability of implementation will be presented. The study contributes to the body of E-learning implementation research that is shaping and incorporating contextual factors into the implementation process. Methodologically, it provides a configuration analysis tool which is tailored to the purpose of analysing data, interpreting individual cases and doing cross-case analysis through a qualitative case study research method. Theoretically, it provides a basis for practices in implementing E-learning, and offers useful suggestions for educators in implementing a formal blended learning system within the higher education sector. The framework of E-learning implementation and associated suggestions presented in this study are expected to assist universities and governments to play a more active role in the implementation of e-learning education to improve the quality of training and institutional performance. The findings are expected to contribute to sustaining E-learning implementation by better planning, organizing, implementing, operating and monitoring regarding institutional policies and practices, including investment in learning technologies, infrastructure, training and development and support services for e-learning.

This project, undertaken in collaboration with OCLC, aimed to investigate the potential role of recommendations within WorldCat, the publicly accessible union catalogue of libraries participating in the OCLC global cooperative. The goal of the project was a set of conceptual design guidelines for a WorldCat.org recommender system, based on a comprehensive understanding of the systems users and their needs. Taking a mixed-methods approach, the investigation consisted of four phases. Phase one consisted of twenty-one focus groups with key user goups held in three locations; the UK, the US, and Australia and New Zealand. Phase 2 consisted of a pop-up survey implemented on WorldCat.org, and gathered 2,918 responses. Phase three represented an analysis of two months of WorldCat.org transaction log data, consisting of over 15,000,000 sessions. Phase four was a lab based user study investigating and comparing the use of WorldCat.org with Amazon. Findings from each strand were integrated, and the key themes to emerge from the research are discussed. Different methods of classifying the WorldCat.org user population are presented, along with a taxonomy of work- and search-tasks. Key perspectives on the utility of a recommender system are considered, along with a reflection on how the information search behaviour exhibited by users interacting with recommendations while undertaking typical catalogue tasks can be interpreted. Based on the enriched perspective of the system, and the role of recommendation in the catalogue, a series of conceptual design specifications are presented for the development of a WorldCat.org recommender system.

An orphan drug is a medicinal product intended for the treatment of a rare disease that affects only a small number of patients, e.g., five in ten thousand. According to the current European orphan drug legislation, the European Union shall not, for a period of ten years, accept another orphan medicinal product for the same therapeutic indication, in respect of a similar medicinal product. Thus far, the European Medicines Agency has used human judgments of similarity when assessing new medicines for rare diseases. The project reported here seeks to develop quantitative methods for this purpose. The project began with an analysis of the correlation between human and computed judgments of similarity for 100 pairs of molecules chosen from the Drug Bank 3.0 database. The human similarity assessments for these pairs of molecules were obtained from a total of 143 experts from Europe, Asia and the US, with the experts being asked to state whether each pair was, or was not, similar. The percentage of the experts judging a pair to be similar was then compared to the Tanimoto coefficient computed using a range of different types of descriptors (1D, 2D and 3D), with the aim of identifying those descriptors that correlated most closely with the human judgments. The following types of fingerprint were studied: ECFP4, ECFC4, Daylight, Unity, BCI, MDL as implemented in the Pipeline Pilot system; and CDK Extended, CDK Standard, Estate, PubChem, MACCS, Morgan, Feat Morgan, Atom Pair, Torsion, RDKit, Avalon, Layers, FP:TGD and FP:TGT as implemented in the KNIME system. The 3D fingerprints studied were the following: FP:TAD and FP:TAT as implemented in the KNIME protocol. 1D molecular property descriptors were also studied but these proved to be of only limited effectiveness for this application. Logistic regression models were developed for each type of descriptor, relating the Tanimoto similarity for a pair of molecules computed with the probability of the human experts regarding that pair as being similar. The resulting regression models were then validated using a separate test-set containing 100 pairs of molecules that had previously been evaluated by the European Medicines Agency in the context of the authorisation of medicines for rare diseases. The best models were able to reproduce over 95% of the human judgments. This success rate was increased to 98-99% using a simple data fusion approach in which a pair of molecules is classified as similar (or non-similar) when three or more of the individual fingerprints are in agreement. The results obtained here suggest that computed Tanimoto values based on 2D descriptors could provide a useful source of information when assessing new active substances that are being proposed for the treatment of rare diseases.