Scientific creativity is viewed as a key catalyst of scientific and technological progress yet it is an area for which there exists little understanding. This is lack of understanding is becoming increasingly problematic as scientific research and practice become ever more complex and multidisciplinary. This is because highly multidisciplinary university scientific research groups represent a rapidly emerging new era of scientific research and practice. Therefore, in order to help sustain scientific and technological progress in both universities and industry in the future, it is vital to gain an understanding of creativity in multidisciplinary scientific research. By this reasoning, this study aimed to gain a deeper understanding of scientific creativity in multidisciplinary research groups. Given the complexity of multidisciplinary scientific research, and the lack of study into scientific creativity by trained scientists, this study was undertaken from the perspective of a scientist trained in a multitude of scientific disciplines. A longitudinal, ethnographic methodology was employed in the study of three research groups. Over the course of two years, over 170 interviews were undertaken combined with many hours of observation. A Grounded Theory analytical approach facilitated the emergence of four theoretical constructs: leadership and supervision, knowledge-related concepts, individual level concepts and group level concepts. Combined, these constructs underpin the central theoretical contribution of this study: creativity in the groups was a multi level, sense-making process existing at: individual, group, faculty and institutional levels. At the individual level, creativity was a process of abstract conceptual blending. Collective engagement in the creative process relied upon distributed reasoning and restructuring. The creative sense-making processes at individual and group levels were also influenced by factors at faculty and institutional levels. Finally, the methodological and practical contributions of the study are discussed.

Reproducibility has long been a cornerstone of science, and is now becoming a key research area for e-Science. This is because it provides a way to validate, and build on, previous results. Underpinning reproducibility in e-Science is provenance, which has the potential to provide scientists with a complete understanding of data generated in eexperiments, including the services that produced and consumed it. This thesis explores the issues in exploiting provenance for reproducibility. Based on this, a reproducibility framework is designed and implemented to allow past experiments to be reproduced. Seven aspects of reproducibility are considered: 1) experiments, 2) reproducibility, 3) provenance, 4) provenance models, 5) provenance and versioning, 6) automatic transformation of provenance to support reproduction, and 7) a reproducibility taxonomy. A key to reproducibility is the provenance model: a data model that structures information about an e-experiment. A review of existing provenance systems shows that the problem caused by services being updated has been neglected. This can have a severe impact on the ability to reproduce experiments and it is therefore argued that the issue of service versioning must be addressed. Even after information on the provenance of an execution, and versioning of services, is captured there is the need for a method to transform this knowledge into a form that allows past experiments to be reproduced: that is another output of this thesis. The thesis focuses on the use of work ow as a means to represent the composition, and to execute experiments. This work explores how work ows can be automatically generated to re-execute past experiments. In order to do this, a transformation algorithm is described that maps a past experiment's execution log data into a work ow format that can be read and processed by the work- ow system. The thesis also introduces a Reproducibility Taxonomy that captures and structures the information required for reproducibility in the presence of versions and provenance.

This research sets out to develop a holistic model for Knowledge Collaboration for scientific Communities of Practice (CoP). It, inter alia, investigates appropriate methods which support Knowledge Collaboration of Scientific Community of Practice (SCoP). It also identifies the main challenges associated with supporting Knowledge Collaboration and ways of addressing specific challenges in the development of a Knowledge Collaboration Environment (KCE) within SCoP. In addition, it establishes how individuals within CoP and groups associated with CoP create new knowledge in collaboration. The necessity for scientific communities to work as CoP has significantly risen in recent years. The requirement of standard collaboration and communication tools, and appropriate methodologies to author KCEs has been an important development for the success of Distributed Knowledge Collaboration (DKC) activities of scientific CoP. The study addresses key issues and gaps found in four different areas: understanding of knowledge and Knowledge Collaboration, KCEs, tools and techniques for supporting Knowledge Collaboration, and specific requirements of scientific communities. The thesis employed a multi-methodological approach in conducting the study, which included the use of questionnaire, workshop, observations, interviews, and focus groups in obtaining data on which the study was based. SCoP refers to those who employ the 'scientific method' for seeking, interrogating, and creating processes and systems in conducting and advancing their work. Knowledge Collaboration needs of SCoP are different to the needs of CoP as members of the SCoP come from diverse backgrounds and disciplines, and their involvement is with heterogeneous work environments. A holistic Knowledge System Model (KSM) and a live prototype to establish the requirements related to the facilitation of Knowledge Collaboration within a SCoP was developed and validated. This development utilises non-intrusive technologies to provide appropriate incorporation of collaboration tools within their work environment and the potential of multiple server integration. The KSM provides the required flexibility and configurability within a prospective Knowledge System due to its ability to fulfil specific needs of the SCoP. The study recommends that members of the SCoP require Knowledge Collaboration tools that can co-exist within their work environment but operate non-intrusively within their professional work setting. Virtual Infrastructure integration provides the required functionality to overcome the challenges of creating an appropriate KCE for realising successful collaboration. The KSM facilitates the development of appropriate KCE for SCoP. There is paramount value in embracing the holistic view of Knowledge Collaboration as defined through the Knowledge Collaboration terminology stack and vast potential in utilising non-intrusive client/server technology for DKC applications. The holistic model's flexibility provides timely provision of an acceptable KCE for community collaboration.

The purpose of this study is to understand the effects of Science Research Based Competitions (SRBCs) on high school students’ responses to science. SRBCs were primarily designed to develop students’ interest in science, their motivation for science learning and their science reasoning in order to provide a platform for students to show potential for carrying out research in science. But, despite their popularity, little research has so far been undertaken to evaluate the effects of SRBCs. The study explores the effects of SRBCs on students’ responses to science from the perspective of three different groups of people: key informants (government staff, SRBC funders), teachers and students. A series of case studies was carried out in six residential schools in Malaysia. Data were gathered from four key informants, six teachers and 360 sixteen-year-old student participants, divided into six groups, in Form 4 of secondary school. Students’ responses to science were explored in a number of ways. Data on attitudes towards science were gathered through the Relevance of Science Education (ROSE) questionnaire, and the findings are compared with those of the ROSE National Survey Data for Malaysia carried out in 2004. Additional data were gathered through interviews with students and from student diaries. Students in residential schools showed more positive responses to science in a number of areas when compared with the ROSE National Survey Data. In particular, students expressed a preference for jobs which favoured recognition after accomplishing challenges, and which offered creative tasks. In contrast, they shared similar views to those found in the national survey towards school science. The study indicates that SRBCs deepen students’ interest in pursuing science and create an ability to apply knowledge which is related to it. The students reported that science is much more enjoyable when it involves autonomous learning and research activity. Students were influenced by their mentors (the teachers running the SRBCs in their schools), the types of project and the degree of external involvement. The teachers reported positive developments in their students’ science processing skills, and their knowledge and awareness of science in general. The students also developed confidence in time management, communication and handling stress along with the project. This represents a revealing insight into the views of the three main components of SRBCs; the organisers/sponsors, the practitioners and the participants.

This thesis examines the origins and development of the National Physical Laboratory, created in 1900 as the first government funded institution in Britain to undertake scientific research of intended industrial benefit. Within an expanding government scientific network the Laboratory's evolution is traced through three distinct stages, separated by the two world wars. Particular emphasis is placed upon the relations between the Laboratory, the Treasury and the Department of Scientific and Industrial Research; upon the. role of the scientific community and civil servants in determining the Laboratory's research orientation; and upon the importance of the Laboratory for the embryonic physics profession. In the light of these themes the thesis analyses a number of historical problems in the relation between science and government since 1900; changing perceptions of the NPL's function; and current debates over the role of government research establishments. It is argued that a lack of close contact with civil industry, after 1939 together with restrictions placed on the Laboratory's work by contemporary theories of technological innovation have been responsible for the NPL's present ill-defined position. In relation to the Laboratory's development and past traditions some prescriptive comments are made concerning the NPL in particular and government research establishments in general.

High-impact academic papers are not necessarily the most cited. For example, Einstein's 'Special Relativity' paper from 1905 received (and continues to receive) fewer citations from other papers than his 'Brownian Motion" paper of the same year, despite the former radically changing the course of an entire scientific discipline to a much greater extent. Similarly, 'impact' metrics using citation count alone are, it is argued, not adequate for determining the scientific influence of papers, authors or small groups of authors. Although valid, they remain controversial when used to determine influence of larger groups or journals. While the term 'impact' has become closely linked to a journal's citation-based Journal Impact Factor score, this thesis uses the term 'influence' to describe the wider effectiveness of research, combining citation and metadata analysis to allow richer calculations to be performed over large-scale document networks. As a result, more qualitative influence ratings can be determined and a broader outlook on scientific disciplines can be produced. These ratings are best applied using an ontology-based data source, allowing more efficient inference than under a traditional RDBMS system, and allowing easier integration between heterogeneous data sources. These metrics, termed 'Semantic Bibliometrics' or 'Semiometrics', can be applied at a variety of levels of granularity, allowing a compositional framework for impact and influence analysis. This thesis describes the process of data preparation, systems architecture, metric value and data integration for such a system, introducing novel approaches at all four stages, thereby creating a working semiometrics system for determining influence at different semantic levels of granularity.

Citizen science, or ‘public participation in scientific research’, can be described as research conducted, in whole or in part, by amateur or nonprofessional participants often through crowd-sourcing techniques. The advance of modern day internet technology that has made the world a more connected place has resulted in a surge of citizen science projects, especially online platforms which allow volunteers to take part in research in both an asynchronous and geographically abstract manner. Due to this increased interest, citizen science is becoming a distinct field of research in its own right beyond the original scientific problems it was devised to address. Although some of this research has considered interface HCI and functionality, there has been relatively little attention paid specifically to human factors issues. Through this work we attempt to address this shortfall, by considering citizen science as a form of ‘work’. Due to its similarities in terms of repetition with production lines of the early 20th century and more recently on-screen visual inspection tasks, some of the many decades of ergonomics research in this field are applied specifically to the virtual citizen science arena. We make a first step in considering how virtual citizen science systems can be better designed for the needs of the volunteer, exploring how manipulating task flow affects both the quality of information collected, and the volunteers’ experience of using the interface. A hierarchical task analysis of 12 Zooniverse projects revealed that the types of tasks, judgements and the way they are presented to the volunteer varies greatly, independent of the science discipline involved. Furthermore, through differing designs of the Zooniverse’s ‘Planet Four: Craters’ platform, it was shown that task workflow design factors such as autonomy, variety, task type and volunteer judgement required can influence the amount of data collected, the accuracy of this data and both volunteer engagement and motivation. Simpler tasks with fewer volunteer judgements required resulted in a significantly greater volume of data collected, however accuracy is affected with an increase of false-positive classifications. Volunteers reported a preference for greater autonomy and task variety, a stance reflected in the number of times they visited and returned to the platform, however this also significantly reduced the accuracy of classifications – both in terms of inter-participant agreement and expert judgement comparison. The interplay of task workflow factors and their effect has been shown to be a complex affair. Through the empirical data collected, a model has been derived predicting the influence of different task workflow configurations on classification numbers over time since a platforms’ launch. It demonstrates that when considering task workflow design, developers of future citizen science platforms will need to perform a balancing act. The importance of user engagement, the data needs of the science case and the resources that can be committed both in terms of time and data reduction will need to be weighed, and balanced with the realistic public reach and promotion the science case can be predicted to generate.

This thesis takes a theoretical framework constructed for transdisciplinary research within different natural science disciplines and investigates what kind of new knowledge is produced when this framework is applied to projects at the interface of art and natural science. The main case study is “Sauti ya Wakulima – The Voice of the Farmers”, which involves collaboration with another intervention artist, and with natural scientists and farmers. This is a collaborative knowledge project with small-scale urban as well as rural farmers in Tanzania who have created an online community archive of their farming practices by using mobile phones to upload images and sounds onto a website. The research uses an open-ended participatory methodology that gives the participants as much creative agency as possible within the given power structures and practical and technical parameters. A second work examined is the Climate Hope Garden, an installation by the author in collaboration with ecologists and climate scientists at the Swiss Federal Institute of Technology, Zürich (ETHZ). The installation consisted of a garden grown in climate-controlled chambers based on the climatic conditions proposed by IPCC climate scenarios. The project aimed to enact these scenarios on a spatial and temporal scale to which visitors could relate. Transdisciplinary research has become a key reference point in funding proposals. Despite many references in the literature, and calls for research involving both the natural sciences and humanities to solve complex world problems such as adaptation to climate change, there seems to be little consensus about exactly what kind of knowledge might be produced from such projects, and how transdisciplinary research proposals might be evaluated, especially those at the interface of art and the natural sciences. Several theoretical frameworks have been suggested for designing transdisciplinary research between and within scientific disciplines, or between the natural and social sciences and humanities. The present study applies the framework proposed by Christian Pohl and Gertrude Hirsch Hadorn (2007) to a real-world transdisciplinary art-science project in a development context in order to examine the balance between the collective, locally embodied experience and the nomothetic knowledge that arises from it. This thesis found that transdisciplinarity is a different question from that of types of knowledge on the nomothetic-idiographic scale. Transdisciplinarity is a pragmatic question of definitions and inherited boundaries of disciplines. The framework categories do not differentiate between nomothetic and idiographic, just to which part of the problem-solving puzzle they fit. This is perfectly valid for goal-oriented, problem-solving research and can be applied to art-science research, but there are other ways of describing this work, such as using a philosophical description of the knowing process which comes closer to encompassing the richness of the knowledge produced. It is in this sense that the new type of knowledge generated by the transdisciplinary projects required an expansion of the given theoretical framework.

The thesis presents a reformative criticism of science funding by peer review. The criticism is based on epistemological scepticism, regarding the ability of scientific peers, or any other agent, to have access to sufficient information regarding the potential of proposed projects at the time of funding. The scepticism is based on the complexity of factors contributing to the merit of scientific projects, and the rate at which the parameters of this complex system change their values. By constructing models of different science funding mechanisms, a construction supported by historical evidence, computational simulations show that in a significant subset of cases it would be better to select research projects by a lottery mechanism than by selection based on peer review. This last result is used to create a template for an alternative funding mechanism that combines the merits of peer review with the benefits of random allocation, while noting that this alternative is not so far removed from current practice as may first appear.

This study examines the ways in which public participation in the production of scientific knowledge, influences the practices and expertise of the scientists in Galaxy Zoo, an online Big Data citizen science initiative. The need for citizen science in the field of Astronomy arose in response to the challenges of rapid advances in data gathering technologies, which demanded pattern recognition capabilities that were too advanced for existing computer algorithms. To address these challenges, Galaxy Zoo scientists recruited volunteers through their online website, a strategy which proved to be remarkably reliable and efficient. In doing so, they opened up the boundaries of scientific processes to the public. This shift has led to important outcomes in terms of the scientific discovery of new Astronomical objects; the creation and refining of scientific practices; and the development of new forms of expertise among key actors while they continue to pursue their scientific goals. This thesis attempts to answer the over-arching research question: How is citizen science shaping the practices and expertise of Galaxy Zoo scientists? The emergence of new practices and development of the expertise in the domain of managing citizen science projects were observed through following the work of the Galaxy Zoo scientists and in particular the Principal Investigator and the project's Technical Lead, from February 2010 to April 2013. A broadly ethnographic approach was taken, which allowed the study to be sensitive to the uncertainty and unprecedented events that characterised the development of Galaxy Zoo as a pioneering project in the field of data-intensive citizen science. Unstructured interviewing was the major source of data on the work of the PI and TL; while the communication between these participants, the broader Science Team and their inter-institutional collaborators was captured through analyses of the team emailing list, their official blog and their social media posts. The process of data analysis was informed by an initial conceptualisation of Galaxy Zoo as a knowledge production system and the concept of knowledge object (Knorr-Cetina,1999), as an unfolding epistemic entity, became a primary analytical tool. Since the direction and future of Galaxy Zoo involved addressing new challenges, the study demanded periodic recursive analysis of the conceptual framework and the knowledge objects of both Galaxy Zoo and the present examination of its development. The key findings were as follows. The involvement of public volunteers shaped the practices of the Science Team, while they pursued robust scientific outcomes. Changes included: negotiating collaborations; designing the classification tasks for the volunteers; re-examining data reduction methods and data release policies; disseminating results; creating new epistemic communities; and science communication. In addition, new kinds of expertise involved in running Galaxy Zoo were identified. The relational and adaptive aspects of expertise were seen as important. It was therefore proposed that the development of the expertise in running citizen science projects should be recognised as a domain-expertise in its own right. In Galaxy Zoo, the development of the expertise could be attributed to a combined understanding of: the design principles of doing good science; innovation in methods; and creating a dialogic space for scientists and volunteers. The empirical and theoretical implications of this study therefore lie in (i) identifying emergent practices in citizen science while prioritising scientific knowledge production and (ii) a re-examination of expertise for science in the emerging context of data-intensive science.