Mapping the structure of science through clustering in citation networks : granularity, labeling and visualization

The science system is large, and millions of research publications are published each year. Within the field of scientometrics, the features and characteristics of this system are studied using quantitative methods. Research publications constitute a rich source of information about the science system and a means to model and study science on a large scale. The classification of research publications into fields is essential to answer many questions about the features and characteristics of the science system. Comprehensive, hierarchical, and detailed classifications of large sets of research publications are not easy to obtain. A solution for this problem is to use network-based approaches to cluster research publications based on their citation relations. Clustering approaches have been applied to large sets of publications at the level of individual articles (in contrast to the journal level) for about a decade. Such approaches are addressed in this thesis. I call the resulting classifications “algorithmically constructed, publications-level classifications of research publications” (ACPLCs). The aim of the thesis is to improve interpretability and utility of ACPLCs. I focus on some issues that hitherto have not received much attention in the previous literature: (1) Conceptual framework. Such a framework is elaborated throughout the thesis. Using the social science citation theory, I argue that citations contextualize and position publications in the science system. Citations may therefore be used to identify research fields, defined as focus areas of research at various granularity levels. (2) Granularity levels corresponding to conceptual framework. In Articles I and II, a method is proposed on how to adjust the granularity of ACPLCs in order to obtain clusters corresponding to research fields at two granularity levels: topics and specialties. (3) Cluster labeling. Article III addresses labeling of clusters at different semantic levels, from broad and large to narrow and small, and compares the use of data from various bibliographic fields and different term weighting approaches. (4) Visualization. The methods resulting from Articles I-III are applied in Article IV to obtain a classification of about 19 million biomedical articles. I propose a visualization methodology that provides overview of the classification, using clusters at coarse levels, as well as the possibility to zoom into details, using clusters at a granular level. In conclusion, I have improved interpretability and utility of ACPLCs by providing a conceptual framework, adjusting granularity of clusters, labeling clusters and, finally, by visualizing an ACPLC in a way that provides both overview and detail. I have demonstrated how these methods can be applied to obtain ACPLCs that are useful to, for example, identify and explore focus areas of research

Bio-inspired Methods for Dynamic Network Analysis in Science Mapping

We apply bio-inspired methods for the analysis of different dynamic bibliometric networks (linking papers by citation, authors, and keywords, respectively). Biological species are clusters of individuals defined by widely different criteria and in the biological perspective it is natural to (1) use different categorizations on the same entities (2) to compare the different categorizations and to analyze the dissimilarities, especially as they change over time. We employ the same methodology to comparisons of bibliometric classifications. We constructed them as analogs of three species concepts: cladistic or lineage based, similarity based, and "biological species" (based on co-reproductive ability). We use the Rand and Jaccard indexes to compare classifications in different time intervals. The experiment is aimed to address the classic problem of science mapping, as to what extent the various techniques based on different bibliometric indicators, such as citations, keywords or authors are able to detect convergent structures in the litrerature, that is, to identify coherent specialities or research directions and their dynamics

Detecting Emerging Technologies in Artificial Intelligence Scientific Ecosystem Using an Indicator-based Model

Early identification of emergent topics is of eminent importance due to their potential impacts on society. There are many methods for detecting emerging terms and topics, all with advantages and drawbacks. However, there is no consensus about the attributes and indicators of emergence. In this study, we evaluate emerging topic detection in the field of artificial intelligence using a new method to evaluate emergence. We also introduce two new attributes of collaboration and technological impact which can help us use both paper and patent information simultaneously. Our results confirm that the proposed new method can successfully identify the emerging topics in the period of the study. Moreover, this new method can provide us with the score of each attribute and a final emergence score, which enable us to rank the emerging topics with their emergence scores and each attribute score

Scientometric Analysis of Technology & Innovation Management Literature

The management of technology and innovation has become an attractive and promising field within the management discipline. Therefore, much insight can be gained by reviewing the Technology & Innovation Management (TIM) research in leading TIM journals to identify and classify the key TIM issues by meta-categories and to identify the current trends. Based on a comprehensive scientometric analysis of 5,591 articles in 10 leading TIM specialty journals from 2005 to 2014, this research revealed several enlightening findings. First, the United States is the major producer of TIM research literature, and the greatest number of papers was published in Research Policy. Among the researchers in the field, M. Song is the most prolific author. Second, the TIM field often plays a bridging role in which the integration of ideas can be grouped into 10 clusters: innovation and firms, new product development (NPD) and marketing strategy, project management, patenting and industry, emerging technologies, science policy, social networks, system modeling and development, business strategy, and knowledge transfer. Third, the connectivity among these terms is highly clustered and a network-based perspective revealed that six new topic clusters are emerging: NPD, technology marketing, patents and intellectual property rights, university-industry cooperation, technology forecasting and roadmapping, and green innovation. Finally, chronological trend analysis of key terms indicates a change in emphasis in TIM research from information systems/technologies to the energy sector and green innovation. The results of the study improve our understanding of the structure of TIM as a field of practice and an academic discipline. This insight provides direction regarding future TIM research opportunities

Author-Topic Modeling of DESIDOC Journal of Library and Information Technology (2008-2017), India

This study presents a method to analyze textual data and applying it to the field of Library and Information Science. This paper subsumes a special case of Latent Dirichlet Allocation and Author-Topic models where each article has one unique author and each author has one unique topic. Topic Modeling Toolkit is used to perform the author-topic modeling. The study further which considers topics and their changes over time by taking into account both the word co-occurrence pattern and time. 393 full-text articles were downloaded from DESIDOC Journal of Library and Information Technology and were analyzed accordingly. 16 core topics have been identified throughout the period of ten years. These core topics can be considered as the core area of research in the journal from 2008 to 2017. This paper further identifies top five authors associated with the representative articles for each studied year. These authors can be treated as the subject-experts for the modeled topics as indicated. The results of the study can serve as a platform to determine the research trend; core areas of research; and the subject-experts related to those core areas in the field the Library and Information Science in India

Unveiling the path towards sustainability: scientific interest at HEIs from a scientometric approach in the period 2008-2017

Mención Internacional en el título de doctorLa humanidad ha experimentado el impacto de un modelo económico insostenible a todos los niveles. Este tema se ha cristalizado en diferentes cumbres y conferencias durante el siglo XX. Como resultado de esta preocupación, surgió el concepto de Desarrollo Sostenible (DS). Sin embargo, este concepto ha recibido muchas críticas por ser altamente antropocéntrico y compartimentado, carente de coherencia conceptual o interconexión entre todos los aspectos involucrados. Más tarde, la aparición de los Objetivos de Desarrollo del Milenio (ODM) en 2000 y los recientes Objetivos de Desarrollo Sostenible (ODS) en 2015 constituyen una nueva era. Este es el plan para lograr un futuro mejor y más sostenible para todos, en el que todos los agentes involucrados deben participar. En este punto, las instituciones de educación superior (IES) tienen un papel central y la sostenibilidad se ha convertido en una prioridad política para la ciencia. El objetivo de este estudio es conocer los patrones de la investigación llevada a cabo en investigación de sostenibilidad, incluido el flujo de actividad científica, así como la colaboración o el impacto que genera dicha investigación. Este estudio de doctorado explora cómo se puede delinear este concepto desde un enfoque bibliométrico, lo cual conduce a la ‘ciencia de la sostenibilidad’. La producción científica de artículos fue identificada y analizada en el período 2008-2017 en la Web of Science (WoS). Además, este estudio explora las instituciones de educación superior (IES) y su papel en el fomento de la sostenibilidad, mediante la evaluación de su investigación y la implementación de prácticas de sostenibilidad en las IES españolas. Además, presenta una delineación de los Objetivos de Desarrollo Sostenible (ODS) y propone una metodología para clasificar la producción científica en cada uno e los objetivos. El análisis de esta producción se realiza a través de indicadores bibliométricos unidimensionales y multidimensionales. Estos indicadores se han dividido y analizado en diferentes niveles de agregación, desde el más general hasta el más específico, comenzando con las características generales de investigación y descendiendo al nivel de país, instituciones o temática, entre otros. Los resultados muestran un interés creciente en la investigación de sostenibilidad y se observa una fuerte influencia del pilar medioambiental. Además, hay países con una alta producción científica pero no tan especializados en el tema como otros con una menor producción. En cuanto a las instituciones, los resultados obtenidos muestran que las IES realizaron un importante esfuerzo de investigación para el desarrollo sostenible y son las que producen un mayor número de documentos. Además, se observa que las instituciones tienden a colaborar con centros geográficamente próximos. Al analizar las Prácticas de sostenibilidad en las IES españolas, se encuentran asociaciones altas entre variables como la presencia de un Plan de Sostenibilidad y de una Oficina Verde. Sin embargo, este estudio demuestra claramente que, aunque se reconoce que el desarrollo sostenible es muy importante para las IES y la sociedad, todavía no está integrado en las estrategias, actividades y políticas de todo el sistema. Como conclusión, se afirma que es esencial identificar estrategias de sostenibilidad e introducir desarrollo sostenible en todas las actividades en el entorno de las IES. Finalmente, esta tesis contribuye a la literatura sobre instituciones de educación superior sostenibles, así como al análisis y la mejora de educación superior para el desarrollo sostenible, especialmente en el sistema de educación superior español. Además, este estudio contribuye al análisis bibliométrico al ofrecer dos propuestas de delineación científica para la ciencia de la sostenibilidad y los objetivos de desarrollo sostenible, así como metodologías para clasificar la producción científica. Este análisis denota la importancia de los estudios bibliométricos para el estudio y la caracterización de la producción científica en un campo transdisciplinario que, además, se puede extrapolar a otros campos de estudio.Humanity has experienced the impact of an unsustainable economic model at all levels. This topic has crystallized in different summits and conferences during the 20th century. As a result of this concern, the concept of sustainable development (SD) emerged. However, it has received much criticism for being highly anthropocentric and compartmentalized, and lacking conceptual coherence or interconnectedness among all the aspects involved. The introduction of the Millennium Development Goals (MDGs) in 2000 and the recent Sustainable Development Goals (SDGs) in 2015 heralded a new era. They represent a blueprint to achieve a better and more sustainable future for all, in which all stakeholders need to be involved. At this point, higher education institutions (HEIs) have a central role to play and sustainability has emerged as a policy priority for science. The objective of this study is to investigate the patterns of sustainability research, including the flow of scientific activity, as well as the collaboration or impact that such research generates. This doctoral study explores how can sustainability can be delineated from a bibliometric approach, leading to a new approach of “sustainability science”. The scientific production of articles was identified and analysed for the period 2008–2017 using the Web of Science (WoS). Moreover, this research study explores HEIs and their role in fostering sustainability, by assessing their research and the implementation of sustainability practices in Spanish HEIs. As well, it presents a delineation of the Sustainable Development Goals (SDGs) and proposes a methodology for classifying the output on each SDG. This analysis is done through unidimensional and multidimensional bibliometric indicators. These indicators have been divided and analysed in different levels of aggregation, from the most general to the most specific, starting with general research features and progressing to country, institutional, and thematic levels, among others. The results indicate a growing interest in sustainability research and a strong influence on the environmental pillar. Moreover, some countries with the highest scientific output are not as specialized in terms of topics as others with a lower output. Regarding institutions, the results obtained indicate that HEIs made an important research contribution to SD and are the ones that produce a higher number of documents. It was found that institutions tend to collaborate with other institutions that are close. By analysing sustainability practices in Spanish HEIs, it was found that there are more associations between variables such as having a sustainability plan and having a green office. However, this study clearly demonstrates that although SD is recognized as being very important to HEIs and society, it is not yet embedded in the whole system’s strategies, activities, and policies. In conclusion, this research study reveals that it is essential to identify sustainability strategies and introduce SD in all activities in the HEI environment. Finally, this thesis contributes to the literature on sustainable HEIs, as well as to how higher education for SD is understood and can be improved, especially in the Spanish higher education system. Moreover, this contributes to bibliometric study by offering two delineation approach to sustainability science and sustainable development goals as well as methodologies for classifying scientific output. This denotes the importante of bibliometric studies for the study and characterization of scientific output in a transdisciplinary field that can be extrapolated to other fields of study.Programa de Doctorado en Documentación: Archivos y Bibliotecas en el Entorno Digital por la Universidad Carlos III de MadridPresidente: Carlos Balaguer Bernaldo de Quirós.- Secretario: Birger Larsen.- Vocal: Sandra Sofía Ferreira Da Silva C

Place Identity:How Far Have We Come in Exploring Its Meanings?

In order to synthesize the extensively studied place identities and their meanings, this paper reviews how researchers have conceived and deconstructed place identity. CiteSpace, a scientometric tool for visualizing and analyzing trends and patterns in scientific literature, is used to identify the active topics and new developments of publications in place identity. The data set input into CiteSpace consists of 1,011 bibliographic records retrieved from the core database of Web of Science with a title search of the articles published between 1985 and July 2019. The scientometric review reveals the extensive applications of place identity in various topics. Studies in this field experienced an active exploration in plural disciplines after 2000, and the hot area gradually concentrated on the discipline of humanities and social sciences after 2010 and shifted toward place marketing until now. A network of co-cited references identified seven dominant research clusters, of which the research on the influence of place identity on social actors' attitudes and behaviors is most prominent and the research on the effects of physical environment change on place identity captures the latest emerging area. Versatile meanings of place identity are witnessed in different clusters and articles of a cluster. These meanings are intertwined in shaping the knowledge base of thematic concentrations. To supplement the scientometric analysis, a deep survey on measuring methods and roles of place identity in the contents of academic articles was done to trace knowledge connections between different empirical understandings of place identity. Finally, this paper summarizes the meanings of place identity in four dimensions and in turn offers some suggestions for further research directions

The distributed organization of science : with empirical illustrations from the field of diabetes medicine

The premise of this thesis holds that the organization of science is distributed in nature. That is, science takes place all over the world and within different spheres of society. Within the literature, the distributed organization of science is characterized in different ways. While some focus primarily on the substantive aspects of science such as the increasing importance of interdisciplinarity, others emphasize processes of de-institutionalization as seen in the cooperation between companies, universities and government agencies. Other contributions combine several aspects of science and as such for example speak of both the social and intellectual organization of science. More in general, then, the distributed organization of science can be characterized along different dimensions. The aim of this thesis is to provide insight into the nature and consequences of a distributed organization of science. We take the distinction between Mode 1 and Mode 2 knowledge production as a starting point to describe the distributed organization of science. Mode 1 knowledge production conforms in many respects to the traditional image of scientific knowledge production that takes place primarily within the university; under Mode 1 knowledge production science takes place within strongly defined disciplines and focuses on the fundamental comprehension of natural and social phenomena. In contrast, the idea of Mode 2 knowledge production is characterized by its heterogeneity along all dimensions. That is, besides universities, actors from industry and government are also involved in science; science takes place across disciplines rather than within disciplines only; and under Mode 2 knowledge production science involves not only a quest for fundamental laws and regularities, but has a clear public interest. Despite, or perhaps because of its rich description of science, the distinction between Mode 1 and Mode 2 knowledge production is much criticized. This criticism can be summarized in terms of three main points. First, the notion of Mode 2 knowledge production is conceptually vague. For example, it is unclear what exactly is meant by the notion of transdisciplinarity. Second, the empirical validity of claims on the emergence, prevalence, and persistence of Mode 2 knowledge production is debatable. Although at the project level there is evidence on an increase in the diversity of actors involved in science, it is unclear to what extent this also holds at the level of science systems at large. Finally, it is unclear to what extent Mode 2 knowledge production should be interpreted as a positive phenomenon in a normative sense. The normative implications of the idea of Mode 2 knowledge production have at least two sides. On the one hand the question arises to what extent and how diversity in the organization of distributed science indeed leads to more relevant knowledge. On the other hand, it could also be asked to what extent a development of science towards Mode 2 would prejudice the public interest of scientific knowledge. Within this thesis, the criticisms of the notion of Mode 2 knowledge production are picked up. As such, this thesis addresses (i) an analytical approach to the notion of Mode 2 knowledge production, (ii) the empirical validity of the notion of Mode 2 knowledge production, (iii) the establishment of relevance in a distributed organization of science, and (iv) the normative implications of Mode 2 knowledge production. To strengthen our arguments empirically, we use the case of diabetes medicine. Diabetes medicine is an interesting case for at least three reasons. First, diabetes is a socially relevant problem in the sense that a large group of people around the world are faced with this disease. Consequently, research on diabetes is also widespread. Second, diabetes constitutes a complex disease involving interacting factors such as genetics, lifestyle, and the environment. However, not only are the aspects involved in the constitution of this disease varied, as a consequence so are the people and organizations occupying themselves with finding solutions to this problem. What medical professionals call translational medicine seems to be especially accurate for diabetes, that is, as a description of medical science that concerns itself with diabetes duly takes into account the whole process from the laboratory bench to the patient bedside involving different actors. As such, the nature of diabetes as a scientific problem is immediately enmeshed with societal undertones whose provision of solutions is expected to be organized along various modes. Hence, we expect the organization of diabetes medicine to be characterized by Mode 2 rather than Mode 1 knowledge production. The patterns of a distributed organization of science are addressed empirically using bibliometric data. The choice for a quantitative approach in our empirical research is pragmatic; bibliometrics allows me to address the science system on a large (i.e. global) scale. More fundamentally, we take the scientific publication as a useful starting point to assess science. Here we make a distinction between research and science. Whereas research is about local knowledge production practices, science is first and foremost about the transformation of knowledge towards universal acceptance. As such, the scientific publication is taken as a first and necessary step towards the certification of knowledge as scientific. It follows that the organizational aspects of science that are displayed on the scientific publication such as authorships, affiliations and references provide an input to investigate the patterns underlying the distributed organization of science. Chapter 1 provides a first outline of an analytical approach to Mode 2 knowledge production. To substantiate the notion of Mode 2 knowledge production analytically we distinguish and define five forms of heterogeneity. First, institutional heterogeneity refers to the different value orientations and norms the different actors involved in science adhere to. Second, organizational heterogeneity refers to the different organizations involved in science. Third, geographical heterogeneity refers to science taking place in different countries, regions and cities. Fourth, cognitive heterogeneity refers to the various disciplinary backgrounds of actors. Finally, social heterogeneity refers to the different communities in which actors are active. While some descriptions of science focus on only one dimension of heterogeneity in the distributed organization of science, the notion of Mode 2 knowledge production provides a description of science along all of these five dimensions. The great advantage of studying science along these five dimensions is that we can now analytically address the distributed organization of science along multiple dimensions simultaneously. Then, chapter 2 provides an overview of the recent empirical literature on the distributed organization of science. Of central concern here is the relationship between proximity on the one hand and impact and collaboration on the other hand. At the relational level, the concept of proximity is taken as the counterpart of the concept of heterogeneity. That is to say, where cooperation takes place between operators who are in close proximity to each other, the relationships between these actors are described as homogenous rather than heterogeneous. The main conclusion of this literature review holds that most studies that examine the role of proximity in collaborative science look only at a limited number of proximity dimensions. It follows that to gain a complete understanding of the distributed organization of science we need to include multiple proximity dimensions simultaneously. Chapter 3 forms the prelude to the study of collaboration patterns between organizations in chapter 4. To come to such an analysis, first the idea of 'the organization' is discussed in chapter 3. While in quantitative science studies the nature of the organization is assumed to be unproblematic, within discussions of Mode 2 knowledge production precisely the opposite is true. That is, within the notion of Mode 2 knowledge production, the boundaries between, say, the university and the commercial enterprise have faded. As such, the organization is not an unambiguous unit of analysis in quantitative science studies. However, this does not mean that the organization cannot be used to study science at a higher level of aggregation. Rather, in taking the organization as the basic unit of analysis in quantitative science studies choices must be made in conceptualizing the organization in the first place. These choices are not completely value-free, but must be viewed in light of the research in which the organization as the unit of analysis is used. On the basis of various organization theories, chapter 3 shows how the organization can be conceptualized along several dimensions. Given our conceptualization of the organization that we proposed in chapter 3, chapter 4 analyzes collaboration patterns between organizations. Whereas in the literature on Mode 2 knowledge production the diversity of backgrounds of scientific actors is taken to form no obstacle for collaboration to take place, within the literature on proximity and innovation emphasis is put on the role of proximity in facilitating collaborative innovation. The latter does not mean that proximity needs to play a role along all five dimensions. On the contrary, there may be substitution between different forms of proximity. As such, differences may exist among science systems in how various proximity dimensions shape collaboration between organizations therein. Chapter 4 examines (i) to what extent proximity in all five dimensions plays a role in scientific collaboration in the field of type 2 diabetes and (ii) to what extent the European science system differs from the North American system of science in terms of the comparative importance of the five proximity dimensions. Regarding the role of proximity in scientific collaboration, the main conclusion of this chapter holds that in general all proximity dimensions play their role in shaping collaboration between organizations. In particular, geographical proximity plays an important role in scientific collaboration which suggests that a regional or national focus in the study of science and innovation systems is legitimate. On the other hand, the focus on a "Triple Helix" of university-industry-government relations is no less legitimate because of the relative importance of this type of collaboration, both in North America and in Europe. Regarding the comparison between the European and North American science system, a difference is observed in the role of geographical, social and organizational proximity in shaping scientific collaboration. Where geographical proximity plays a larger role within the European science system, social and organizational proximity play a larger role within the North American science system. The relative importance of geographical proximity within the European science system can be traced to the greater differences in terms of language and culture in Europe. On the other hand the relative importance of organizational and social proximity in North America suggests a more hierarchical system there. It is notable that with regard to the role of institutional proximity the two science systems do not differ. In other words, the attention paid in policy discussions to a relative absence of relationships between academic and non-academic actors in Europe as compared to North America is not justified. The last three chapters of this thesis discuss the implications of a distributed organization of science. First, chapter 5 addresses the citation as a measure of scientific (Mode 1) impact. Within science studies the citation is a contested measure of scientific impact. While some take little issue in using citation indicators, others completely dispense with the use of citation analysis as a tool for scientific evaluation. In order to get out of this impasse we turn to information science studies (in particular, "information retrieval" studies), in which the concept of relevance is important. Parallel to the debate on citation theories, where a distinction is made between a Mertonian perspective on citation as value and a rhetorical perspective on citation as personal, within the information science literature a distinction is made between relevance as system-oriented and relevance as user-oriented. Recently, however, a third perspective on relevance emerged within the information retrieval literature. This socio-cognitive perspective on relevance connects the system approach to the user approach on relevance by paying explicit attention to the context in which relevance is established. On the basis of this socio-cognitive perspective on relevance, we develop a supplement to existing citation theories on the basis of the notion of social embeddedness. The most important conclusion is that, on the basis of the concept of social embeddedness, the two opposite perspectives on citation can be connected. In all we argue that, in the context of Mode 1 knowledge production, the establishment of scientific relevance is contingent upon the structure of social networks and the position of scientists therein. Chapter 6 addresses the role of heterogeneity in relation to the societal relevance (Mode 2 impact) of science. Again we use the case of science in the field of type 2 diabetes. As in Chapter 4, we operationalize the distributed organization of science through five forms of heterogeneity. However, instead of talking about the role of distance (proximity) in the distributed organization of science we speak of the impact that diversity (singularity) in the organization of science has on in its societal relevance. To assess societal relevance, we use the references listed in a clinical practice guideline. Two types of references are distinguished: (i) references that are included in the clinical practice guideline but not as evidence for the treatment of type 2 diabetes and (ii) references that are included in the medical manual and also reflect evidence for the treatment of type 2 diabetes. In comparing the organizational aspects related to the publications associated with these two types of references, we assess the determinants of societal relevance in medical science in the field of type 2 diabetes. The main conclusion holds that, controlling for the scientific relevance of publications, only geographical diversity increases the likelihood of societal relevance. In all it seems that heterogeneity in the distributed organization of science does not naturally lead to a greater chance of societally relevant knowledge. Interesting fact is that publications in which industry is involved have a greater chance of becoming societally relevant. This suggests that the influence of industry in the creation of societally relevant knowledge is large. Finally, chapter 7 elaborates further on the position of industry in medicine. We assess the publication behavior of firms in a context of complete information disclosure where firms face the choice of publishing study outcomes either in scientific publications or in web publications. Due to recent institutional reforms it is now mandated to register clinical trial protocols before onset and publish basic results after study completion. For a sample of clinical trials on diabetes, we link clinical trial protocols to result publications and classify those publications based on the type of evidence they disclose. The results indicate that under conditions of complete information disclosure, firms do indeed not publish less than not-for-profit organizations. However, firms strategically publish in scientific journals where they highlight favorable outcomes to their therapies and clinically relevant studies, since regulators value evidence published in peerreviewed journals much more than evidence published on web sites without peer-review. Thus, despite institutional reforms, pharmaceutical firms still find a way to strategically highlight particular pieces of evidence in scientific journals. We conclude that concerns about publication based on the nature of evidence have shifted rather than disappeared. The presented results in this chapter thus signal a problem of persistent publication bias of a more fundamental nature which is not easily solved by regulatory reform alone. The general conclusion of this thesis is threefold. First, the framework of proximity (distance) and diversity (uniformity) along five dimensions provides a useful analytical tool to address the distributed organization of science. Using this framework, two important critiques on the idea of Mode 2 knowledge production, namely its lacking conceptual clarity and empirical validity, can be tackled. Characterizing scientific actors and their relations along lines of geographical, social, cognitive, institutional, and organizational heterogeneity, renders a more distinct picture of the distributed organization of science. Second, the idea of Mode 2 knowledge production as conceptualized along five dimensions of heterogeneity takes different shapes depending on the level of aggregation. On the level of individual organizations we argue that since the boundaries of the organizations are inherently blurred, many organizations can in principle be characterized as Mode 2. Yet, our empirical analysis shows that on an aggregate level the science system as a whole is not likely to be characterized as Mode 2. Rather, proximity plays an important role in shaping collaboration among organizations. Third, the implications of heterogeneity or Mode 2-ness in the distributed organization of science are ambiguous. On the one hand, heterogeneity in the distributed organization of (medical) science does not render societal relevant knowledge more likely per se. We only find evidence of an increase in the likelihood of societal relevant outcomes under geographical diversity and not for the other four dimensions of heterogeneity. On the other hand, the involvement of industrial actors does render societal relevant knowledge more likely. However, the extent to which such involvement is desirable from a normative perspective is unclear. What holds is that pharmaceutical companies publish their study outcomes strategically. This study has two important implications for further research on the distributed organization of science. First, the framework of proximity and diversity along several dimensions provides an input for further research on the distributed organization of science. Not only can local science systems in this way be compared; in principle one can also compare different disciplinary systems in the same way. In addition, the dynamics of scientific collaboration can be addressed using social network analysis techniques. Second, the relationship between scientific and societal relevance warrants further research. Some exceptions aside, much of quantitative science studies focuses primarily on the development of scientific relevance leaving societal relevance often unaddressed. Ultimately, such data sets enable us to get a better description and explanation of the whole sequence from research via publication towards science becoming societally relevant. More in general, quantitative studies of science might bring together our understanding of knowledge production by not only taking into account journal publication data but also considering alternative data sets reflecting upon research and science’s societal relevance. Finally, with regard to science policy, the question holds what kind of heterogeneity should be targeted given the particular scientific and societal problems at stake. In addition, science policy makers should take into account the institutional requirements of a heterogeneous science system. Non-traditional scientific actors such as companies have interests that are not necessarily in line with the public provision of scientific knowledge. This does not mean that these actors by definition should be excluded from science. Rather, this raises the question whether the way that science is traditionally organized still adequately serves the general interest of public knowledge provision