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Abstract With the rapid accumulation of online information, efficient web navigation has grown vital yet challenging. To create an easily navigable cyberspace catering to diverse demographics, understanding how people navigate differently is paramount. While previous research has unveiled individual differences in spatial navigation, such differences in knowledge space navigation remain sparse. To bridge this gap, we conducted an online experiment where participants played a navigation game on Wikipedia and completed personal information questionnaires. Our analysis shows that age negatively affects knowledge space navigation performance, while multilingualism enhances it. Under time pressure, participants’ performance improves across trials and males outperform females, an effect not observed in games without time pressure. In our experiment, successful route-finding is usually not related to abilities of innovative exploration of routes. Our results underline the importance of age, multilingualism and time constraint in the knowledge space navigation.

We leverage the knowledge network representation of the Medical Subject Heading (MeSH) ontology to infer conceptual distances between roughly 30,000 distinct MeSH keywords — each being prescribed to particular knowledge domains — in order to quantify the origins of cross-domain biomedical convergence. Analysis of MeSH co-occurrence networks based upon 21.6 million research articles indexed by PubMed identifies three robust knowledge clusters: micro-level biological entities and structures; meso-level representations of systems, and diseases and diagnostics; and emergent macro-level biological and social phenomena. Analysis of cross-cluster dynamics shows how these domains integrated from the 1990s onward via technological and informatic capabilities — captured by MeSH belonging to the “Technology, Industry, and Agriculture” (J) and “Information Science” (L) branches — representing highly controllable, scalable and permutable research processes and invaluable imaging techniques for illuminating fundamental yet transformative structure–function–behavior questions. Our results indicate that 8.2% of biomedical research from 2000 to 2018 include MeSH terms from both the J and L MeSH branches, representing a 291% increase from 1980s levels. Article-level MeSH analysis further identifies the increasing prominence of cross-domain integration, and confirms a positive relationship between team size and topical diversity. Journal-level analysis reveals variable trends in topical diversity, suggesting that demand and appreciation for convergence science vary by scholarly community. Altogether, we develop a knowledge network framework that identifies the critical role of techno-informatic inputs as convergence bridges — or catalyzers of integration across distinct knowledge domains — as highlighted by the 1990s genomics revolution, and onward in contemporary brain, behavior and health science initiatives.

With the rapid accumulation of online information, efficient web navigation has grown vital yet challenging. To create an easily navigable cyberspace catering to diverse demographics, understanding how people navigate differently is paramount. While previous research has unveiled individual differences in spatial navigation, such differences in knowledge space navigation remain sparse. To bridge this gap, we conducted an online experiment where participants played a navigation game on Wikipedia and completed personal information questionnaires. Our analysis shows that age negatively affects knowledge space navigation performance, while multilingualism enhances it. Under time pressure, participants' performance improves across trials and males outperform females, an effect not observed in games without time pressure. In our experiment, successful route-finding is usually not related to abilities of innovative exploration of routes. Our results underline the importance of age, multilingualism and time constraint in the knowledge space navigation. [ABSTRACT FROM AUTHOR]

Knowledge networks have become a critical factor in the development of innovation. However, most studies focus on the innovation benefits derived from network embedding, and there are fewer studies on firms' knowledge networks from the perspective of feature attributes. This study analyzes the direct and interactive effects of knowledge diversity and the combination of knowledge potential on innovation performance. The research also explores how the complementarity of ambidextrous learning affects the relationship between knowledge networks and innovation performance. The empirical analysis is based on panel data from 116 firms in China's automotive manufacturing industry from 2010-2018. The results processed by the fixed effects negative binomial regression model indicate that the combinatorial potential of knowledge has an inverted U-shaped relationship with firm innovation performance, and knowledge diversity has a positive effect on firm innovation performance. There is an interactive effect between knowledge combination potential and knowledge diversity, and their mutual coordination improves firm innovation performance. The complementarity of ambidextrous learning significantly and positively moderates the positive relationship between the combination potential of knowledge and firm innovation performance. [ABSTRACT FROM AUTHOR]

Theoretical constructs, such as the information gap theory and compression progress theory, seek to explain how humans practice curiosity. According to the former, curiosity is the drive to acquire information missing from our understanding of the world. According to the latter, curiosity is the drive to construct parsimonious mental world models. To complement the densification and simplification processes inherent to these frameworks, we propose the conformational change theory, wherein we posit that curiosity builds mental models with marked conceptual flexibility. We formalize curiosity as a knowledge-network-building process to investigate each theoretical account for individuals and collectives. In knowledge networks, gaps can be identified as topological cavities, compression progress can be quantified using network compressibility, and flexibility can be measured as the number of conformational degrees of freedom. We find that curiosity fills gaps and constructs increasingly compressible and flexible knowledge networks. Across individuals and collectives, we determine the contexts in which each account is explanatory, clarifying their complementary and distinct contributions. Our findings offer a novel networks-based perspective that harmonizes with (and compels an expansion of) the traditional taxonomy of curiosity. [ABSTRACT FROM AUTHOR]

Copyright of Research Papers of the Wroclaw University of Economics / Prace Naukowe Uniwersytetu Ekonomicznego we Wroclawiu is the property of Uniwersytet Ekonomiczny we Wroclawiu and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We develop a quantitative framework for understanding the class of wicked problems that emerge at the intersections of natural, social, and technological complex systems. Wicked problems reflect our incomplete understanding of interdependent global systems and the systemic risk they pose; such problems escape solutions because they are often ill-defined, and thus mis-identified and under-appreciated by communities of problem-solvers. While there are well-documented benefits to tackling boundary-crossing problems from various viewpoints, the integration of diverse approaches can nevertheless contribute confusion around the collective understanding of the core concepts and feasible solutions. We explore this paradox by analyzing the development of both scholarly (social) and topical (cognitive) communities — two facets of knowledge production studies here that contribute towards the evolution of knowledge in and around a problem, termed a knowledge trajectory — associated with three wicked problems: deforestation, invasive species, and wildlife trade. We posit that saturation in the dynamics of social and cognitive diversity growth is an indicator of reduced uncertainty in the evolution of the comprehensive knowledge trajectory emerging around each wicked problem. Informed by comprehensive bibliometric data capturing both social and cognitive dimensions of each problem domain, we thereby develop a framework that assesses the stability of knowledge trajectory dynamics as an indicator of wickedness associated with conceptual and solution uncertainty. As such, our results identify wildlife trade as a wicked problem that may be difficult to address given recent instability in its knowledge trajectory.

Ornamental plants play a fundamental role in diverse applications, from cut flower production to landscape design and space decoration. The ornamental industry, which is part of horticulture, has experienced significant advances and mobilizes billions of dollars in the global economy, being also a totally globalized market. In recent years, this industry has implemented advanced production strategies, from genetic improvement to sustainability and supply chain, promoting scientific research in various areas. However, the dispersion of knowledge has hindered the integration of the various research networks. Therefore, this article seeks to provide an overview of the scientific production in the cut flower sector, establishing a reference line for researchers, using bibliometrics as a tool to identify trends and the scientific structure of this area of knowledge. The results revealed that worldwide since 1983 there have been 975 articles focused on this productive system, gene rated in more than 69 countries by 2750 authors who published their research in 160 academic journals. Relevant research topics that are already developed and those that need a more intense and integrated research focus on the knowledge already generated were also identified.

Copyright of NovaRUA Revista Universitaria de Administracion is the property of NovaRUA Revista Universitaria de Administracion and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Brazilian Business Law Journal / Administração de Empresas em Revista is the property of Administracao de Empresas em Revista and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study seeks to investigate firm-level innovation, exploring whether social relationships located in knowledge networks influence the transfer of university knowledge to Ghanaian firms. Firms’ informal relationships with universities have been under-researched in developing economies. The extant literature suggests that informal relationships in the context of economies with advanced regional and national innovation systems have a positive association with firm level innovation performance. The research project employs a cross-sectional survey of 245 firms in Ghana. The aim of the project is to explore the influence of informal mechanisms of university knowledge transfer on firm level innovation performance in Ghana. The study adopts a structural model with partial least squares as an analytical technique. The findings reveal that to deliver positive results in a firm’s innovation performance by informal means, a well-coordinated social system to attract research knowledge from all aspects of the university system is required. The research project’s implications for Ghana’s innovation system include a need to be aware of the impact of corruption and lack of intellectual property rights on the efficacy informal knowledge transfer.

Copyright of Tecnura is the property of Tecnura and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Despite its recent growth in popularity since the COVID-19 pandemic, One Health* can be traced back to the colonial period when it was used to control the health of local communities and their animals while exploiting natural resources. At present, it is necessary to move away from this asymmetrical colonialist view and develop more inclusive perspectives. Local communities have their own knowledge with a holistic vision of health involving humans, animals and the environment. Their viewpoint is nevertheless rarely taken into consideration within the scientific approach to health. To fill this gap, the humanities and social sciences can be used to revive this local knowledge and to initiate a dialogue with scientific knowledge. More crucially, to effectively put One Health into practice, researchers must call into question their own practices, reflect on what constitutes science and rethink the way of producing knowledge, all the while acknowledging the different ways of understanding the world and diseases. This means opening up to other forms of knowledge and epistemologies and networking them.

Artificial Intelligence (AI) has emerged as a field of knowledge that is displacing and disrupting technologies, leading to changes in human life. Therefore, the purpose of this study is to scientifically map this topic and its ramifications, in order to analyze its growth. The study was developed under the bibliometric approach and considered the period 1990–2019. The steps followed were (i) Identification and selection of keyword terms in three methodological layers by a panel of experts. (ii) Design and application of an algorithm to identify these selected keywords in titles, abstracts, and keywords using terms in Web of Science to contrast them. (iii) Performing data processing based on the Journals of the Journal Citation Report during 2020. Knowing the evolution of a field of knowledge such as AI from a bibliometric study and subsequently establishing the ramifications of new research streams is in itself a relevant finding. Addressing a broad field of knowledge as AI from a multidisciplinary approach given the convergence it generates with other disciplines and specialties is of high strategic value for decision makers such as governments, academics, scientists, and entrepreneurs. [ABSTRACT FROM AUTHOR]

The effects of climate change are instigating a discourse shift towards net-zero emissions agriculture. However, a sectoral silo paradigm of policy design is incompatible with a systems approach to address complex global environmental challenges. This study introduces a social cartography approach that amalgamates network theory with a nexus perspective to identify social relation changes in the making. The study examines the role of an advisor-led initiative promoting the discourse of climate-smart farming in Scotland and identifies the impacts upon farmer knowledge networks. The social cartography comprises of a survey, farm meeting observations, and social network analysis of the agriculture, climate change, and energy (ACE) policyscape. As a visualization method, the social cartography provides a conceptual compass to navigate social relation changes of farmer knowledge networks amidst discursive transition. The results demonstrate that the advisor-led initiative acts an intermediary of discursive transition by introducing new knowledge frames and practices of farming that facilitate network shifts. However, voluntary measures fall short of instigating cross-sectoral interplay to actualize transformation towards systems integration. Furthermore, the study presents policy design elements to chart a new frontier of integrated agrifood and energy systems governance in Scotland. • Innovative policyscape approach to agrifood systems transformation. • Novel ACE nexus concept: agriculture, climate change, energy policy intersection. • Role of advisors as intermediaries in farmer knowledge networks. • Social processes and properties for discourse transition. • Policy design elements for integrated agrifood and energy systems governance. [ABSTRACT FROM AUTHOR]

This study seeks to investigate firm-level innovation, exploring whether social relationships located in knowledge networks influence the transfer of university knowledge to Ghanaian firms. Firms' informal relationships with universities have been under-researched in developing economies. The extant literature suggests that informal relationships in the context of economies with advanced regional and national innovation systems have a positive association with firm level innovation performance. The research project employs a cross-sectional survey of 245 firms in Ghana. The aim of the project is to explore the influence of informal mechanisms of university knowledge transfer on firm level innovation performance in Ghana. The study adopts a structural model with partial least squares as an analytical technique. The findings reveal that to deliver positive results in a firm's innovation performance by informal means, a well-coordinated social system to attract research knowledge from all aspects of the university system is required. The research project's implications for Ghana's innovation system include a need to be aware of the impact of corruption and lack of intellectual property rights on the efficacy informal knowledge transfer. [ABSTRACT FROM AUTHOR]

This document aims to predict the level of innovation in manufacturing companies in Colombia between 2017-2018. A forecasting mechanism for innovation performance has been constructed using Neural Networks (NNs). This model considers the objectives of innovation, obstacles to innovation, knowledge networks, and technical information of each one of the firms. Results show that demand push, vertical sources, financial obstacles, and qualified personnel are the most important variables in predicting innovative performance. Our empirical analysis uses firm-level innovation survey data from the EDIT (Encuesta de Desarrollo e Innovación Tecnológica in Spanish, Technological Development, and Innovation Survey in English) for Colombia for the years 2017-2018.

In addition to their often‐cited role as global service hubs, world cities are also global innovation hubs with their connectivity in knowledge networks crucial for the innovation clusters they harbour. While both aspects of world cities' global connectivity may allow their urban economies to grow, we argue that specialization in one of these two networks may increase economic performance. We provide systematic evidence of this substitution effect by examining the changing positions of 129 world cities in inter‐city innovation and service firm networks (2000–2012). Fixed effects panel analysis of city GDP growth confirm that the two networks are partial substitutes. [ABSTRACT FROM AUTHOR]

Young people are on the front lines of transforming agriculture and food systems, coping with the social and economic impacts of COVID-19 as well as environmental and climate change effects which are likely to accelerate and intensify during their lifetimes. At the same time, young people across global contexts are increasingly emerging as visible agents of change in food systems, especially through networks that create, transform, and distribute food systems knowledge. This policy and practice review examines the role of youth as actors through food systems knowledge networks. Increasing youth participation in creating sustainable food systems for the future requires policies and practices that support food systems-related knowledge in two ways: (1) democratizing formal education systems; and (2) strengthening horizontal networks of grassroots research and innovation, including through traditional, ecological, local and community knowledge (TELCK). Food systems policies should be developed through dialogue with diverse knowledge systems, experiences, place-based needs, and aspirations of young people to maximize their participation in food systems policy development and evaluation.

Abstract Background Scientific literature carries a wealth of information crucial for research, but only a fraction of it is present as structured information in databases and therefore can be analyzed using traditional data analysis tools. Natural language processing (NLP) is often and successfully employed to support humans by distilling relevant information from large corpora of free text and structuring it in a way that lends itself to further computational analyses. For this pilot, we developed a pipeline that uses NLP on biological literature to produce knowledge networks. We focused on the flesh color of potato, a well-studied trait with known associations, and we investigated whether these knowledge networks can assist us in formulating new hypotheses on the underlying biological processes. Results We trained an NLP model based on a manually annotated corpus of 34 full-text potato articles, to recognize relevant biological entities and relationships between them in text (genes, proteins, metabolites and traits). This model detected the number of biological entities with a precision of 97.65% and a recall of 88.91% on the training set. We conducted a time series analysis on 4023 PubMed abstract of plant genetics-based articles which focus on 4 major Solanaceous crops (tomato, potato, eggplant and capsicum), to determine that the networks contained both previously known and contemporaneously unknown leads to subsequently discovered biological phenomena relating to flesh color. A novel time-based analysis of these networks indicates a connection between our trait and a candidate gene (zeaxanthin epoxidase) already two years prior to explicit statements of that connection in the literature. Conclusions Our time-based analysis indicates that network-assisted hypothesis generation shows promise for knowledge discovery, data integration and hypothesis generation in scientific research.

Impact assessment (IA) involves complex interactions among societal actors with diverse knowledge systems and worldviews (ontological pluralism) that ideally combine to both define and support societal goals, such as sustainable development. An often acknowledged but rarely explored concept in these efforts is research capacity — the ability of a group to engage, produce, maintain and use knowledge — and associated implications for pluralistic process outcomes. This paper presents an embedded case study of the IA policy network in the Yukon Territory, Canada, to explore the various roles of research capacity in a well-established IA process where Indigenous and public representation are guaranteed, as is financial support for boundary spanning and knowledge brokering roles to support pluralism. Using Rapid Policy Network Mapping, we examine the formal and informal connections amongst IA policy actors and identify sources and flows of knowledge throughout the network. Results indicate that while research capacity is critical to well-functioning IA processes in the Yukon Territory, the ability of the IA policy network to source, disseminate and engage new knowledge is limited. Important boundary spanning 'choke points' can act as both facilitators and barriers, based on the capacity of the knowledge brokers occupying these spaces. The findings inform policy efforts to ensure inclusion and advance pluralism in IA processes. [ABSTRACT FROM AUTHOR]

This paper explores effect of proximities on R&D collaboration and focus on a prime mechanism of intentional search for knowledge—joint R&D projects—using data on R&D projects co‐financed by various public sector bodies in the period 2003–2018. Our findings show that R&D collaboration based on cognitive proximity is intentional and firms prefer partners with technological distance smaller than expected based on a reference population. In the case of repeated R&D collaboration among the same companies in manufacturing, there is a statistically significant shift towards a higher cognitive proximity. As for geographical proximity, we found relatively low intra‐regional R‐D collaboration and high openness of regional innovation systems. [ABSTRACT FROM AUTHOR]

This study introduces novel research using Practice Context Models supported by Knowledge Networks and Percolation Theory with the aim to contribute to knowledge management in Proof-of-Concept (PoC) activities. The authors envision this proposal as a potential instrument to identify network structures based on a percolation (propagation) threshold and to analyze the importance of nodes (e.g., practitioners, practices, competencies, movements, and scenarios) during the percolation of knowledge in PoC activities. After thirty months immersed in the natural PoC habitat, acting as observers and practitioners, and supported by an ethnographic exercise and a designer-research mindset, the authors identified the production of meaning in PoC activities occurring in a hermeneutic circle characterized by the presence of several knowledge networks; thus, discovering the ‘natural knowledge’ in PoC as a spectrum of cognitive development spread throughout its network, as each node could produce and disseminate certain knowledge that flows and influences other nodes. Therefore, this research presents the use of Practice Context Models ‘connected’ to Knowledge Networks and Percolation Theory as a potential and feasible proposal to be built using the attribution of values (weights) to the nodes (e.g., practitioners, practices, competencies, movements, scenarios, and also knowledge) in the context of PoC with the aim to allow the players (e.g., PoC practitioners) to have more flexibility in building alliances with other players (new nodes); that is, focusing on those nodes with higher value (focus on quality) in collaboration networks, i.e., alliances (connections) with the aim to contribute to knowledge management in the context of PoC.

Although there is a broad agreement on the importance of scientific knowledge for the implementation of the Sustainable Development Goals, high levels of uncertainty and debate about what counts as knowledge challenge the use of research for political decision-making. Hence, the question arises, which strategies of scientific knowledge integration are adopted by science-based actor-networks that seek to enhance evidence in sustainability governance. In this article, I study the Sustainable Development Solution Network (SDSN) engaged in different institutional settings and policy fields. With a qualitative document analysis, I compare the overall structure, objectives, thematic focus, formal knowledge processes, and outputs of 22 national sub-networks of the global SDSN in order to elucidate how these initiatives integrate contested sustainability knowledge underpinning the implementation of the 2030 Agenda. My findings suggest that most SDSNs adopt solution-oriented knowledge integration strategies but also that networks in countries with better overall SDG performance tend to adopt assessment-oriented and learning-oriented strategies. In reflecting on these results in the context of the current literature on knowledge integration in sustainability governance, I argue that science–policy interfaces are shaped by the intentional and dynamic interactions of actors within their institutional setting and policy environment, and propose pathways for further research.

Purpose – The nature of the collaborations that exists among the organizations in the climate change and agriculture sectors can influence the tailoring of climate forecasts into information useable for adapting agricultural practices to the risks posed by climate change. Also, the extent to which farmers are integrated into this organizational collaboration network can influence their access to climate information. This paper aims to examine how organizational collaborations in the process of climate information generation and dissemination acts as either barriers or enablers of farmers’ access to and use of climate information in Ghana. Design/methodology/approach – This study used key informant interview and questionnaire survey to interview the organizations in the climate change and agriculture sectors. Using network analysis as an analytical framework, the authors estimated the networks’ core-periphery, density, reciprocity and degree centrality. Findings – The authors observed that communication of climate information to farmers is mostly influenced by the collaborations between governmental organizations and nongovernmental organizations. Nevertheless, information flow and exchange through organizational collaboration network is having limited effect on improving farmers’ knowledge about climate risks, impacts and available risk response options. This is mostly because the feedback flow of information from farmers to national level organizations has not been effective in addressing localized climate/agro challenges. Originality/value – This paper provides a critical overview of key issues in influencing the relevancy and usefulness of climate information in the Ghanaian agriculture sector. Insights gained and recommendations made are essential for deploying effective climate services in Ghana and can be relevant for many African countries because of similar socioeconomic contexts.

All living beings use autopoiesis and cognition to manage their "life" processes from birth through death. Autopoiesis enables them to use the specification in their genomes to instantiate themselves using matter and energy transformations. They reproduce, replicate, and manage their stability. Cognition allows them to process information into knowledge and use it to manage its interactions between various constituent parts within the system and its interaction with the environment. Currently, various attempts are underway to make modern computers mimic the resilience and intelligence of living beings using symbolic and sub-symbolic computing. We discuss here the limitations of classical computer science for implementing autopoietic and cognitive behaviors in digital machines. We propose a new architecture applying the general theory of information (GTI) and pave the path to make digital automata mimic living organisms by exhibiting autopoiesis and cognitive behaviors. The new science, based on GTI, asserts that information is a fundamental constituent of the physical world and that living beings convert information into knowledge using physical structures that use matter and energy. Our proposal uses the tools derived from GTI to provide a common knowledge representation from existing symbolic and sub-symbolic computing structures to implement autopoiesis and cognitive behaviors. [ABSTRACT FROM AUTHOR]

Copyright of Journal History of Latin American Education / Revista Historia de la Educación Latinoamericana is the property of Universidad Pedagogica y Tecnologica de Colombia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Industrial strategies based on industrial ecology and circular economy have populated the current industrial landscape. However, these approaches focusing on the creation of symbiotic relationship among industries have been relatively insufficiently researched. Although economically and environmentally beneficial, the process of their emergence and development remains unclear. This conceptual research advances the potential role of knowledge in the creation of symbiotic linkages through a qualitative theoretical literature research. The result is a conceptual framework combining different theoretical streams. I conclude that by using absorptive capacity constructs coupled with the principles of industrial ecosystem framed under social network analysis, the genesis of industrial ecosystem can be unearthed. Las estrategias industriales basadas en la ecología industrial y la economía circular han poblado el panorama industrial actual. Sin embargo, los enfoques que se centran en la creación de relaciones simbióticas entre las industrias han sido relativamente poco investigados. Aunque económica y ambientalmente beneficioso, el proceso de su surgimiento y desarrollo sigue sin estar claro. Esta investigación conceptual avanza en el papel potencial del conocimiento en la creación de enlaces simbióticos a través de una investigación cualitativa de revisión de literatura teórica. El resultado es un marco conceptual que combina diferentes corrientes teóricas. Se concluye que, al usar constructos como capacidad de absorción junto con los principios del ecosistema industrial enmarcados en el análisis de redes sociales, el génesis de un ecosistema industrial puede ser descubierto. Estratégias industriais baseadas na ecologia industrial e na economia circular povoaram o cenário industrial atual. No entanto, essas abordagens que se concentram na criação de relações simbióticas entre indústrias têm sido relativamente pouco pesquisadas. Embora seja econômico e ambientalmente benéfico, o processo de seu surgimento e desenvolvimento permanece incerto. Esta pesquisa conceitual avança o papel potencial do conhecimento na criação de vínculos simbióticos por meio de uma revisão qualitativa da literatura teórica. O resultado é uma estrutura conceitual que combina diferentes correntes teóricas. Conclui-se que, usando construções como capacidade de absorção juntamente com os princípios do ecossistema industrial enquadrados na análise de redes sociais, pode-se descobrir a gênese de um ecossistema industrial.

Contextual information is a crucial factor in interdisciplinary research on social networks. At the same time, missing linked data and missing methods for large-scale knowledge networks are a serious limitation. Only few researches have addressed the questions between data science, graph theory and social network analysis. This paper seeks to discuss how this gap can be closed. For this, we use an interdisciplinary approach trying to improve the interdisciplinary exchange and method exchange. We investigate how new methods from computer science, in particular knowledge graphs, can be used within the field of SNA. The contributions of this paper are (1) a knowledge graph model representation of a multi-layer social network, (2) the showcase of examples from different domains and (3) a perspective for more interdisciplinary discussion. We present an innovative solution to discuss coming challenges in SNA with methods from the digital humanities, in particular computer science.

Several natural and artificial structures are characterized by an intrinsic hierarchical organization. The present work describes a methodology for quantifying the degree of adherence between a given hierarchical template and a respective modular document (e.g. books or homepages with content organized into modules) organized as a respective content network. The original document, which in the case of the present work concerns Wikipedia pages, is transformed into a respective content network by first dividing the document into parts or modules. Then, the contents (words) of each pair of modules are compared in terms of the coincidence similarity index, yielding a respective weight. The adherence between the hierarchical template and the content network can then be measured by considering the coincidence similarity between the respective adjacency matrices, leading to the respective hierarchical adherence index. In order to provide additional information about this adherence, four specific indices are also proposed, quantifying the number of links between non-adjacent levels, links between nodes in the same level, converging links between adjacent levels, and missing links. The potential of the approach is illustrated respectively to model-theoretical networks as well as to real-world data obtained from Wikipedia. In addition to confirming the effectiveness of the suggested concepts and methods, the results suggest that real-world documents do not tend to substantially adhere to respective hierarchical templates.

Journal clubs have an extensive history that dates back to the time of Sir William Osler. They provide a venue to discuss the latest medical literature among groups of peers and are an innovative method for translating knowledge into practice within individual institutions. With advances in social media, journal clubs are poised to take an evolutionary step by harnessing digital connectivity. Online journal clubs are uniting hundreds of medical practitioners from around the world under the banner of one cause: enhancing knowledge translation of the medical literature without the limitations of geography. This article describes 10 steps for creating online journal clubs based on the experiences of a multidisciplinary team of clinicians and medical educators.

Entrepreneurship in the sub-Saharan African agricultural sector has been growing in recent years because of increasing unemployment and underemployment. In Benin, policies and programs are encouraging individuals to start their own agribusinesses. To further sharpen these policies and programs to improve agricultural entrepreneurship's contribution to the economy, it is essential to avail information on the entrepreneurs, their businesses, and the typologies of agribusinesses. Such information is limited, which reduces the ability to develop evidence-informed policies and programs. This research aims to fill the gaps by describing the features of agricultural entrepreneurs in Benin. A random sample of819 agricultural entrepreneurs was used, and data were collected on entrepreneurs and their businesses. Descriptive analysis and hierarchical clustering of principal components were performed. The study found that women's participation in agricultural entrepreneurship in terms of new business formation is still low. Also, the agricultural entrepreneurs are more driven by necessity than opportunity, although they have a highly positive personality, mainly in terms of optimism and risk. At the enterprise level, most agribusinesses have been in operation for more than three years, but only one out of ten entrepreneurs felt that their business was at a mature phase. The research also evidenced that informality in the agribusiness sector is high because almost half of the agribusinesses were not registered with any formal governmental entity, and only three out of ten complied with tax regulations. Agricultural entrepreneurs were active in knowledge networks to expand their activities and improve their performance. Three categories of agribusiness were defined with the cluster analysis: 'informal agribusinesses' essentially built for profit, not registered, and owned by not highly educated adult entrepreneurs; 'professional new agribusinesses' were mainly operated by young entrepreneurs with a university education and agricultural professional training; and 'mature agribusinesses' were mostly formally registered and owned by highly educated entrepreneurs. This research will be instrumental for policymakers and practitioners to better understand agricultural entrepreneurship and improve its economic outcomes. It provides a strong evidence base to support the ongoing motivation of policymakers to provide solutions to unemployment and underemployment through agricultural entrepreneurship. [ABSTRACT FROM AUTHOR]

The aim of this paper is to develop and test the metrics to quantitatively identify technological discontinuities in a knowledge network. We first analyzed the various conceptual frameworks for defining such discontinuities and arrived at four metrics. We tested the four metrics: Metric 1 and 2 are the normalized versions of previously existing metrics and Metric 3 and 4 are newly developed from the innovation theories, by using a patent set representative of the magnetic information storage domain. The three representative patents associated with a well-known breakthrough technology in the domain, the giant magneto-resistance spin valve sensor, were selected based on qualitative studies, and the metrics were tested by how well each identifies the selected patents as top-ranked patents. The empirical results show that, first, global citation structure-based metrics clearly provide better performance in the identification of technological discontinuities than local citation count-based metrics which have not been shown as clearly before, second, non-continuous nodes on the major knowledge networks are not at all related to technological discontinuities, and, third, the two global metrics (Metric2: z-score of Persistence and Metric 4: z-score of Persistence times # of converging main paths) successfully identified the three selected patents as top-ranked patents out of over 30 000 patents.

Since December 2019, there has been a global explosion of research on COVID-19. In Canada, the six National Collaborating Centres (NCCs) for Public Health form one of the central pillars supporting evidence-informed decision making by gathering, synthesizing and translating emerging findings. Funded by the Public Health Agency of Canada and located across Canada, the six NCCs promote and support the use of scientific research and other knowledges to strengthen public health practice, programs and policies. This paper offers an overview of the NCCs as an example of public health knowledge mobilization in Canada and showcases the NCCs' contribution to the COVID-19 response while reflecting on the numerous challenges encountered. [ABSTRACT FROM AUTHOR]

Background: Scientific literature carries a wealth of information crucial for research, but only a fraction of it is present as structured information in databases and therefore can be analyzed using traditional data analysis tools. Natural language processing (NLP) is often and successfully employed to support humans by distilling relevant information from large corpora of free text and structuring it in a way that lends itself to further computational analyses. For this pilot, we developed a pipeline that uses NLP on biological literature to produce knowledge networks. We focused on the flesh color of potato, a well-studied trait with known associations, and we investigated whether these knowledge networks can assist us in formulating new hypotheses on the underlying biological processes. Results: We trained an NLP model based on a manually annotated corpus of 34 full-text potato articles, to recognize relevant biological entities and relationships between them in text (genes, proteins, metabolites and traits). This model detected the number of biological entities with a precision of 97.65% and a recall of 88.91% on the training set. We conducted a time series analysis on 4023 PubMed abstract of plant genetics-based articles which focus on 4 major Solanaceous crops (tomato, potato, eggplant and capsicum), to determine that the networks contained both previously known and contemporaneously unknown leads to subsequently discovered biological phenomena relating to flesh color. A novel time-based analysis of these networks indicates a connection between our trait and a candidate gene (zeaxanthin epoxidase) already two years prior to explicit statements of that connection in the literature. Conclusions: Our time-based analysis indicates that network-assisted hypothesis generation shows promise for knowledge discovery, data integration and hypothesis generation in scientific research. [ABSTRACT FROM AUTHOR]

The standards of educational information exchange are still firmly rooted in a Newtonian paradigm that emphasizes strict rules of information exchange. With the explosion of information since World War II, and especially its accessibility through the mechanism of the internet, this paradigm has become a barrier to effective exchanges of information at all levels. Vannevar Bush recognized this problem as early as 1945 and provided a roadmap to addressing it in his famous As We May Think. Douglas Engelbart and Theodore Holmes Nelson applied Bush’s vision to technology but we have never fully realized its potential in part due to our Newtonian information paradigm. This article argues that what Bush, Engelbart, and Nelson proposed is essentially an Einsteinian (relativistic) notion of information flows with tools specifically designed to facilitate the augmentation of human knowledge. It further posits what such a system of knowledge exchange might look like and how we might begin to build it.

This study introduces novel research using Practice Context Models supported by Knowledge Networks and Percolation Theory with the aim to contribute to knowledge management in Proof-of-Concept (PoC) activities. The authors envision this proposal as a potential instrument to identify network structures based on a percolation (propagation) threshold and to analyze the importance of nodes (e.g., practitioners, practices, competencies, movements, and scenarios) during the percolation of knowledge in PoC activities. After thirty months immersed in the natural PoC habitat, acting as observers and practitioners, and supported by an ethnographic exercise and a designer-research mindset, the authors identified the production of meaning in PoC activities occurring in a hermeneutic circle characterized by the presence of several knowledge networks; thus, discovering the 'natural knowledge' in PoC as a spectrum of cognitive development spread throughout its network, as each node could produce and disseminate certain knowledge that flows and influences other nodes. Therefore, this research presents the use of Practice Context Models 'connected' to Knowledge Networks and Percolation Theory as a potential and feasible proposal to be built using the attribution of values (weights) to the nodes (e.g., practitioners, practices, competencies, movements, scenarios, and also knowledge) in the context of PoC with the aim to allow the players (e.g., PoC practitioners) to have more flexibility in building alliances with other players (new nodes); that is, focusing on those nodes with higher value (focus on quality) in collaboration networks, i.e., alliances (connections) with the aim to contribute to knowledge management in the context of PoC. [ABSTRACT FROM AUTHOR]

Although there is a broad agreement on the importance of scientific knowledge for the implementation of the Sustainable Development Goals, high levels of uncertainty and debate about what counts as knowledge challenge the use of research for political decision-making. Hence, the question arises, which strategies of scientific knowledge integration are adopted by science-based actor-networks that seek to enhance evidence in sustainability governance. In this article, I study the Sustainable Development Solution Network (SDSN) engaged in different institutional settings and policy fields. With a qualitative document analysis, I compare the overall structure, objectives, thematic focus, formal knowledge processes, and outputs of 22 national sub-networks of the global SDSN in order to elucidate how these initiatives integrate contested sustainability knowledge underpinning the implementation of the 2030 Agenda. My findings suggest that most SDSNs adopt solution-oriented knowledge integration strategies but also that networks in countries with better overall SDG performance tend to adopt assessment-oriented and learning-oriented strategies. In reflecting on these results in the context of the current literature on knowledge integration in sustainability governance, I argue that science--policy interfaces are shaped by the intentional and dynamic interactions of actors within their institutional setting and policy environment, and propose pathways for further research. [ABSTRACT FROM AUTHOR]

The standards of educational information exchange are still firmly rooted in a Newtonian paradigm that emphasizes strict rules of information exchange. With the explosion of information since World War II, and especially its accessibility through the mechanism of the internet, this paradigm has become a barrier to effective exchanges of information at all levels. Vannevar Bush recognized this problem as early as 1945 and provided a roadmap to addressing it in his famous As We May Think. Douglas Engelbart and Theodore Holmes Nelson applied Bush's vision to technology but we have never fully realized its potential in part due to our Newtonian information paradigm. This article argues that what Bush, Engelbart, and Nelson proposed is essentially an Einsteinian (relativistic) notion of information flows with tools specifically designed to facilitate the augmentation of human knowledge. It further posits what such a system of knowledge exchange might look like and how we might begin to build it. [ABSTRACT FROM AUTHOR]

Formal and semi-formal networks are emerging as effective, collaborative, and adaptable approaches for addressing complex, rapidly evolving ocean governance issues. One such group of networks, which we refer to as marine-related learning networks, play multifaceted roles within ocean governance systems by facilitating knowledge creation, exchange, and dissemination, and by building the capacity of individuals and institutions to address problems and improve coastal and ocean governance. This study investigates the emergence, key attributes, and outcomes of marine-related networks using semi-structured interview data from 40 key informants representing 16 different networks that operate around the world at local, national, regional, and global scales. Our findings indicate that marine-related learning networks form in response to knowledge and action gaps and the specific needs of network members, and they function to inform policy and improve ocean management. Their success depends on attributes such as having a distinct purpose, building trust and relationships, emphasizing equitable participation, and supporting clear, sustained leadership. Marine-related learning networks are uniquely positioned to act as catalyzers and conduits to build capacity and develop solutions in response to governance needs through inclusive and collaborative responses to ongoing and emerging marine issues. As such, a broader understanding of their growing significance and the effective practices they employ is warranted.

All living beings use autopoiesis and cognition to manage their “life” processes from birth through death. Autopoiesis enables them to use the specification in their genomes to instantiate themselves using matter and energy transformations. They reproduce, replicate, and manage their stability. Cognition allows them to process information into knowledge and use it to manage its interactions between various constituent parts within the system and its interaction with the environment. Currently, various attempts are underway to make modern computers mimic the resilience and intelligence of living beings using symbolic and sub-symbolic computing. We discuss here the limitations of classical computer science for implementing autopoietic and cognitive behaviors in digital machines. We propose a new architecture applying the general theory of information (GTI) and pave the path to make digital automata mimic living organisms by exhibiting autopoiesis and cognitive behaviors. The new science, based on GTI, asserts that information is a fundamental constituent of the physical world and that living beings convert information into knowledge using physical structures that use matter and energy. Our proposal uses the tools derived from GTI to provide a common knowledge representation from existing symbolic and sub-symbolic computing structures to implement autopoiesis and cognitive behaviors.

This is a condensed version of an interview with Laura Grace Weldon, author of Free Range Learning: How Homeschooling Changes Everything, by Rebecca Bohnman on The Luminous Mind podcast. Weldon discusses her family’s shift from schooling to homeschooling tounschooling. She also describes using research to shake off a conventional school mindset, the benefits of diversity in homeschooling/unschooling groups, recognizing knowledge networks, and more.

Humans receive information from the world around them in sequences of discrete items--from words in language or notes in music to abstract concepts in books and websites on the Internet. To model their environment, from a young age people are tasked with learning the network structures formed by these items (nodes) and the connections between them (edges). But how do humans uncover the large-scale structures of networks when they experience only sequences of individual items? Moreover, what do people's internal maps and models of these networks look like? Here, we introduce graph learning, a growing and interdisciplinary field studying how humans learn and represent networks in the world around them. Specifically, we review progress toward understanding how people uncover the complex webs of relationships underlying sequences of items. We begin by describing established results showing that humans can detect fine-scale network structure, such as variations in the probabilities of transitions between items. We next present recent experiments that directly control for differences in transition probabilities, demonstrating that human behavior depends critically on the mesoscale and macroscale properties of networks. Finally, we introduce computational models of human graph learning that make testable predictions about the impact of network structure on people's behavior and cognition. Throughout, we highlight open questions in the study of graph learning that will require creative insights from cognitive scientists and network scientists alike. [ABSTRACT FROM AUTHOR]

We examine how a firm's centrality within a network of geographically proximate firms affects its competitive capabilities. Our study of the total population of one Spanish cluster of fishing firms shows that the effects of centrality on a firm's competitive capabilities are contingent on the effects of two relational characteristics of its direct ties: strength and degree of cognitive cohesion. Specifically, our results indicate that the centrality of a firm within the cluster network enhances its competitive capabilities as the strength of its direct ties increases. Furthermore, firms can capture the value of centrality for enhancing competitive capabilities with a combination of strong (or weak) direct ties and low (or high) degree of cognitive cohesion. We contribute to the network and strategy literatures by reconciling conflicting results with regard to the strategic benefits of a firm's centrality in a cluster and the relational characteristics of its direct ties. [ABSTRACT FROM AUTHOR]

Most innovation builds closely on existing knowledge and technology, delivering incremental advances on existing ideas, products, and processes. Sometimes, however, inventors make discoveries that seem very distant from what is known and well understood. How do individuals and firms explore such uncharted technological terrain? This paper extends research on knowledge networks and innovation to propose three main processes of knowledge creation that are more likely to result in discoveries that are distant from existing inventions: long search paths, scientific reasoning, and distant recombination. We explore these processes with a combination of a large and unique data set on outlier patents filed at the U.S. Patent and Trademark Office and interviews with inventors of outlier patents. Our exploratory analysis suggests that there are significant differences in the inventor teams, assignees, and search processes that result in outlier patents. These results have important implications for managers who wish to encourage a more exploratory search for breakthrough innovation. [ABSTRACT FROM AUTHOR]

Human learners acquire complex interconnected networks of relational knowledge. The capacity for such learning naturally depends on two factors: the architecture (or informational structure) of the knowledge network itself and the architecture of the computational unit--the brain--that encodes and processes the information. That is, learning is reliant on integrated network architectures at two levels: the epistemic and the computational, or the conceptual and the neural. Motivated by a wish to understand conventional human knowledge, here, we discuss emerging work assessing network constraints on the learnability of relational knowledge, and theories from statistical physics that instantiate the principles of thermodynamics and information theory to offer an explanatory model for such constraints. We then highlight similarities between those constraints on the learnability of relational networks, at one level, and the physical constraints on the development of interconnected patterns in neural systems, at another level, both leading to hierarchically modular networks. To support our discussion of these similarities, we employ an operational distinction between the modeller (e.g. the human brain), the model (e.g. a single human's knowledge) and the modelled (e.g. the information present in our experiences). We then turn to a philosophical discussion of whether and how we can extend our observations to a claim regarding explanation and mechanism for knowledge acquisition. What relation between hierarchical networks, at the conceptual and neural levels, best facilitate learning? Are the architectures of optimally learnable networks a topological reflection of the architectures of comparably developed neural networks? Finally, we contribute to a unified approach to hierarchies and levels in biological networks by proposing several epistemological norms for analysing the computational brain and social epistemes, and for developing pedagogical principles conducive to curious thought. [ABSTRACT FROM AUTHOR]