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The purpose of this study is to assess the opportunity for a distributed, networked open biomedical repository (OBR) using a knowledge management system (KMS) conceptual framework. An innovative KMS conceptual framework is proposed to guide the transition from a traditional, siloed approach to a sustainable OBR.

This paper reports on a cycle of action research, involving literature review, interviews and focus group with leaders in biomedical research, open science and librarianship, and an audit of elements needed for an Australasian OBR; these, along with an Australian KM standard, informed the resultant KMS framework.

The proposed KMS framework aligns the requirements for an OBR with the people, process, technology and content elements of the KM standard. It identifies and defines nine processes underpinning biomedical knowledge – discovery, creation, representation, classification, storage, retrieval, dissemination, transfer and translation. The results comprise an explanation of these processes and examples of the people, process, technology and content dimensions of each process. While the repository is an integral cog within the collaborative, distributed open science network, its effectiveness depends on understanding the relationships and linkages between system elements and achieving an appropriate balance between them.

The current research has focused on biomedicine. This research builds on the worldwide effort to reduce barriers, in particular paywalls to health knowledge. The findings present an opportunity to rationalize and improve a KMS integral to biomedical knowledge.

Adoption of the KMS framework for a distributed, networked OBR will facilitate open science through reducing duplication of effort, removing barriers to the flow of knowledge and ensuring effective management of biomedical knowledge.

Achieving quality, permanency and discoverability of a region’s digital assets is possible through ongoing usage of the framework for researchers, industry and consumers.

The framework demonstrates the dependencies and interplay of elements and processes to frame an OBR KMS.

The ability to manage the COVID-19 pandemic is contingent upon the ability to effectively manage its heterogeneous knowledge resources. Knowledge mapping represents a great opportunity to create value by bringing stakeholders together, facilitating comprehensive collaboration and facilitating broader in-depth knowledge sharing and transfer. However, identifying and analysing critical knowledge areas is one of the most important steps when creating a knowledge map. Therefore, the purpose of this paper is to appraise the critical knowledge areas for managing COVID-19, and thereby enhance decision-making in tackling the consequences of the pandemic.

The methodological approach for this study is a critical literature review, covering publications on knowledge management, knowledge mapping and COVID-19. EBSCOhost, PubMed, Scopus, Science Direct, TRID, Web of Science and Wiley Online Library were searched for full text, peer-reviewed articles written in English that investigated on critical knowledge areas for managing the spread of COVID-19. After full screening, 21 articles met the criteria for inclusion and were analysed and reported.

The study revealed seven critical knowledge areas for managing the COVID-19 pandemic. These are cleaning and disinfection; training, education and communication; reporting guidance and updates; testing; infection control measures, personal protective equipment; and potential COVID-19 transmission in health and other care settings. The study developed a concept knowledge map illustrating areas of critical knowledge which decision-makers need to be aware of.

Providing decision-makers with access to key knowledge during the COVID-19 pandemic seems to be crucial for effective decision-making. This study has provided insights for the professionals and decision-makers identifying the critical knowledge areas for managing the COVID-19 pandemic.

The study advances the literature on knowledge management and builds a theoretical link with the management of public health emergencies. Additionally, the findings support the theoretical position that knowledge maps facilitate decision-making and help users to identify critical knowledge areas easily and effectively.

This study fills gaps in the existing literature by providing an explicit representation of know-how for managing the COVID-19 pandemic. This paper uses an objective and qualitative approach by reviewing related publications, reports and guidelines in the analysis. The concept map illustrates the critical knowledge areas for managing the COVID-19 pandemic.

Knowledge management (KM) is widely adopted by organisations to improve their performance and make informed decisions. Prior research has confirmed that Information Systems (IS) play a critical role in effective KM. The purpose of this study is to examine the existing literature on the role of cloud-based KM systems (C-KMS) in small- and medium-sized enterprise (SMEs) by understanding its impact on the five KM processes: knowledge acquisition, creation, storage, sharing and usage.

This study conducted a systematic literature review by examining 133 journal articles and 24 conference papers from 2010 to 2021 on the role of cloud computing in KM for SMEs.

This study revealed that there are numerous empirical analyses on KM processes and tools in SMEs; however, only few studies demonstrate how the whole gamut of KM processes can adopt cloud computing in SMEs. Therefore, SMEs are ineffective at KM with limited IS intervention. This paper offers a proposition on how C-KMS can impact all five KM process, thereby increasing its effectiveness of KM in SMEs. This study analysed the benefits of C-KMS that brings to SMEs in terms of availability, scalability, reliability, security and cost.

This systematic review is restricted to certain databases (ScienceDirect, Sage journals, Scopus and Emerald Insight) and specific IS conference proceedings to source articles. The selection of search criteria and time frame is based on this study’s assessment and choice. This study adds value to our understanding of the role of KM in SMEs, and it reinforces the role of cloud computing in effectively managing knowledge in SMEs. The proposal of C-KMS for the enhancement of KM has significant implications for SMEs to effectively use knowledge for their survival and superior performance.

This study suggests three practical implications. First, adopting and using C-KMS provide a strong foundation to manage knowledge for SMEs in a cost-effective way. Second, C-KMS improves the effectiveness of KM by increasing availability of knowledge artifacts, which in turn aids SMEs’ growth. Third, C-KMS is useful to codify SME’s knowledge, and accordingly supports employees to acquire and use knowledge based on their requirements.

This study discussed C-KMS with contemporary social issues, such as the COVID-19 pandemic challenges for SMEs and demonstrated how C-KMS can support SMEs to handle such crises by managing knowledge effectively.

This research highlights the importance of the implementation of a C-KMS for the enhancement of KM in SMEs. The review provides empirical evidence on the challenges faced by SMEs regarding KM, as they often only have enough resources to focus on a single KM process, predominantly knowledge sharing. Consequently, a holistic approach to KM cannot be realised by SMEs. In this context, the findings of this study offer theoretical and practical insights into the role of cloud computing by addressing the challenges of KM in SMEs.

This chapter takes a critical look at the sociological notion of ‘medicalisation’ in relation to recent trends and developments in neuroscience, neurotechnology and society, taking memory, medicine and the brain as our prime focus and the disease category of mild cognitive impairment (MCI) as our empirical case study. Five relational nexuses in particular are identified as relevant to these developments and debates, namely the bio-psych nexus, the pharma-psych nexus, the selves-subjectivity nexus, the wellness-enhancement nexus, and the neuroculture-neurofuture nexus. We show that developments in memory medicine and the shifting boundaries of cognitive health, as embodied and expressed in the case of MCI, shed further valuable light on these issues and the interconnectivity of these relational nexuses. As an emergent disease and susceptibility category, MCI illuminates not only the fuzzy boundaries between normal and abnormal cognitive functioning, but also the working of neuroscientific, neurocultural and pharmacological interests, which, in this case, are already claiming MCI as the next locus of enhancing the mind and optimising aging. Thinking both within and beyond medicalisation challenges us to find new ways to critically understand the ideas about life and health as they travel, translate or migrate from (neuro)scientific and clinical spheres to cultural life and patient experience.

This work shows the results of a systematic literature review on biomedical text mining. The purpose of this study is to identify the different text mining approaches used in different application areas of the biomedical domain, the common tools used and the challenges of biomedical text mining as compared to generic text mining algorithms. This study will be of value to biomedical researchers by allowing them to correlate text mining approaches to specific biomedical application areas. Implications for future research are also discussed.

The review was conducted following the principles of the Kitchenham method. A number of research questions were first formulated, followed by the definition of the search strategy. The papers were then selected based on a list of assessment criteria. Each of the papers were analyzed and information relevant to the research questions were extracted.

It was found that researchers have mostly harnessed data sources such as electronic health records, biomedical literature, social media and health-related forums. The most common text mining technique was natural language processing using tools such as MetaMap and Unstructured Information Management Architecture, alongside the use of medical terminologies such as Unified Medical Language System. The main application area was the detection of adverse drug events. Challenges identified included the need to deal with huge amounts of text, the heterogeneity of the different data sources, the duality of meaning of words in biomedical text and the amount of noise introduced mainly from social media and health-related forums.

To the best of the authors’ knowledge, other reviews in this area have focused on either specific techniques, specific application areas or specific data sources. The results of this review will help researchers to correlate most relevant and recent advances in text mining approaches to specific biomedical application areas by providing an up-to-date and holistic view of work done in this research area. The use of emerging text mining techniques has great potential to spur the development of innovative applications, thus considerably impacting on the advancement of biomedical research.

Enormous amount of biomedical wastes (BMW) produced everyday across the world. Management of BMW depends on adherence to protocol. BMW management at generation point, definitely, depends upon the awareness, attitudes and practises of health-care staff, the purpose of this study will assess the awareness, attitude and practise regarding different aspects of BMW.

An observational with appropriate checklists, and a cross-sectional study, involving questionnaires, was conducted during 7-24 January 2016. The existing system of BMW management, funds, resources, etc., knowledge, attitude and practises about BMW were assessed amongst 273 health-care workers in selected public health-care institutes of Karnataka.

Of 273 study participants, majority (54%) of them have not received any training pertaining to BMW. The results showed a poor level of knowledge and awareness of BMW management amongst health-care personnel. Merely, 43% of the participants correctly knew the categorization of BMW and its disposal in proper colour-coded bins/bags. Awareness is very poor amongst the lower age group, male participants, lab-technicians/pharmacists and supporting staff. Doctors were good at theoretical knowledge such as rules, legislation and public-health importance of BMW management than the practical aspects such as categorization and colour-coding. Further, the attitude of health-care staff is favourable about BMW. Immunization for hepatitis-B was very poor amongst waste handlers (43%).

As the awareness and practise regarding BMW management were poor across different health-care staff there is a need to conduct periodic training and regular monitoring with special focus on the proper use of personal protective equipment. Further, precautionary immunization should be provided, especially waste handlers and sanitary workers.

The authors contribute to the literature on leadership by investigating how characteristics of principal investigators (PIs) affect innovation performance, and how collaborative and non-collaborative projects moderate this relationship within the context of inter-organisational research projects.

The authors analysed panel data from the National Science and Technology Information Service on 171 research projects within a biomedical and regenerative medicines programme overseen by the Korea Health Industry Development Institute. The authors used a hierarchical regression model, based on the ordinary least squares method, to examine the relationship between PI characteristics and performance, considering both quantity and quality.

The results show that the characteristics of PIs have diverse effects on the quantity and quality of innovation performance. Gender diversity within PIs negatively affects the quality of innovation performance, while the capacity of PIs positively influences it. Moreover, the degree of PI’s engagement is positively associated with the quantity of innovation performance but does not have a significant relationship with the quality of performance. In terms of moderating effects, collaborative projects with multiple leaders seem less reliant on PI capacity than non-collaborative projects led by a single leader, in terms of innovation performance.

The results contribute significantly to the literature on innovation management by examining the role of leadership in collaborative environments to enhance innovation performance, addressing the need for empirical evidence in this area. Analyses of PI characteristics in government R&D management can lead to improved team performance, more efficient processes and effective resource allocation, ultimately fostering innovation.

This paper aims to explore how the cross-fertilization of knowledge and technologies in EU-funded research projects, including serious games and gamification, is influenced by the following variables: multidisciplinarity, knowledge base and organizations (number and diversity). The interrelation of actors and projects form a network of innovation. The largest contribution to cross-fertilization comes from the multidisciplinary nature of projects and the previous knowledge and technology of actors. The analysis draws on the understanding of how consortia perform as an innovation network, what their outcomes are and what capabilities are needed to reap value.

All the research projects including serious games and/or gamification, funded by the EU-Horizon 2020 work programme, have been analyzed to test the hypotheses in this paper. The study sample covers the period between 2014 and 2016 (June), selecting the 87 research projects that comprised 519 organizations as coordinators and participants, and 597 observations – because more organizations participate in more than one project. The data were complemented by documentary and external database analysis.

To create cross-fertilization of knowledge and technologies, the following emphasis should be placed on projects: partners concern various disciplines; partners have an extensive knowledge base for generating novel combinations and added-value technologies; there is a diverse typology of partners with unique knowledge and skills; and there is a limited number of organizations not too closely connected to provide cross-fertilization.

First, the database sample covers a period of 30 months. The authors’ attention was focused on this period because H2020 prioritized for the first time the serious games and gamification with two specific calls (ICT-21–14 and ICT-24–16) and, second, for the explosion of projects including these technologies in the past years (Adkins, 2017). These facts can be understood as a way to push the research to higher technology readiness levels (TRLs) and introducing the end-user in the co-creation and co-development along the value chain. Second, an additional limitation makes reference to the European focus of the projects, missing strong regional initiatives not identified and studied.

This paper has attempted to explore and define theoretically and empirically the characteristics found in the cross-fertilization of collaborative research projects, emphasizing which variables, and how, need to be stimulated to benefit more multidisciplinary consortia and accelerate the process of innovation.

An investigation of the marketing approaches for biomedical science small- and medium-sized enterprises (SMEs) and organisations in the United Kingdom (UK) was carried out; the research question is as follows: Should the marketing approaches for biomedical science SMEs change as their product or service moves along the development life cycle?

An online questionnaire was used, which petitioned biomedical science SMEs and organisations in the UK to investigate the marketing tactics or approaches used for the different products and services they offered; the results were analysed by comparing the results to recognised marketing approaches in the literature and by mapping those approaches against the established technology readiness levels (TRLs).

A direct relationship was seen between the status of a product or service in relation to its development life cycle, and therefore the relevant TRL of the product and service, and the appropriate marketing approach for that product or service.

This paper offers a contribution to the literature, in which a theoretical framework is proposed for determining the appropriate marketing approach for biomedical science SMEs by understanding the maturity of the products offered by a company using the established TRL. The theoretical framework maps the TRL against known marketing approaches; this framework should be used as a guide for biomedical science SMEs as a tool to refine and evolve their overall marketing approach as the product portfolio matures along the TRL.

The huge volume of biomedical literature provides a nice opportunity and challenge to induce novel knowledge by finding some connections among logical‐related medical concepts This paper aims to propose a semantic‐based knowledge discovery system for mining novel connections from large online digital libraries.

The method takes advantages of the biomedical ontologies, MeSH and UMLS, as the source of semantic knowledge. A prototype system, Biomedical Semantic‐based Knowledge Discovery System (Bio‐SbKDS), is designed to uncover novel hypothesis/connections hidden in the biomedical literature. Using only the starting concept and the initial semantic relation derived from UMLS, Bio‐SbKDS can automatically generate the semantic types as category restrictions for concepts. Using the semantic types and semantic relations of the biomedical concepts, Bio‐SbKDS can identify the relevant concepts collected from Medline in terms of the semantic type and generate the novel hypothesis between these concepts based on the semantic relations.

The system successfully replicates Dr Swanson's famous discoveries: Raynaud disease/fish oil automatically, and generates much less intermediate concepts and spurious connections.

The method takes full advantage of the semantic knowledge of the biomedical concepts, compared with previous approaches, our methods generate much less but more relevant novel hypotheses. Another significant advantage over other traditional approaches is that our method requires much less human intervention in the discovery procedure.