Developing a knowledge ecosystem for large-scale research infrastructure

Large-scale research infrastructures (RIs), such as MAX IV and European Spallation Source in Lund, Sweden, are considered critical for advancing science and addressing social challenges. These research facilities are central to research, innovation, and education; in playing a key role in developing and disseminating knowledge and technology. In this study, we develop a conceptual framework of a knowledge ecosystem for large-scale RIs. The study is explorative, with primary data from 13 interviews with key informants from different stakeholders in academia, industry, and policy. Secondary data were obtained from reports from national agencies that develop and operate research facilities and from industrial and regional governmental reports, internal reports, newsletters, and information from the facilities’ websites. We find that academia, industry, and policy, together with four themes, have an effect on the value proposition of these facilities, on geographical distances (nodes), catalysts, platforms, and hubs. Therefore, they will affect the structure and design of a knowledge ecosystem. Our framework explains knowledge ecosystem structure and design

IT Service Management Knowledge Ecosystem – Literature Review and a Conceptual Model

Information Technology Service Management (ITSM) is a customer-centric approach to manage IT Services in order to provide value to the business. The ITSM Knowledge ecosystem comprises multiple knowledge areas including process frameworks, technology tools and skills. Organisations struggle to comprehend the ecosystem due to the sheer volume and dynamic nature of the business technology environment. A Systematic Literature Review was conducted to understand the state of the current research in ITSM knowledge ecosystem. The review indicated that the focus of the existing research is skewed towards process frameworks knowledge area neglecting tools and training. The approach proposed in the extant research fails to provide a holistic view of the ecosystem. To overcome the limitations a conceptual model is proposed based on Knowledge Commons theory

Experiencing information use for early career academics' learning: a knowledge ecosystem model

Purpose This study explores the informed learning experiences of early career academics while building their networks for professional and personal development. The notion that information and learning are inextricably linked via the concept of ‘informed learning’ is used as a conceptual framework to gain a clearer picture of what informs early career academics while they learn and how they experience using that which informs their learning within this complex practice: to build, maintain and utilise their developmental networks. Methodology This research employs a qualitative framework using a constructivist grounded theory approach (Charmaz, 2006). Through semi-structured interviews with a sample of fourteen early career academics from across two Australian universities, data were generated to investigate the research questions. The study used the methods of constant comparison to create codes and categories towards theme development. Further examination considered the relationship between thematic categories to construct an original theoretical model. Findings The model presented is a ‘knowledge ecosystem’, which represents the core informed learning experience. The model consists of informal learning interactions such as relating to information to create knowledge and engaging in mutually supportive relationships with a variety of knowledge resources found in people who assist in early career development. Originality/Value Findings from this study present an alternative interpretation of informed learning that is focused on processes manifesting as human interactions with informing entities revolving around the contexts of reciprocal human relationships

Towards an agriculture knowledge ecosystem :A social life network for farmers in Sri Lanka

We have developed and successfully trialled a Social Life Network (SLN); a Mobile Based Information System to support farming activities in Sri Lanka. It provides information required to support activities such as crop selection and cultivation planning in the context of farmer, farm location, season and task being performed. The system also provides a facility for farmers to sell farming related products and services to other farmers. The final system architecture evolved through a series of iterative relevance and design cycles based on Design Science Research methodology. In the first relevance cycle we identified farmer information needs, their current decision making patterns, and some possible ways to enhance their decision making process. In the first design cycles we developed the initial prototype to visualise a possible solution and in subsequent cycles a crop ontology to reorganise published crop information that would be queried in context and processes to empower farmers. Next we went through 2 cycles of creating functional prototypes, field testing with farmers and improving these to arrive at the final system. We noted that this system can enhance the flow of information in the agriculture domain by aggregating or disaggregating information produced by some stakeholders to be consumed by others. Based on this observation the overall architecture was reconceptualised as a Digital Knowledge Ecosystem

From Finnish AEC knowledge ecosystem to business ecosystem: lessons learned from the national deployment of BIM

Government actors, public agencies, industry and academics have struggled to change the rules of the existing business ecosystem to support the networked practices that were envisioned back in the 1980s with the introduction of building information modelling (BIM). Despite the industry’s far-reaching technological capabilities, BIM has primarily assumed productivity improvement by individual firms, which has not lead to a systemic change in the Finnish architecture, engineering and construction (AEC) business ecosystem. A field study of the Finnish AEC industry has resulted in a critical understanding of why successful and intensive R&D at a national level and wide adoption of BIM technology in Finland has not led to the expected systemic evolution of its AEC business ecosystem. Additionally, a methodology based on inductive grounded theory and historical analysis has been used to capture and identify the evolving and dynamic relationships between various events and actors between 1965 and 2015, which, in turn, has aided in the identification and characterisation of the knowledge and innovation ecosystems. The research findings provide insights for BIM researchers and governments in terms of establishing new policies that will better align BIM adoption with the systemic evolution of business practices in the AEC business ecosystem

A Grand Challenges-Based Research Agenda for Scholarly Communication and Information Science [MIT Grand Challenge PubPub Participation Platform]

Identifying Grand Challenges A global and multidisciplinary community of stakeholders came together in March 2018 to identify, scope, and prioritize a common vision for specific grand research challenges related to the fields of information science and scholarly communications. The participants included domain researchers in academia, practitioners, and those who are aiming to democratize scholarship. An explicit goal of the summit was to identify research needs related to barriers in the development of scalable, interoperable, socially beneficial, and equitable systems for scholarly information; and to explore the development of non-market approaches to governing the scholarly knowledge ecosystem. To spur discussion and exploration, grand challenge provocations were suggested by participants and framed into one of three sections: scholarly discovery, digital curation and preservation, and open scholarship. A few people participated in three segments, but most only attended discussions around a single topic. To create the guest list of desired participants within our three workshop target areas we invited a distribution of expertise providing diversity across several facets. In addition to having expertise in the specific focus area, we aimed for the participants in each track to be diverse across sectors, disciplines, and regions of the world. Each track had approximately 20-25 people from different parts of the world—including the United States, European Union, South Africa, and India. Domain researchers brought perspectives from a range of scientific disciplines, while practitioners brought perspectives from different roles (drawn from commercial, non-profit, and governmental sectors). Notwithstanding, we were constrained by our social networks, and by the location of the workshop in Cambridge, Massachusetts— and most of the participants were affiliated with US and European institutions. During our discussions, it quickly became clear that the grand challenges themselves cannot be neatly categorized into discovery, curation and preservation, and open scholarship—or even, for that matter, limited to library science and information sciences. Several cross-cutting themes emerged, such as a strong need to include underrepresented voices and communities outside of mainstream publishing and academic institutions, a need to identify incentives that will motivate people to make changes in their own approaches and processes toward a more open and trusted framework, and a need to identify collaborators and partners from multiple disciplines in order to build strong programs. The discussions were full of energy, insights, and enthusiasm for inclusive participation—and concluded with a desire for a global call to action to spark changes that will enable more equitable and open scholarship. Some important and productive tensions surfaced in our discussions, particularly around the best paths forward on the challenges we identified. On many core topics, however, there was widespread agreement among participants, especially on the urgent need to address the exclusion of knowledge production and access of so many people around the globe, and the troubling overrepresentation in the scholarly record of white, male, English-language voices. Ultimately, all agreed that we have an obligation to better enrich and greatly expand this space so that our communities can be catalysts for change. Towards a more inclusive, open, equitable, and sustainable scholarly knowledge ecosystem: Vision; Broadest impacts; Recommendations for broad impact. Research landscape: Challenges, threats, and barriers; Challenges to participation in the research community; Restrictions on forms of knowledge; Threats to integrity and trust; Threats to the durability of knowledge; Threats to individual agency; Incentives to sustain a scholarly knowledge ecosystem that is inclusive, equity, trustworthy, and sustainable; Grand Challenges research areas; Recommendations for research areas and programs. Targeted research questions, research challenges: Legal economic, policy, and organizational design for enduring, equitable, open scholarship; Measuring, predicting, and adapting to use and utility across scholarly communities; Designing and governing algorithms in the scholarly knowledge ecosystem to support accountability, credibility, and agency; Integrating oral and tacit knowledge into the scholarly knowledge ecosystem. Integrating research, practice, and policy: The need for leadership to coordinate research, policy, and practice initiatives; Role of libraries and archives as advocates and collaborators; Incorporating values of openness, sustainability, and equity into scholarly infrastructure and practice; Funders, catalysts, and coordinators; Recommendations for integrating research, practice, and policy

Exploring Pathways from Data to Knowledge to Insights in the Pharmaceutical Industry: ‘Introducing the Pharmaceutical Knowledge Ecosystem’

The ecosystem of how the pharmaceutical industry acquires data, transforms these data into tangible knowledge, and derives valuable insights throughout the process, is highly complex. Data, information, knowledge, and the resulting insights, are necessary to support decision- making, manage risk, problem solve, ensure product realisation, enable continual improvement, and enhance operational effectiveness. Building on the fundamental concepts established in the well-known Data Information Knowledge Wisdom (DIKW) hierarchy, this paper reviews the basic concepts involved in the DIKW pathway and begins to relate these concepts to both established capabilities (e.g., PAT), existing requirements (e.g., data integrity), and emerging trends in the industry (e.g., industry 4.0). This paper introduces additional research studies which the Pharmaceutical Regulatory Science Team (PRST) is considering, regarding how one might apply systems thinking concepts to develop a framework which will enable key stakeholders (Industry, Regulatory and Academia) to better relate the many elements of this ecosystem. The paper concludes by identifying preliminary foundational principles which could form the basis of such a framework, coined by the authors as ‘The pharmaceutical knowledge ecosystem’, and makes the case for further exploration of this concept

Smart Platform Evolution for Sustainable Open Innovation: Implications for STEM Youth Programs

☞ An emerging global platform ecosystem (e g Amazon, Apple, Facebook, Google) ☞ Continues to involves a complexity of knowledge ecosystem and a variety of internal and external sources for innovative opportunities Chesbrough 2003 ☞ To sustain an effective open innovative model , a better understanding of the platform economy, and a sharing economy business model need ( Ritter & Schanz , 2019) ☞ The younger generation increasingly needs knowledge and application of OI to meet the current trend: OI education will be very important more and more to STEM high school students