Humanner Posted July 2, 2021 Share Posted July 2, 2021 (edited) the active participation of the public in scientific research projects, is a rapidly expanding field in open science and open innovation. It provides an integrated model of public knowledge production and engagement with science. As a growing worldwide phenomenon, it is invigorated by evolving new technologies that connect people easily and effectively with the scientific community.Catalysed by citizens’ wishes to be actively involved in scientific processes, as a result of recent societal trends, it also offers contributions to the rise in tertiary education.In addition, citizen science provides a valuable tool for citizens to play a more active role in sustainable development. https://www.uclpress.co.uk/products/107613 How can we help build the Collective Intelligence of our society? Edited July 2, 2021 by Humanner Link to comment Share on other sites More sharing options...
Humanner Posted July 9, 2021 Author Share Posted July 9, 2021 Do you know any similar Citizen scientists innovation support program in the UK?https://coactproject.eu/https://coeso.hypotheses.org/https://sshopencloud.eu/ Link to comment Share on other sites More sharing options...
Humanner Posted May 6, 2022 Author Share Posted May 6, 2022 (edited) A knowledge commons is a combination of intelligent information representation and the openness, governance, and trust required to create a participatory ecosystem whereby the whole community maintains and evolves this shared information space. A knowledge commons is predicated on a central movement from a data society to a knowledge and wisdom society. A knowledge commons is a core ‘technology’ (defined to include both hardware/software and cultural technologies) of the solution for a more inclusive, open, and equitable community. In this participatory ecosystem, the whole community maintains and evolves the shared space. Although graph databases are a relatively new development in computer science, learning theory has indeed traced human cognition as a progression from disconnected concepts to a graph organization. Edited May 6, 2022 by Humanner 1 Link to comment Share on other sites More sharing options...
Humanner Posted July 11, 2022 Author Share Posted July 11, 2022 The tech entrepreneurial community is too focused on simply growing their business and generating greater revenue for this community to really change the status quo. The social innovation community is generally focused on individual social and environmental issues, while largely leaving systems unchanged. We need a new kind of innovation capacity in the city for it to really move forwards on these key challenges. One that is proportional to and of a kind that is relevant for the major transformations that are underway. What is needed is a different kind of innovation, a kind that is able to transform systems. Imagine a city where systems work, and they work for everyone. This is certainly not the world we live in. We currently live with a set of Industrial Age systems that were either not designed in the first place or poorly designed. They do not integrate properly with each other so we get silos and fractured systems. These systems create negative externalities that accumulate and lead to periodic systemic crises instead of effectively adapting, evolving, and regenerating. How do we get to a world where systems are better designed, integrated, systems that create positive externalities, that adapt and regenerate effectively? Instead of linear supply chains that create mounting waste, supply chains systems that are circular instead. Where food systems are circular. Where education systems are not a factory model of batch processing but learnercentered. Where finance is decentralized, health systems integrated, infrastructure adaptive. Where systems work and they work together in the way that is needed. Business and innovation as usual will not get us there. We need to learn something new, we need to learn how to innovate in systems In the coming decades, a huge wave of technology will drive mass automation across many industries and spheres of human activity. The development and expansion of emerging technology will automate basic information, services, and managerial work. This will enable new forms of networked organizations with wholly new business models using digital token economies. Along with this major changes in institutions and governance will need to be made to realize the benefits of emerging technology to our outdated political systems and public service provisioning models. The digital platforms of today that already create so many tensions with existing institutions will evolve into ever more powerful, incentivized networks in the coming years. Yet, there is no single solution to these challenges, no policy, no plan, nor a single organization that can help us navigate this transition. Success is predicated upon adaptive capacity. Adaptive capacity at scale across a wide variety of systems and domains - the innovation capacity of individuals and organizations. These kinds of transformations cannot be achieved through any summation of single-point interventions. They require a new kind of innovation, one that is able to coordinate across the different elements of a system in order to align them towards making the needed structural changes. The winners in this new world will not be one-off unicorns, but those who create and invest in the development of an infrastructure to enable innovation ecosystems, and networks of collaboration that bring into being new forms of coordination. The societies that reap the most benefits will be those that are able to do this in a holistic fashion. The concept of innovation itself will be increasingly expanded beyond that of technical innovation to see the need for social innovations. To innovate, adapt, and transform; to create not just new autonomous cars or solar panels but in the very patterns and structure of the institutions that coordinate human beings in social interaction, in governance, in economic activity. Shifting the paradigm from how can we create an autonomous car, to how can we create a society, a city, a public transport system so attractive that it renders autonomous cars in limited demand. Shifting up the value chain to groundbreaking social innovation at scale will be key to maintaining relevance and creating quality of life. Expanding beyond the box of a given product or service to build the capacity of individuals, organizations, cities, and regions for transformational change. Many of these innovations will be on the micro-level, incremental developments in individual products and services, but more than this innovation will be required on the macro-level for the transformation of whole systems - we call this systems innovation. What the city needs is innovation across a wide variety of systems but this alone will not be sufficient to realize the kind of transformative changes that are needed, as this innovation will also need to integrate into broader systems change processes. What is needed is an ecosystem approach where many diverse and smaller initiatives can be synergistically combined into large change initiatives that are working at the level of the whole system. Smart Citizens in Smart Cities - Semantic Multi Layered Social Innovation Platform Forecasting - Macro Trends / Futuristic visioners, Academics - Researchers, CSS, Universities, Uni students, think thanks, policy makers Digital Innovation - TechMinded individuals, Open Source projects, Innovation Hubs, Local Public Service, Council, Local Gov Agencies, etc (no political parties) Communities, NGO, Nonprofit, Social Service, Social Enterprise, CSS, etc General Public - Neighborhood, Hobby, etc (Facebook kind of knowledge builders by sharing information) Glocal Business - Start-up support, Virtual Gig Volunteers, Bargains brackets, Networking The base philosophy of the platform: Service learning - learning flow with support from different expert levels 1/ You share any information from the web (like Facebook) 2/ Saved in internet archive system (like Wayback machine) 3/ Semantic ontology + AI analysis and interlinking 4/ User can have personal knowledge graph What I learned What I need to learn My interest - Identity Points (hobby, health, problem related, religion, etc) community desk research Collect and analyse with different ontology can share and follow each collections (import part or all) Decentralized Economies of Knowledge Commons A knowledge commons is a core ‘technology’ (defined to include both hardware/software and cultural technologies) of the solution for a more inclusive, open, and equitable space community. In this participatory ecosystem, the whole community maintains and evolves the shared space. We believe that the path towards creating this commons lies in an embrace of radical collaboration, new scales of interaction, and the corresponding changes (in thinking, in community structure, and in support) that must accompany this movement. What Is A Knowledge Commons? A knowledge commons includes 1) a technical knowledge representation system and a 2) a social community system for producing and governing the knowledge network. Below, we describe examples of each of these systems, building on the following elements: Knowledge Graph (KG): information structured into a graph form by a specific data model/schema/ontology that defines entities (objects, events, situations or abstract concepts) and their relationships. It is a collection of interlinked descriptions of entities – objects, events or concepts. An example is DBpedia [undefined]. Knowledge Network (KN): Connected knowledge graphs. Knowledge networks construct linkages between disparate knowledge bases. An example is the Linked Open Data Cloud (https://lod-cloud.net/). Knowledge Community: The knowledge network provided in a manner to build community around it--connecting the traditional technological to a cultural technological component. An example is the full complement of Wikimedia Foundation projects and chapters: (https://www.wikimedia.org/). The Knowledge Commons is a combination of these three pieces. The knowledge graph is the first layer of the technical composition of the knowledge commons. Multiple knowledge graphs are then organized into a knowledge network (KN). Knowledge networks construct linkages between disparate knowledge bases. An example is the Linked Open Data Cloud (https://lod-cloud.net/). From Knowledge Graphs and Networks to A Knowledge Commons In itself, the knowledge network will break down technical/disciplinary silos and create a system for more effective data sharing and collective understanding. Link to comment Share on other sites More sharing options...
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