Co-innovation – new approaches to translating research outputs for innovation in agriculture
•Download as PPTX, PDF•
1 like•884 views
A presentation exploring how research outputs can be used more effectively in agriculture. By focusing on various models of innovation, this presentation considers a shift in thinking from research outputs as a product to a more networked and interactive approach involving stakeholders. The research project VALERIE is used as a case study to evidence this approach - translating promising research into end-user content.
Recommended
Recommended
More Related Content
What's hot
What's hot (20)
Viewers also liked
Viewers also liked (20)
Similar to Co-innovation – new approaches to translating research outputs for innovation in agriculture
Similar to Co-innovation – new approaches to translating research outputs for innovation in agriculture (20)
More from Countryside and Community Research Institute
More from Countryside and Community Research Institute (20)
Recently uploaded
Recently uploaded (20)
Co-innovation – new approaches to translating research outputs for innovation in agriculture
- 1. Co-innovation – new approaches to translating research outputs for innovation in agriculture Julie Ingram
- 2. Outline • Models of Innovation • Translating research • European policy context • CCRI research project approach • Conclusions
- 3. Innovation Transformation in European agriculture has brought about an evolution of ideas about knowledge and innovation Linear model of innovation and adoption Interactive innovation systems
- 4. Extension/advice Farmer From a linear Agricultural Knowledge System to… • Reorientation of the CAP -increasing emphasis on sustainability • Diverse actors with diverse knowledge needs • Economic drivers- competitiveness • Advice/extension/research funding reforms - privatisation, demand driven Research
- 5. A networked Agricultural and Knowledge Innovation System Government driven and funded integrated AKS pluralistic and responsive AKIS EU SCAR AKIS Report 2012
- 6. Innovation Science-driven - Innovation is development of products and technologies by science for end users • carried out by research organisations with little involvement of users; outputs are judged on scientific quality
- 7. Innovation-driven - networks of producers and users of knowledge are integral to the research process and outputs are judged on relevance • Innovation is described as an emergent product ‘co-produced’ through interactions between multiple actors Innovation
- 8. Challenges in translating research DeMeyer 2014 Modified from: Birner et al. 2006 Science continues to be essential for innovation But challenges in translating research into practice Disconnect between research and farming
- 9. combined science-driven and innovation-driven research ensures research is better adapted to needs increased collaboration between researchers and end users integration of different actors Translating research more effectively Innovation: the process of creating and putting into use combinations of knowledge from many different sources
- 10. New partnership under the Common Agricultural Policy combining • Rural development programme - linking farmers, advisors, researchers, and businesses (etc.) in operational groups • New programme of research funding (H2020)- multi actor approach to boost translation of research • EIP Network facility European Innovation Partnership „Agricultural Productivity and Sustainability“
- 11. Valorising European Research for Innovation in Agriculture and Forestry www.valerie.eu EU Seventh framework
- 12. • Outreach and translation of results into field practices from EU and nationally funded research projects (agriculture and forestry) is limited • The overall aim of VALERIE is to boost the outreach of research by facilitating the integration into innovative field practices VALERIE - background and overall aim
- 13. • Review, extract and summarise knowledge - from research projects • Translate “promising” research results into formats for end-users • Work with stakeholders in case studies to identify innovation needs and to assess, refine and test research results • Use expert and stakeholders’ knowledge to create a structured vocabulary • Develop a ‘smart’ search engine (AskValerie.eu) for research outputs, for use by farm/forestry community and embed this in EIP-NF The VALERIE objectives
- 14. The VALERIE approach Extract knowledge for innovation • Extract, screen, summarise • Create knowledge base for AskValerie.eu • Identify gaps Create data infrastructure • Themes structure the extraction • Structured vocabulary Case studies on innovation • Articulate knowledge needs • Evaluate solutions Create smart search tool AskValerie.eu Integrate into EIP NF Stakeholder driven Thematic driven
- 15. The VALERIE approach • Theme-driven approach- 6 thematic domains structure the research extraction and summaries • Stakeholder-driven approach - co-innovation in 10 case studies • Structured vocabularies –to structure data and create AskValerie It combines the benefits of Interactive innovation model with effective translation of research
- 16. Theme-driven approach Research is extracted and summarised according to the following themes: • Crop rotation, soil cover management, IPM • Ecosystem and social services in agriculture and forestry • Soil management as an integrated agro-ecol system • Water management in agriculture • Sustainable integrated supply chain services & tools • Recycling and smart use of biomass and food waste
- 17. • Farmers, advisers, supply chain actors (SHs) in 10 case studies identify research needs • SHs apply, test and refine screened research outputs (structured by theme) for their innovation potential in the local context, and • assess viability of solutions and expose barriers Stakeholder driven approach
- 18. • Catchment management • Soil management under pigs • Forest-based bio economy • Herbicide reduction in arable crops • Soil fertility and pesticides reduction • Sustainable forestry • Irrigated maize and tomato • Bread wheat quality • Onion supply chain • Potato supply chain Case studies Red flags= case studies; green flags = partners
- 19. Series of meetings in case studies • Farmers identify research needs • Scientists search and retrieve ‘best matching’ information • Scientists translate science into end user format (Fact sheets) • Farmers review Fact sheets and feedback to scientists • Farmers test information- assess viability with trials Iterative process - repeat in 3-4 cycles Stakeholder driven approach
- 20. What are the possible reasons causing internal brown spots in potatoes? Is the variety Innovator known for internal brown spot problems and what could be the reason? Yes, Dutch advisors recognise the problem. They mention low calcium uptake as a possible reason. This is confirmed in research (ref). If low Calcium uptake is the main factor causing internal brown spot, how can variety differences be explained? Stakeholder driven approach
- 21. The VALERIE approach Extract knowledge for innovation • Extract, screen, summarise • Create knowledge base for. AskValerie.eu • Identify gaps Create data infrastructure • Themes structure the extraction • Structured vocabulary Case studies on innovation • Articulate knowledge needs • Evaluate solutions Create smart search tool AskValerie.eu Integrate into EIP NF Stakeholder driven Thematic driven Vocabulary
- 22. Create structured vocabulary • Expert vocabularies (concepts, issues, problems and questions) relevant to the 6 themes collected • SH vocabularies particular to cases studies are collected • Structured vocabulary created- used as a tool/retrieval filter to search best matching information to meet SH needs and to create AskValerie.eu
- 23. Search with Google, wiki or OrgEprint broad-leaved dock results of previous research in the agronomy & forestry domain VALERIE Search with VALERIE – find the golden documents VALERIE
- 24. AskValerie.eu • makes knowledge accessible to the end-users - farmers, foresters, advisers and researchers, extension orgs • understands the individual user: • It knows the context of the user • It understands the problem • It understands what possible solutions match the problem • will enable them to share their empirical knowledge, experience and views with peers across Europe
- 25. Can this approach provide a model for boosting the outreach of research?
- 26. Reflections on ‘doing’ co-innovation Co-innovation is not a recipe: there are elements of participatory and multi-stakeholder approaches: • social learning • combining formal knowledge with SH knowledge • stakeholder management • process facilitation • monitoring and evaluation
- 27. • Assumptions that SHs and researchers will engage • SHs take time to identify and articulate needs • Assumptions that scientists will find relevant research • Ambitious – raises SH expectations, require concrete outputs • Relationship building is important • Dealing with diversity • Who participates? Reflections on ‘doing’ co-innovation
- 28. Translating research and co-innovation DeMeyer 2014 Modified from: Birner et al. 2006 Operational groups Multi actors research projects
- 29. • Shows that co-innovation is more than SH consultation • Combines SH learning with utilising existing research outputs -benefits of science-driven and innovation driven • Mobilises SHs to assess their innovation demands and capture their knowledge for integration into AskValerie.eu • AskValerie.eu -translates promising research results into end- user content Conclusion: translating research and on-farm innovation
- 30. jingram@glos.ac.uk www.ccri.ac.uk Thank you for your attention
Editor's Notes
- reorientation of the CAP and the increasing emphasis on the economic, environmental, and social dimensions of sustainability As such farming has become more diverse and farmers and other rural actors need support in providing both public good and private goods and in negotiating new regulations. At the same time extension policy reforms of 1990s in many EU countries have seen a move away from government driven and funded AKS towards pluralistic, market-driven, multi-actor systems, in which private actors have come to play a larger role Aim to make the AKS more responsive to users’ needs, and hence more demand driven. One consequence however has been an increasing disconnect between research and farming as the traditional AKS, with its strong integration of public research, education and extension bodies, has become fragmented backdrop of economic volatility - Climate change threats etc
- AKIS is now an established framework for understanding innovation processes in the context of agriculture in Europe Useful concept to describe a system of innovation, with emphasis on the organisations involved, the links and interactions between them, the institutional infrastructure with its incentives and the budget mechanisms (EU SCAR 2012). There has been a move away from government driven and funded AKS towards pluralistic, market-driven, multi-actor systems, in which private actors have come to play a larger role
- Innovation- is a broad concept- two perspectives
- Innovation: The process of creating and putting into use combinations of knowledge from many different sources This knowledge may be brand-new, but usually it is new combinations of existing knowledge. Process of constant learning and adaptation Occurs through interaction between multiple stakeholders. For an invention to become an innovation, it has to be used by farmers ! DeMeyer 2014; Hall, 2001 From Systems of Innovation thinking Roling and Wagemakers, 1998
- Innovation encompasses much more than R&D but science continues to be an essential ingredient of innovation However in several EU countries there are challenges in translating results from research into practice, and in channeling practitioners’ demands for knowledge into research and advisory agendas Increasing disconnect between research and farming as the knowledge and innovation system has become fragmented
- EIP a new feature in the reformed Common Agricultural Policy which is trying to help farmers to get to grips with more sustainable and competitive agriculture by working EIP understanding of innovation is co-creation of innovation: speeds up the introduction of innovative ideas helps to target the research agenda helps relevant research to switch to a problem-solving mode
- combines the benefits of ‘learning networks’ /innovation driven with those of ‘linear’ dissemination modes/science driven - something that is considered essential for an optimal Agricultural Knowledge and Innovation System (AKIS) (EU SCAR 2012).
- Review, extract and summarise knowledge - from national, international and EU research projects - for innovation in agriculture and forestry (6 themes) Translate “promising” research results into formats for end-users (farmers, advisers, supply chain) Detailed objectives Mobilise practitioners /SH to assess their innovation demands & capture their knowledge for integration into AskValerie Translate “promising” research results into end-user content Integrate feedback from practitioners on innovations Refine & test applications of research results Reveal social, economic & cultural barriers to research uptake Elicit stakeholders’ knowledge, experience & innovation needs; for storage in the form of an ontology (WP4) Field-test AskValerie with SHs
- Review and summarise knowledge - from national, international and EU research projects and studies - for innovation in agriculture and forestry; with a focus on the six themes The project will extract, review, and wrap-up research outcomes and existing scientific information on selected themes, and with a special interest for innovative and applicable approaches. It will present the results in a format suited to end-users in the primary production sector, and will facilitate their integration into practices through a series of ‘case studies on innovation’. These have a regional orientation, and a focus on either specific commodities, on farming systems, or on the landscape scale. Consult stakeholders in ten case studies to identify knowledge gaps, assess technical and economic viability of innovative solutions (the summaries) and to reveal barriers to uptake Create a structured vocabulary ontology with SH in cs starting from the concepts that are relevant to each of the six themes then building though iterative process. Build Linked Open Data Infrastructure (LODI) based on themes Develop a ‘smart’ search engine for agricultural and forestry knowledge and research outputs, for use by farmers, foresters, advisers and researchers. This ‘Communication Facility’ (“AskValerie.eu”) will not only make new knowledge accessible to the end-users, such as extension organisations, but will also enable them to share their empirical knowledge, experience and views with peers across Europe. While the case studies (WP3) are the source for collecting empirical knowledge from practitioners, the work in WP2 has a focus on scientific knowledge contained in products from EU and international projects and studies (e.g., reports, databases, prototypes, scientific publications). Innovation requires effective communication between actors in the field, as well as frequent interaction between researchers and practitioners. To facilitate these interactions while injecting new knowledge into the process, this project will launch AskValerie search tool
- VALERIE consists of three major approaches. (1). Stakeholder-driven approach. Ten case studies set the central stage for the bottom-up approach of the project, aided by highly effective tools of web semantics and ontology. Cases are centred around a specific supply-chain, a farming sector or a landscape. The stakeholder communities (SHC) represent the natural networks engaged in innovation. They drive the process of articulating innovation needs, enabling the retrieval of precisely matching knowledge and solutions, and evaluating their potential in the local context. (2) Theme-driven approach. VALERIE retains six thematic domains that are at the heart of sustainable production and resource use. These six provide the back-bone for structuring the annotation and summarising activities, which in turn will provide a vast body of knowledge accessible via the Communication Facility (CF). WP2 extracts research and prepares in a format suited to end-users in the primary production sector, and will facilitate their integration into practices through a series of ‘case studies on innovation’. These have a regional orientation, and a focus on either specific commodities, on farming systems, or on the landscape scale. (3) Structured vocabularies . VALERIE will launch a search tool for the EIP-Networking Facility.
- In stakeholder communities (SHC) in each case study (WP3). Through a series of interviews and workshops, ‘vocabularies’ particular to that SHC are created. This involves the identification and description of concepts (issues, problems and questions) that are important to stakeholders. Usually, key concepts differ between user groups within a SHC (e.g., farmers, processing industry, retailer), and so all groups contribute their own concepts to the collective vocabulary for that case. The concepts are then structured into a formal hierarchy, defining how they relate to each other (WP4). Such a structured vocabulary captures already much of the empirical knowledge, and is called an ‘ontology’. It is utilised in the next step (WP2) by a powerful tool (retrieval filter) to search and retrieve context-sensitive, ‘best matching’ information, useful to address the needs of the SHC identified in WP3. This information is translated into end-user format (WP3), and presented to the SHC for feedback, thus completing one cycle. Intertwined with the ontology development (iterative cycle )- a series of participatory activities oriented towards co-innovation ‘vocabularies’ particular to that SHC are created. This involves the identification and description of concepts (issues, problems and questions) that are important to stakeholders. The concepts are then structured into a formal ontology. It is utilised in the next step (WP2) by a powerful tool (retrieval filter) to search and retrieve context-sensitive ‘best matching’ information, useful to address the needs of the SHC identified in WP3. This information is translated into end-user format (WP3), and presented to the SHC for feedback, thus completing one cycle. Ontological cycle At the same time - The research team will work together with the SHC to solve problems reflectively. Specifically they will apply, test and refine screened research outputs for their innovation potential in the local context, and will assess viability of solutions and expose barriers and bottlenecks that limit uptake of innovative solutions The project will extract, review, and wrap-up research outcomes and existing scientific information on selected themes, and with a special interest for innovative and applicable approaches.
- Regional diversity, cover all themes and actors It will present the results in a format suited to end-users in the primary production sector, and will facilitate their integration into practices through a series of ‘case studies on innovation’. These have a regional orientation, and a focus on either specific commodities, on farming systems, or on the landscape scale. Consult stakeholders in ten case studies to identify knowledge gaps, assess technical and economic viability of innovative solutions (the summaries) and to reveal barriers to uptake
- Refine and test applications of research results within reach for technical and economical viability of the innovative solutions Feedback on the potential for innovation from SH is used to refine innovations Reveal social, economic and cultural barriers to research uptake
- Create a structured vocabulary ontology with SH in cs starting from the concepts that are relevant to each of the six themes then building though iterative process. Build Linked Open Data Infrastructure (LODI) based on themes Develop a ‘smart’ search engine for agricultural and forestry knowledge and research outputs, for use by farmers, foresters, advisers and researchers. This ‘Communication Facility’ (“AskValerie.eu”) will not only make new knowledge accessible to the end-users, such as extension organisations, but will also enable them to share their empirical knowledge, experience and views with peers across Europe. While the case studies (WP3) are the source for collecting empirical knowledge from practitioners, the work in WP2 has a focus on scientific knowledge contained in products from EU and international projects and studies (e.g., reports, databases, prototypes, scientific publications). The cycle starts with the stakeholder communities (SHC) in each case study (WP3). Through a series of interviews and workshops, ‘vocabularies’ particular to that SHC are created. This involves the identification and description of concepts (issues, problems and questions) that are important to stakeholders. Usually, key concepts differ between user groups within a SHC (e.g., farmers, processing industry, retailer), and so all groups contribute their own concepts to the collective vocabulary for that case. The concepts are then structured into a formal hierarchy, defining how they relate to each other (WP4). Such a structured vocabulary captures already much of the empirical knowledge, and is called an ‘ontology’. It is utilised in the next step (WP2) by a powerful tool (retrieval filter) to search and retrieve context-sensitive, ‘best matching’ information, useful to address the needs of the SHC identified in WP3. This information is translated into end-user format (WP3), and presented to the SHC for feedback, thus completing one cycle. The cycle starts with the stakeholder communities (SHC) in each case study In interviews and workshops SH identify and describe concepts (issues, problems and questions) that are important to them The concepts are then structured into a formal hierarchy (ontology) defining how they relate to each other (WP4). Usually, key concepts differ between user groups within a SHC (e.g., farmers, processing industry, retailer), and so all groups contribute their own concepts to the collective vocabulary for that case. Case study groups led by extension partners - meet at least 4 times but aim for more WP2 search and retrieve ‘best matching’ information, to address the needs of the SHC identified in WP3 . At the same time the parallel theme driven approach continues WP2 search and retrieve relevant information and create summaries according to the 6 themes and these are presented to the SH in meetings This information is translated into end-user format example summaries and presented to the SHC for feedback
- Red circle denotes interaction space where support is porivded through H2020 and RDP and where porjects like VALERIE are active
- Shows that co-innovation is more than SH consultation Combines SH learning with utilising existing research outputs - co-innovation- benefits of science-driven research and innovation driven Mobilises SHs to assess their innovation demands and capture their knowledge for integration into AskValerie.eu AskValerie.eu -translates promising research results into end-user content- outcomes are filtered and tested and will be produced as Fact sheets for dissemination on and locally