AquaSmart Horizon 2020 Project Introduction
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AquaSmart Horizon 2020 Project Introduction
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AquaSmart Horizon 2020 Project Introduction
- 2. Big Data and Open Data Innovation and Take-up » AQUASMART focuses on innovation and technology transfer in multilingual data harvesting and analytics solutions and services » AQUASMART addresses cross-sectorial, cross-border and/or cross-lingual scope taking into account the users' and societal perspectives » AQUASMART’s consortium has companies dedicated to aquaculture activities with a clear business perspective of the project, which has contributed to the identification of verifiable milestones and market validation procedures
- 3. Innovation Action » AQUASMART accomplishes: › Actions primarily consisting of activities directly aiming at producing plans and arrangements or designs for new, altered or improved products, processes or services. › For this purpose it intends to include prototyping, testing, demonstrating, piloting, large-scale product validation and market replication.
- 4. AQUASMART Goal » The prime goal of AQUASMART is to accelerate innovation in Europe’s Aquaculture through: › technology transfer for the deployment of open data solutions › multilingual data collection and analytics solutions › turning the large volumes of heterogeneous aquaculture data that is distributed across the value chain, into an open cloud › Semantically interoperable data assets and knowledge.
- 5. AQUASMART Challenges » Technology transfer: › to tackle the existing state of the art appropriate tools and solutions » Innovation: › to improve existing business process and new business opportunities » Usability: › to build it for end-users, and deliver the appropriate training » Robustness: › to build for real world use, outside of the lab, cross-sectorial setting » Global: › multi-lingual, cross-border allowing seamless open data setting » Commercialisation: › to develop an effective market strategy
- 6. Bringing Big and Open Data Analytics as a Service to the Aquaculture Industry The Motto
- 8. Expected Results » Transform data into global knowledge. » Better view of the life to date of fish. » Better view of the living inventory (biomass) that exist in a farm. » Be able to analyze more data, in a seamless global way. » Understand the analysis at the “global” level. » Be able to make accurate estimations of the growth of the fish. » Minimizes the uncertainty of each local production process. » Substantial improvement of the company’s growth model
- 9. Development Methodology » Identification of business needs » Scoping of technology requirements » Technology transfer routines and validation in defined trials » Collection and analysis of data in Open Data Cloud setting » Specification and development of end-user training » High levels of stakeholder involvement to support adoption » Stakeholder exploitation of results, enhanced production » Market deployment and adoption activity » Promotion, execution of commercialization strategy
- 10. Current Technology / Solutions » Currently there is only empirical knowledge on the effect of data parameters to the growth, cost, health and production time of the fish. These parameters relationships can be very deep and difficult to be understood. › For example, a small change in the type or administration dosage or an enrichment that is given to rotifers that are then used to feed the fish larvae can have a very big effect on the malformations that the fish are going to develop during the growing phase. » Fish Farms struggle to interpret the data they capture and also use other data, in order to identify systematic relationships between the variables that affect production. » By doing so, there is the potential to dramatically improve the production in terms of feed conversion rate, cost, mortality, diseases, environmental impact, etc.
- 11. Required Management » Coordinate communications between all stakeholders including external experts » Ensure compliance with legal, ethical and privacy concerns with respect to data management
- 12. AQUASMART Open Data Cloud » Have an Open Data Cloud Platform with a UI to facilitate data visualization and connectors to enable transfer of multi-lingual information » Incorporate action and parameter recommendation algorithms accomplished with machine learning and classification to enable prescriptive analytics based on open data sources » It aims to create a cloud based platform with a backend based on machine learning and data mining techniques to provide assistance to aquaculture managers in the decision making process
- 13. AQUASMART Multi-lingual e-Training » Develop a training framework and strategy in line with the aquaculture companies training and open data policies; » Setup a training platform based in MOODLE, to deploy the training materials and to support the delivery of the training programme; » Develop and make available multi-lingual training material made of teaching manuals and e-learning material; » Develop the multi-lingual AQUASMART training programme, targeting main aquaculture user profiles » Deploy mobile capability extended from MOODLE for training purposes;
- 14. AQUASMART Trials and Validation » The aim is the deployment and validation of AQUASMART both in technical terms (stability, efficiency and usability) as well as in terms of business benefits, analysing the relationships in the data:
- 15. Engagement & Dissemination » Communicate the innovation capacity of the project to the target audience to encourage engagement with stakeholder participants, which are : › (Primarily) Aquaculture sector (Fish Farmers), regional Aquaculture associations. › (Additionally) Policy making, Standards community (e.g. CEN), other sectors (e.g. Transportation). » Timely and efficiently disseminate the project results to the audience (e.g. web social). » Promote awareness through the engagement of stakeholder participation. » Set in train the foundation for greater exploitation.
- 16. Market Deployment & Commercialisation » AQUASMART intends › to develop an efficient marketing strategy › Generate a database of potential customers and business contacts. This will serve as a critical mass of contacts for the commercialization of the project results. › Prepare a business plan for the future development and operation of AQUASMART › Set the guidelines for the necessary agreements between the partners
- 17. Conclusions » The AQUASMART project responds to the EU’s Blue Growth Strategy for marine and maritime sustainable growth and the Commission’s Europe 2020 Strategy. » Globally, nearly half the fish consumed by humans is produced by fish farms. Global production is forecasted to increase from 45 million tons in 2014 to 85 million by 2030, making the aquaculture industry the fastest growing animal food producing sector in the world. » The European Union needs an innovative aquaculture industry to meet rising seafood demand and to enhance its commercial stocks. › AQUASMART is a solution!!!
- 18. The End H2020 ICT-15-2014: 644715 Email: info@aquasmartdata.eu URL: www.aquasmartdata.eu Twitter: @AquaSmartData LinkedIn Group: AquaSmartData Facebook Page: www.facebook.com/Aquasmartdata
Editor's Notes
- Welcome to this AquaSmart training Course. The AquaSmart project is funded by the European Commission under the H2020 program. The drivers of AquaSmart Project is the usage of Open data and Big Data analysis along with Open Data Cloud Innovation to promote the Aquaculture Industry.
- The AquaSmart project is focused on innovation and technology transfer. It is a multilingual technology transfer solution that relies on data harvesting and analytic solutions and also to provide services on top of that. AquaSmart has a cross-sectorial, cross-border and cross-lingual scope that takes in account the user’s perspectives without disregarding the societal concerns. As for the business value of AquaSmart, it is important to notice that its consortium has companies dedicated to aquaculture activities with a clear contribution to the business perspective of the project.
- As for the Innovation Actions, AQUASMART accomplishes activities aiming at production plans and arrangement designs for new improved products processes and services. For that, it will include prototyping, testing, demonstrating and piloting on large-scale product validation that will be suitable for market replications.
- The prime goal of AQUASMART is to accelerate innovation in Europe’s Aquaculture through: - technology transfer for the deployment of open data solutions; - multilingual data collection and analytics solutions; - turning the large volumes of dispersed aquaculture data into an open cloud; - To produce semantically interoperable data assets and knowledge.
- The AquaSmart challenges are ambitious and aim at a strong contribution to the development of the aquaculture industry. Technology transfer: by tackling existing state of the art appropriate tools and solutions. Innovation: by improving existing business processes and open new business opportunities. Usability: to build it for end-users, and deliver the appropriate training. Robustness: to build it for real world use, outside of the lab, and in a cross-sectorial setting. Becoming Global: to be multi-lingual and cross-border independent, allowing seamless open data setting. Targeting Commercialization: to develop an effective market strategy.
- The AquaSmart project has a motto that is: To Bring Big and Open Data Analytics as a Service to the Aquaculture Industry.
- AquaSmart aims at collecting, organizing that data, and reason through big data analytics’ technics to generate results that make sense to the Aquaculture industry. Thus, as illustrated by these figures, without AquaSmart the big data, which the aquaculture industry produces is not understood, or not used at all. With AquaSmart, all the data intends to be collected in a formal way able to facilitate its analysis to improve any aquaculture stakeholders business process. This bring us to the conclusion that the use of big data in aquaculture really makes sense.
- The Expected Results for AquaSmart are: Transform data into global knowledge. Better view of the life to date of fish and current inventory. Be able to analyze and understand more data, in a seamless global way. Be able to make accurate estimations of the growth of the fish, minimizing uncertainty, Aiming at a substantial improvement of the company’s growth model.
- This slide presents the methodological approach followed in AquaSmart, which starts in the identification of business needs along with technological needs. By identifying the requirements for a desired solution, the process of technology transfer will be validated in adequately defined trials. The process consists in collecting and analyzing data in Open Data Cloud environment and producing multi-lingual adequate training. The whole process involves stakeholders that will support the Trials and the data collection process, but also will be strongly involved in the e-training process in identifying the needs and, later, testing and using the courses. Stakeholders will exploit the results promoting its marked deployment and commercialization strategy.
- In order to improve the AquaSmart business, it is important to understand the current technology status in the domain, and what are the desired solutions. Currently in aquaculture, there is only empirical knowledge on the effect of data parameters to the growth, cost, health and production time of the fish. These parameters relationships can be very deep and difficult to be understood. For example, a small change in dosage or an enrichment that is given to rotifers, which are then used to feed the fish larvae, can have a very big effect, on the malformations that the fish will develop during the growing phase. A main problem is that companies cannot interpret their data, or use others data, in order to identify systematic relationships between the variables that affect production. If they could, they would be able to dramatically improve the production in terms of feed conversion rate, cost, mortality, diseases, environmental impact, etc.
- As for Management, it is necessary to coordinate communications between all stakeholders including external experts. And to ensure compliance with legal, ethical and privacy concerns with respect to data management.
- Looking to this slide, we have information about what is the concept of AQUASMART Open Data Cloud. And that means: to have an Open Data Cloud Platform with a User Interface to facilitate data visualization and connectors to enable transfer of multi-lingual information. Incorporate action and parameter recommendation algorithms accomplished with machine learning and classification to enable prescriptive analytics based on open data source. It aims to create a cloud based platform with a backend based on machine learning, and data mining techniques to provide assistance to aquaculture managers in the decision making processes.
- AquaSmart is producing a Multi-lingual e-Training platform. For that the consortium is developing a training framework and strategy in line with the aquaculture companies training and open data policies. It is setting up a training platform based in MOODLE, to deploy the training materials and to support the delivery of the training programme. Developing and making available multi-lingual training material composed by teaching manuals and e-learning material. It will accomplish a multi-lingual AQUASMART training programme, targeting main aquaculture user profiles. Through specific MOODLE plug-ins, these materials will be available through mobile applications.
- In this slide we have the Trials and Validation to be performed within the scope of AquaSmart project. The aim is the deployment and validation of the AQUASMART both in technical terms (stability, efficiency and usability), as well, as in terms of business benefits. This will be supported by Trials, which will be designed, and simulated, to then effectively validate the AQUASMART results. Thus, such trials will analyse the connections of the various kinds of data produced by aquaculture companies in relation to the various key performance indicators identified by the project able of measuring the improvement of the business in the domain. Some of these data examples are enumerated or presented in the bottom of this slide.
- This slide presents some guidelines of the Stakeholders Engagement and Dissemination strategy. Intends to communicate the innovation capacity of the project to the target audience to encourage engagement with stakeholder participants, which are : (Primarily) Aquaculture sector (Fish Farmers), and regional Aquaculture associations. (Additionally) Policy making, Standards community (e.g. CEN), and other sectors (e.g. Transportation). It also intends to timely and efficiently disseminate the project results to the audience (e.g. web social). To promote awareness through the engagement of stakeholder participation. And set in train the foundation for greater exploitation achievements.
- As for the Market Deployment & Commercialization, AquaSmart intends: - To develop an efficient marketing strategy. - To generate a database of potential customers and business contacts. - To prepare a business plan for the future development and operation of AQUASMART. - To set the guidelines for the necessary agreements between the partners.
- In conclusion we say that; - The AquaSmart project responds to the EU’s Blue Growth Strategy for marine and maritime sustainable growth and the Commission’s Europe 2020 Strategy. - Globally, nearly half the fish consumed by humans is produced by fish farms. Global production is forecasted to increase from 45 million tons in 2014 to 85 million by 2030, making the aquaculture industry the fastest growing animal food producing sector in the world. - Thus, the European Union needs an innovative aquaculture industry to meet rising seafood demand and to enhance its commercial stocks. AquaSmart is a solution!!!
- Thank you by attending this course! For any additional information about this project, just use one of the following contacts.