AquaSmart Horizon 2020 Project Introduction

H2020 ICT-15-2014: 644715

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

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.

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.

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

Bringing Big and Open Data Analytics as a Service to the Aquaculture

Industry

The Motto

Vision of Impact

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

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

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.

Required Management

» Coordinate communications between all stakeholders including external experts

» Ensure compliance with legal, ethical and privacy concerns with respect to data management

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

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;

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:

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.

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

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!!!

The End

H2020 ICT-15-2014: 644715

Email: [email protected] URL: www.aquasmartdata.eu Twitter: @AquaSmartData LinkedIn Group: AquaSmartData Facebook Page: www.facebook.com/Aquasmartdata