Project description
Advancing agricultural monitoring infrastructure
Agricultural production is facing various challenges including climate change, environmental concerns, energy demands and growing expectations from consumers. Collectively, these necessitate carefully designed processes based on data collection and innovative visual analytics. The EU-funded OB-VISLY project will exploit advances in data visualisation and analytics to provide insight into complex datasets. Following research in regional fruit-growing apple orchards and vineyards, scientists will create a single visual analytics user interface that can turn the obtained data into knowledge. The project's efforts will contribute to more precise and sustainable agriculture methods and increase agricultural potential in Europe by establishing a digital single market within the sector.
Objective
Increasing challenges for agricultural production such as climate change, environmental concerns, energy demands, and growing expectations from consumers triggered the necessity for innovation using data-driven approaches such as visual analytics. OB-VISLY extends the visual analytics approach with a structural way of data organization (ontologies), data mining, and visualization techniques to retrieve knowledge from the agricultural monitoring data. The latest advances in data visualization and analytics made it possible to fully exploit the potential of the proposed approach and gain insights into high complexity datasets (multi-source, multi-scale, and different stages).
In OB-VISLY, I will carry out state-of-the-art research that unites two strands of recent, significant inquiry: Big Data analytics in the agricultural sector and visual methods. OB-VISLY aims to (1) establish a regionally significant dataspace enabled to synthesize information about fruit-growing apple orchards and vineyards and derive insight from massive, dynamic, and often conflicting data by providing up-to-date, consistent, and credible assessments; (2) create a single visual analytics user interface that can turn the data into knowledge for users of different information retrieval proficiency.
OB-VISLY will establish and implement an innovative visual analytics-enabled dataspace within the European agricultural sector. The findings will contribute to European priority in building a digital single market and tackle obstacles that hinder the exploitation of big data and digital tools. Thus OB-VISLY will serve social and environmental well-being by uncovering hidden patterns from big agricultural data for future sustainable and environmentally friendly development. Such an endeavor aims to pave a way towards strengthening precision and conservation agriculture methods and create an added value to sustain under competitive conditions and increase agricultural potential in Europe.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- agricultural sciences agriculture, forestry, and fisheries agriculture horticulture viticulture
- natural sciences computer and information sciences knowledge engineering ontology
- natural sciences computer and information sciences data science big data
- natural sciences computer and information sciences data science data mining
- natural sciences earth and related environmental sciences atmospheric sciences climatology climatic changes
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2019
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
39100 BOLZANO
Italy
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.