Objective
In VIVIR, I will conduct state-of-the-art research on supporting collaborative face-to-face data analysis. This is motivated by the increasing need for interdisciplinary teams to collaborate on understanding and analysing data. Additionally, as the scale and complexity of data increase, so does the demand for data-based insights and decision-making. My approach is to empower people who are working with large and complex data, by letting them lay out as many visualization views (in the following, denoted views) as necessary on large displays, and creating specialized meta-visualizations to show relations between these views. These meta-visualizations will allow team workers to be aware of each other’s work and the changing view- and data-relationships as they work. While the potential of view meta-visualizations has been acknowledged , there are currently only a few frequently used and considered essential examples of such meta-visualizations. These might show that data in two views are compared in a third view, or that a view shows a subset of the data shown in another view. Most importantly, there has been no thorough exploration into the power and potential of meta-visualization support for data-driven decision-making. To understand the potential impact of meta-visualizations on data analysis, we need to take a structured approach, to formalize these possibilities, which will improve our abilities to support knowledge worker teams as they face the challenges of analyzing increasingly complex data.
In brief, data can be difficult to understand. Creating visualizations of data lets people see their data more clearly. As data size and complexity increases, more views are needed to reveal the information hidden in data. Large displays might be useful to solve this. However, a new problem is emerging – how to be aware of the data relationships, and keep an overview of analysis provenance , findings, and decisions between these multiple views. VIVIR tackles this issue.
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.
- natural sciences computer and information sciences data science
- social sciences media and communications graphic design
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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-GF - Global Fellowships
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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-2016
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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.
1165 KOBENHAVN
Denmark
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.