Objective
Data is becoming the key to effective decision making in more and more aspects of modern society. Big data analytics provide insight into complex processes considering a breadth of factors. This promises to increase the efficiency of decision making in areas such as policy making, research, product development, or financial and retail markets. Currently, big data analytics is employed only by technologically savvy organisations with control over the relevant data. This further exacerbates the information asymmetry that has been plaguing many of these areas: real estate where buyers have long suffered from limited information, often controlled by the seller; or retail markets where sellers are now employing sophisticated competitive price intelligence solutions unaffordable to buyers. Who can tell you if it is better to buy a house with a garden or with a garage; or where renovations will yield more rent over time? ExtraLytics answers these questions through a combination of big data extraction and analytics. ExtraLytics introduces analytics and prediction models into DIADEM’s platform for accurate big data extraction from the web, which is able to extract required data at massive scale from the web. For the proof-of-concept, ExtraLytics initially focuses on residential real estate in the UK, a £4,135bn market (UBS), where buyers and renters are required to make fast decision with limited information—time on market is often below a week or even below a day as for desirable rentals in Oxford. “In an age when ‘big data’ is shaping our every move, how come an industry that takes so much profit can’t keep pace with technology and use it to actually deliver a service worth the money they take in commission?” (The Telegraph). ExtraLytics addresses this lack of data-driven analytics by giving consumers and investors alike a tool for better understanding properties, their location, their neighborhood, and their investment potential compared to other properties.
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.
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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.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
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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.
ERC-POC - Proof of Concept Grant
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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) ERC-2014-PoC
See all projects funded under this callHost institution
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.
OX1 2JD Oxford
United Kingdom
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.