Open Call ICT-14-2016-2017: Big Data PPP: Cross-Sectorial and Cross-Lingual Data Integration and Experimentation

European CommissionEurope lacks a systematic transfer of knowledge and technology across different sectors and there is an underdeveloped data sharing and linking culture. Traditionally, data has been collected and used for a certain purpose within sectorial "silos", while using data across sectors for offering new services opens new opportunities for solving business and societal challenges. The lack of agreed standards and formats, and the low rates of publishing data assets in machine discoverable formats further hold back data integration. The fact that textual data appears in many languages creates an additional challenge for sharing and linking such data. Finally, there is a lack in Europe of secure environments where researchers and SMEs can test innovative services and product ideas based on open data and business data.

The challenge is to break these barriers and to foster exchange, linking and re-use, as well as to integrate data assets from multiple sectors and across languages and formats. A more specific challenge is to create a stimulating, encouraging and safe environment for experiments where not only data assets but also knowledge and technologies can be shared.

Proposals should cover one of the following bullets:

  • a. Data integration activities will address data challenges in cross-domain setups, where similar contributions of data assets will be required by groups of EU industries that are arranged along data value chains (i.e. such that the value extracted by a company in a given industrial sector is greatly increased by the availability and reuse of data produced by other companies in different industrial sectors). The actions will cover the range from informal collaboration to formal specification of standards and will include (but not be limited to) the operation of shared systems of entity identifiers (so that data about the same entity could be easily assembled from different sources), the definition of agreed data models (so that two companies carrying out the same basic activity would produce data organised in the same way, to the benefit of developers of data analytics tools), support for multilingual data management, data brokerage schemes and the definition of agreed processes to ensure data quality and the protection of commercial confidentiality and personal data. The actions are encouraged to make use of existing data infrastructures and platforms.
  • b. Data experimentation incubators should address big data experimentation in a cross-sectorial, cross lingual and/or cross-border setup. This setup should include access to data in different domains and languages, appropriate computational infrastructure, and open software tools. The incubator should make these available to the experimenters, who are expected to be mainly SMEs, web entrepreneurs and start-ups. Experimentation is to be conducted on horizontal/vertical contributed data pools provided by the incubator. At least half of the experiments should address challenges of industrial importance jointly defined by the data providers, where quantitative performance targets are defined beforehand and results measured against them. Effective cross-sector and cross-border exchange and re-use of data are key elements in the experiments ecosystem supported by the incubators. Therefore, the incubators are expected to address the technical, linguistic, legal, organisational, and IPR issues, and provide a supported environment for running the experiments. To remain flexible on which experiments are carried out and to allow for a fast turn-over of data experimentation activities, the action may involve financial support to third parties, in line with the conditions set out in part K of the General Annexes. The proposal will define the selection process of the experimenters running the data activities for which financial support will be granted (typically in the order of EUR 50 000 - 100 000[1] per party). At least 70% of the EU funding shall be allocated to this purpose. Experiments are expected to run for a maximum of 6 months, while the incubator should run for a minimum of three years. The proposals are expected to explain how the incubator would become self-sustaining by the end of the funded duration of action.

The Commission considers that proposals requesting a contribution from the EU of between EUR 1 and 3 million (for the data integration activities under a) or about EUR 7 million (for the incubators under b) would allow this area to be addressed appropriately. Nonetheless, this does not preclude submission and selection of proposals requesting other amounts.

Deadline Date: 12 April 2016 17:00:00 (Brussels local time)

Type of action: IA Innovation action.

For topic conditions, documents and submission service, please visit:
http://ec.europa.eu/research/participants/portal/desktop/en/opportunities/h2020/topics/5093-ict-14-2016-2017.html

PS: Find your partners or consortia preparing a project proposal
If you are working on Horizon 2020 research project proposals and you would be interested in a SME partner from Germany, please contact us, we are ready to share our experience, expertise and knowledge. If you need help to identify a potential partner with particular competences, facilities or experience, please explore and join our project, (HEALTH IT) SPACE, at www.healthitspace.eu.

Most Popular Now

Giving Doctors an AI-Powered Head Start …

Detection of melanoma and a range of other skin diseases will be faster and more accurate with a new artificial intelligence (AI) powered tool that analyses multiple imaging types simultaneously...

AI Agents for Oncology

Clinical decision-making in oncology is challenging and requires the analysis of various data types - from medical imaging and genetic information to patient records and treatment guidelines. To effectively support...

AI Medical Receptionist Modernizing Doct…

A virtual medical receptionist named "Cassie," developed through research at Texas A&M University, is transforming the way patients interact with health care providers. Cassie is a digital-human assistant created by Humanate...

Using Data and AI to Create Better Healt…

Academic medical centers could transform patient care by adopting principles from learning health systems principles, according to researchers from Weill Cornell Medicine and the University of California, San Diego. In...

AI Tool Set to Transform Characterisatio…

A multinational team of researchers, co-led by the Garvan Institute of Medical Research, has developed and tested a new AI tool to better characterise the diversity of individual cells within...

AI Detects Hidden Heart Disease Using Ex…

Mass General Brigham researchers have developed a new AI tool in collaboration with the United States Department of Veterans Affairs (VA) to probe through previously collected CT scans and identify...

Human-AI Collectives Make the Most Accur…

Diagnostic errors are among the most serious problems in everyday medical practice. AI systems - especially large language models (LLMs) like ChatGPT-4, Gemini, or Claude 3 - offer new ways...

Northern Ireland Completes Nationwide Ro…

Go-lives at Western and Southern health and social care trusts mean every pathology service is using the same laboratory information management system; improving efficiency and quality. An ambitious technology project to...

Highland Marketing Announced as Official…

Highland Marketing has been named, for the second year running, the official communications partner for HETT Show 2025, the UK's leading digital health conference and exhibition. Taking place 7-8 October...

MHP-Net: A Revolutionary AI Model for Ac…

Liver cancer is the sixth most common cancer globally and a leading cause of cancer-related deaths. Accurate segmentation of liver tumors is a crucial step for the management of the...

Groundbreaking TACIT Algorithm Offers Ne…

Researchers at VCU Massey Comprehensive Cancer Center have developed a novel algorithm that could provide a revolutionary tool for determining the best options for patients - both in the treatment...

The Many Ways that AI Enters Rheumatolog…

High-resolution computed tomography (HRCT) is the standard to diagnose and assess progression in interstitial lung disease (ILD), a key feature in systemic sclerosis (SSc). But AI-assisted interpretation has the potential...