Deliverables
The project website will function as the primary source of information available at all times to all stakeholders providing the following: - Project Activities and outcomes; - Repository for external facing project information, reports and deliverables; - Project consortium details and the Horizon 2020 funding mechanism; - Mechanism for contacting the project team and sign-up to project e-newsletter; - Big Data Challenges; The website will make use of an open source mobile responsive framework, such as Twitter Bootstrap, to deliver a high quality device-agnostic, responsive design, user experience. The website and associated social media platforms for MIDAS will make use of appropriate platform tools for digital analytics to measure and report on digital interaction and allow iterative design based on functional test results.
Brochure, Poster and e-Newsletters 4Information materials will be developed within the brand platform: logos, social media material, e-newsletters, banners, letter templates, power points
Brochure, Poster and e-Newsletters 1Information materials will be developed within the brand platform: logos, social media material, e-newsletters, banners, letter templates, power points.
Brochure, Poster and e-Newsletters 2Information materials will be developed within the brand platform: logos, social media material, e-newsletters, banners, letter templates, power points.
Brochure, Poster and e-Newsletters 3Information materials will be developed within the brand platform: logos, social media material, e-newsletters, banners, letter templates, power points
Development of an open data related Data Management Plan (DMP) in accordance to the “Guidelines on data management in Horizon 2020”
MIDAS Framework User Guide
Framework and model for the use of the MIDAS platform. This will address issues highlighted in D1.1. This framework and model will include guides on implementation, engagement, communication and benefits.
Report on Public Perceptions of Personal Identifiable DataReport on Public Perceptions of Personal Identifiable Data (M24) - A paper exploring public perceptions of various health and security-related uses of PID prepared and submitted for publication.
Gender balance participation reportAs part of the dissemination activities, a more balanced workforce will be promoted. A report on gender balance participation performance within the Consortium will be presented to the Commission at the end of the project. It is anticipated that the report will support the Commission regarding equality policies decision making as well as interim reviews of the effective implementation of the Horizon 2020 framework programme
Good Practice Report 1Good Practice Report 1 describing current legislation, good practice and process in respect of consent, access, storage and use of personal data throughout the consortium/ member states.
Visual analytics tool(s) concept V1Concepts of visualization and visual analytics tools for different stakeholders are defined, including: • Identification of the different stakeholders (e.g. government, national and regional/local health authorities, individuals) and their visualization and analytics needs. The MIDAS Policy Board will play an important role in supporting this work; • Analysis of the data resources and selection of the data variables and indicators for the visualizations. Definitions of information abstraction levels to be able to explore specific impacts in detail; • Selection of the visualization, analysis and other methods (e.g. simulation) for different stakeholders and purposes; • Definition of most critical scenario’s/use cases (Simulation, Forecasting, Policy, Effectiveness assessment, Feedback); • Visual analytics tool specification, including interfaces to data sources, user interfaces and iterative reasoning loop support.
Visual analytics tool(s) concept V2Concepts of visualization and visual analytics tools for different stakeholders are defined, including: • Identification of the different stakeholders (e.g. government, national and regional/local health authorities, individuals) and their visualization and analytics needs. The MIDAS Policy Board will play an important role in supporting this work; • Analysis of the data resources and selection of the data variables and indicators for the visualizations. Definitions of information abstraction levels to be able to explore specific impacts in detail; • Selection of the visualization, analysis and other methods (e.g. simulation) for different stakeholders and purposes; • Definition of most critical scenario’s/use cases (Simulation, Forecasting, Policy, Effectiveness assessment, Feedback); • Visual analytics tool specification, including interfaces to data sources, user interfaces and iterative reasoning loop support.
Good Practice Report 2Good Practice Report 2 describing current legislation, good practice and process in respect of consent, access, storage and use of personal data throughout the consortium/ member states.
Synthetic data is known as ‘artificial data’ that is simulated from real data using statistical models in order to represent the population yet avoid any divulgence of actual patient records. This task will involve creating synthetic data from the real population datasets that are made available in this project. This artificial data will be simulated using the SynthPop library inside the R programming environment. The synthetic datasets will be validated with the real data by analysing summary statistics and Gaussian distributions. Whilst they are somewhat representative, synthetic datasets avoid various governance and confidentiality issues since real patient or citizen records are not provided or disclosed.
Synthetic Datasets 1Synthetic data is known as ‘artificial data’ that is simulated from real data using statistical models in order to represent the population yet avoid any divulgence of actual patient records. This task will involve creating synthetic data from the real population datasets that are made available in this project. This artificial data will be simulated using the SynthPop library inside the R programming environment. The synthetic datasets will be validated with the real data by analysing summary statistics and Gaussian distributions. Whilst they are somewhat representative, synthetic datasets avoid various governance and confidentiality issues since real patient or citizen records are not provided or disclosed.
Publications
Author(s):
Pikkarainen, M., Iivari, M., Gomes, J.F., Ranta, J., Ylén, P. and Hurmelinna-Laukkanen, P.
Published in:
ISPIM Innovation Symposium, Issue December 2017, 2017
Publisher:
The International Society for Professional Innovation Management (ISPIM)
Author(s):
Cleland, B., Wallace, J., Bond, R., Black, M., Mulvenna, M., Rankin, D. and Tanney, A.
Published in:
International Conference on Innovative Techniques and Applications of Artificial Intelligence, Issue November 2017, 2017, Page(s) 193-206
Publisher:
Springer
Author(s):
Joao Pita Costa, Flavio Fuart, Marko Grobelnik, Gregor Leban, Luka Stopar and Paul Carlin
Published in:
Slovenian Conference on Data Mining and Data Warehouses (SIKDD 2017), 2017
Publisher:
SIKDD 2017
Author(s):
Joao Pita Costa, Flavio Fuart, Marko Grobelnik, Gregor Leban, Luka Stopar and Paul Carlin
Published in:
Workshop on Information Technologies and Systems (WITS 2017), 2017
Publisher:
WITS 2017
Author(s):
A Boilson, S Gauttier, R Connolly, P Davis, J Connolly, D Weston, A Staines
Published in:
Abstract Supplement to the European Journal of Public Health, 2019
Publisher:
European Public Health Association (EPH)
Author(s):
Peter Poliwoda, Juha Pajula
Published in:
OpenTech AI workshop, Issue 06/05/2019, 2019
Publisher:
IBM Helsinki, VTT Finland
Author(s):
A Boilson, S Gauttier, R Connolly, P Davis, J Connolly, D Weston, A Staines
Published in:
Journal of the Operational Research Society, 2019
Publisher:
(OR) Society
Author(s):
Connolly, J., Staines, A., Connolly, R., Boilson, A., Davis, P., Weston, D., Bloodworth, N.
Published in:
Entrenova, 2018
Publisher:
Entrenova
Author(s):
Joao Pita Costa, Primož Škraba, Daniela Paolotti and Ricardo Mexia
Published in:
KDD Healthday 2018, 2018
Publisher:
KDD
Author(s):
A Boilson, A Staines, J Connolly, R Connolly, P Davis, D Weston
Published in:
International Journal of Informatics, 2019
Publisher:
International Conference on Information Society (i Society)
Author(s):
Joao Pita Costa, Luka Stopar, Flavio Fuart, Marko Grobelnik, Raghu Santanam, Chen Lu, Paul Carlin, Michaela Black, Johnathan Wallace
Published in:
SiKDD 2018, 2018
Publisher:
IJS
Author(s):
J. Pita Costa, F. Fuart, L. Stopar, M. Grobelnik, D. Mladenić, A. Košmerlj, Evgenia Belayeva, Gregor Leban
Published in:
Data and Algorithms Bias, 2018
Publisher:
CIKM
Author(s):
Iivari, Marika., Gomes, Julius Francis., Pikkarainen, Minna., Häikiö, Juha., Ylén, Peter.
Published in:
XXVIII ISPIM Innovation Conference, Issue 18-21 June 2017, 2018
Publisher:
ISPIM
Author(s):
Gomes, Julius Francis., Pääkkönen, Jarmo., Iivari, Marika., Kemppainen, Laura., Pikkarainen, Minna.
Published in:
9th Annual EDSI Conference, Issue 3 - 6 June, 2018, 2018
Publisher:
European Decision Science Institute
Author(s):
Michaela Black, Jonathan Wallace, Debbie Rankin, Paul Carlin, Raymond Bond, Maurice Mulvenna, Brian Cleland, Scott Fischaber, Gorka Epelde, Gorana Nikolic, Juha Pajula, Regina Connolly
Published in:
32nd IEEE CBMS International Symposium on Computer-Based Medical Systems`, 2019
Publisher:
IEEE
Author(s):
A Boilson, A Staines, R Connolly, P Davis, J Connolly, D Weston
Published in:
Journal Informatics, Special Issue (Open Access Journal by MDPI), 2019
Publisher:
24th UK Academy for Information Systemsms International Conference
Author(s):
Pikkarainen, Minna., Iivari, Marika., Gomes, Julius Francis., Ranta, Jukka., Ylén, Peter., Hurmelinna-Laukkanen, Pia.
Published in:
ISPIM Innovation Summit 2017, Issue 10 - 13 December 2017, 2018
Publisher:
ISPIM
Author(s):
Connolly, J., Staines, A., Connolly, R., Weston, D., Boilson, A., Davis, P.
Published in:
Irish Academy of Management Conference, 2018
Publisher:
Entrenova
Author(s):
A Staines, S Gauttier, R Connolly, P Davis, J Connolly, D Weston, A Boilson
Published in:
The International Journal of Q Methodology, 2019
Publisher:
35th Annual Q Conference for the Scientific Study of Subjectivity
Author(s):
A Boilson, R Connolly, A Staines, P Davis, J Connolly, D. Weston
Published in:
Biomed Central (BMC) Implementation Science Journal, 2019
Publisher:
2nd UK Implementation Science Research Conference
Author(s):
Rachel Heyburn, Raymond R. Bond, Michaela Black, Maurice Mulvenna, Jonathan Wallace, Deborah Rankin, Brian Cleland
Published in:
Data Science and Knowledge Engineering for Sensing Decision Support, 2018, Page(s) 1281-1291, ISBN 978-981-327-323-8
Publisher:
WORLD SCIENTIFIC
DOI:
10.1142/9789813273238_0160
Author(s):
A Boilson, S Gauttier, R Connolly, P Davis, J Connolly, D Weston, A Staines
Published in:
ENTRENOVA Conference Proceedings, 2019
Publisher:
Enterprise Research Innovation Conference (ENTERNOVA)
Author(s):
Joao Pita Costa, Luka Stopar, Flavio Fuart, Marko Grobelnik, Raghu Santanam, Chen Lu, Paul Carlin, Michaela Black, Johnathan Wallace
Published in:
KDD Project Showcase Track, 2018
Publisher:
KDD
Author(s):
Iivari, Marika., Pikkarainen, Minna., Ylén, Peter., Gomes, Julius Francis., Ranta, Jukka.
Published in:
4th World Open Innovation Conference 2017, Issue 14 - 15 December, 2018, 2018
Publisher:
N/A
Author(s):
J. Pita Costa, F. Fuart, L. Stopar, M. Grobelnik, D. Mladenić, A. Košmerlj, E. Belayeva, L. Rei, G. Leban, J. Wallace
Published in:
SIKDD Conference Proceedings, 2019
Publisher:
Institute Jozef Stefan
Author(s):
J. Pita Costa, F. Fuart, A. Staines, O.Belar, J. Bidaurrazaga, J. Pääkkönen, G. Epelde, P. Poliwoda, B. Cleland, J. Wallace
Published in:
European Public Health Conference, 2019
Publisher:
EUPHA
Author(s):
Ezkerra Elizalde, I ; Belar Beitia, O; González Lopez, N; Bidaurrazaga Van-Dierdonck, J; Bilbao Urquiola, R
Published in:
National Biobank Congress, 2019
Publisher:
National Biobank Congress
Author(s):
J. Pita Costa, F. Fuart, L. Stopar, D. Paolotti, M. Hirsch, R. Mexia, Paul Carlin, J. Wallace
Published in:
SIKDD Conference Proceedings, 2019
Publisher:
Institute Jozef Stefan
Author(s):
Rankin, D., Black, M., Mulvenna, M., Bond, R., Cleland, B.
Published in:
8th Translational Medicine Conference (TMED8), Issue September 2017, 2017
Publisher:
8th Translational Medicine Conference (TMED8)
Author(s):
Juha Pajula, Mark van Gils
Published in:
EMBEC 2017, Issue June 2017, 2017
Publisher:
EMBEC 2017
Author(s):
Joao Pita Costa
Published in:
2020
Publisher:
Visao
Author(s):
Brian Cleland, Jonathan Wallace, Raymond Bond, Michaela Black, Maurice Mulvenna, Deborah Rankin, Austin Tanney
Published in:
Big Data Research, 2018, ISSN 2214-5796
Publisher:
Elsevier Inc.
DOI:
10.1016/j.bdr.2018.02.002
Author(s):
Brian Cleland, Jonathan Wallace, Raymond Bond, Michaela Black, Maurice Mulvenna, Deborah Rankin, Austin Tanney
Published in:
Artificial Intelligence XXXIV, Issue 10630, 2017, Page(s) 193-206, ISBN 978-3-319-71077-8
Publisher:
Springer International Publishing
DOI:
10.1007/978-3-319-71078-5_18
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