Meaningful Integration of Data, Analytics and Services

Leistungen

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 4

Information materials will be developed within the brand platform: logos, social media material, e-newsletters, banners, letter templates, power points

Brochure, Poster and e-Newsletters 1

Information materials will be developed within the brand platform: logos, social media material, e-newsletters, banners, letter templates, power points.

Brochure, Poster and e-Newsletters 2

Information materials will be developed within the brand platform: logos, social media material, e-newsletters, banners, letter templates, power points.

Brochure, Poster and e-Newsletters 3

Information materials will be developed within the brand platform: logos, social media material, e-newsletters, banners, letter templates, power points

Data management plan

Development of an open data related Data Management Plan (DMP) in accordance to the “Guidelines on data management in Horizon 2020”

Project Plan
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 Data

Report 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 report

As 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 1

Good 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 V1

Concepts 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 V2

Good Practice Report 2

Good 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 Datasets 2

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 1

Veröffentlichungen

System dynamics modelling in policy level innovation orchestration

Autoren: Pikkarainen, M., Iivari, M., Gomes, J.F., Ranta, J., Ylén, P. and Hurmelinna-Laukkanen, P.
Veröffentlicht in: ISPIM Innovation Symposium, Ausgabe December 2017, 2017
Herausgeber: The International Society for Professional Innovation Management (ISPIM)

Towards the Integration of Prescription Analytics into Health Policy and General Practice

Autoren: Cleland, B., Wallace, J., Bond, R., Black, M., Mulvenna, M., Rankin, D. and Tanney, A.
Veröffentlicht in: International Conference on Innovative Techniques and Applications of Artificial Intelligence, Ausgabe November 2017, 2017, Seite(n) 193-206
Herausgeber: Springer

Text mining tools to explore the news in the context of public health

Autoren: Joao Pita Costa, Flavio Fuart, Marko Grobelnik, Gregor Leban, Luka Stopar and Paul Carlin
Veröffentlicht in: Slovenian Conference on Data Mining and Data Warehouses (SIKDD 2017), 2017
Herausgeber: SIKDD 2017

Text mining open datasets to support public health

Autoren: Joao Pita Costa, Flavio Fuart, Marko Grobelnik, Gregor Leban, Luka Stopar and Paul Carlin
Veröffentlicht in: Workshop on Information Technologies and Systems (WITS 2017), 2017
Herausgeber: WITS 2017

Q-Methodology Evaluation of a European Health Data Analytic End User Framework

Autoren: A Boilson, S Gauttier, R Connolly, P Davis, J Connolly, D Weston, A Staines
Veröffentlicht in: Abstract Supplement to the European Journal of Public Health, 2019
Herausgeber: European Public Health Association (EPH)

BOTter than the real thing

Autoren: Peter Poliwoda, Juha Pajula
Veröffentlicht in: OpenTech AI workshop, Ausgabe 06/05/2019, 2019
Herausgeber: IBM Helsinki, VTT Finland

Application of Q-Methodology & Mixed Methods Design to Explore the Utility of a Data Analytic Framework

Autoren: A Boilson, S Gauttier, R Connolly, P Davis, J Connolly, D Weston, A Staines
Veröffentlicht in: Journal of the Operational Research Society, 2019
Herausgeber: (OR) Society

Evaluating Impact of an Emerging Big Health Data Platform: A Logic Model and Q-Methodology Approach

Autoren: Connolly, J., Staines, A., Connolly, R., Boilson, A., Davis, P., Weston, D., Bloodworth, N.
Veröffentlicht in: Entrenova, 2018
Herausgeber: Entrenova

A topological data analysis approach to influenza-like-illness

Autoren: Joao Pita Costa, Primož Škraba, Daniela Paolotti and Ricardo Mexia
Veröffentlicht in: KDD Healthday 2018, 2018
Herausgeber: KDD

Qualitative Evaluation of a Multi-Level Framework of Technology Acceptance & Use for a European Health Data Analytic Platform

Autoren: A Boilson, A Staines, J Connolly, R Connolly, P Davis, D Weston
Veröffentlicht in: International Journal of Informatics, 2019
Herausgeber: International Conference on Information Society (i Society)

Text mining MEDLINE to support public health

Autoren: Joao Pita Costa, Luka Stopar, Flavio Fuart, Marko Grobelnik, Raghu Santanam, Chen Lu, Paul Carlin, Michaela Black, Johnathan Wallace
Veröffentlicht in: SiKDD 2018, 2018
Herausgeber: IJS

Health news bias, public health and digital epidemiology

Autoren: J. Pita Costa, F. Fuart, L. Stopar, M. Grobelnik, D. Mladenić, A. Košmerlj, Evgenia Belayeva, Gregor Leban
Veröffentlicht in: Data and Algorithms Bias, 2018
Herausgeber: CIKM

Digitalisation of healthcare: Use of data in policy making

Autoren: Iivari, Marika., Gomes, Julius Francis., Pikkarainen, Minna., Häikiö, Juha., Ylén, Peter.
Veröffentlicht in: XXVIII ISPIM Innovation Conference, Ausgabe 18-21 June 2017, 2018
Herausgeber: ISPIM

"""MyData"" potential in public health decisions"

Autoren: Gomes, Julius Francis., Pääkkönen, Jarmo., Iivari, Marika., Kemppainen, Laura., Pikkarainen, Minna.
Veröffentlicht in: 9th Annual EDSI Conference, Ausgabe 3 - 6 June, 2018, 2018
Herausgeber: European Decision Science Institute

Meaningful Integration of Data, Analytics and Services of Computer-Based Medical Systems: The MIDAS Touch

Autoren: Michaela Black, Jonathan Wallace, Debbie Rankin, Paul Carlin, Raymond Bond, Maurice Mulvenna, Brian Cleland, Scott Fischaber, Gorka Epelde, Gorana Nikolic, Juha Pajula, Regina Connolly
Veröffentlicht in: 32nd IEEE CBMS International Symposium on Computer-Based Medical Systems`, 2019
Herausgeber: IEEE

Logic Model Early Stage Evaluation of a European Public Health Data Analytic Framework

Autoren: A Boilson, A Staines, R Connolly, P Davis, J Connolly, D Weston
Veröffentlicht in: Journal Informatics, Special Ausgabe (Open Access Journal by MDPI), 2019
Herausgeber: 24th UK Academy for Information Systemsms International Conference

System dynamics modelling in policy level innovation orchestration

Autoren: Pikkarainen, Minna., Iivari, Marika., Gomes, Julius Francis., Ranta, Jukka., Ylén, Peter., Hurmelinna-Laukkanen, Pia.
Veröffentlicht in: ISPIM Innovation Summit 2017, Ausgabe 10 - 13 December 2017, 2018
Herausgeber: ISPIM

Using Big Data to Transform Health: The Importance of Evaluation Frameworks

Autoren: Connolly, J., Staines, A., Connolly, R., Weston, D., Boilson, A., Davis, P.
Veröffentlicht in: Irish Academy of Management Conference, 2018
Herausgeber: Entrenova

Q-Method and the Bootstrap - Visualizations

Autoren: A Staines, S Gauttier, R Connolly, P Davis, J Connolly, D Weston, A Boilson
Veröffentlicht in: The International Journal of Q Methodology, 2019
Herausgeber: 35th Annual Q Conference for the Scientific Study of Subjectivity

Improving European Healthcare Systems through the Development of a Realist Evaluation Framework for a European Public Health Data Analytic Project

Autoren: A Boilson, R Connolly, A Staines, P Davis, J Connolly, D. Weston
Veröffentlicht in: Biomed Central (BMC) Implementation Science Journal, 2019
Herausgeber: 2nd UK Implementation Science Research Conference

Machine learning using synthetic and real data: Similarity of evaluation metrics for different healthcare datasets and for different algorithms

Autoren: Rachel Heyburn, Raymond R. Bond, Michaela Black, Maurice Mulvenna, Jonathan Wallace, Deborah Rankin, Brian Cleland
Veröffentlicht in: Data Science and Knowledge Engineering for Sensing Decision Support, 2018, Seite(n) 1281-1291, ISBN 978-981-327-323-8
Herausgeber: WORLD SCIENTIFIC
DOI: 10.1142/9789813273238_0160

Q-Method Evaluation of a European Health Data Analytic End User Framework

Autoren: A Boilson, S Gauttier, R Connolly, P Davis, J Connolly, D Weston, A Staines
Veröffentlicht in: ENTRENOVA Conference Proceedings, 2019
Herausgeber: Enterprise Research Innovation Conference (ENTERNOVA)

"Mining MEDLINE for the visualisation of a global perspective on biomedical knowledge"""

Autoren: Joao Pita Costa, Luka Stopar, Flavio Fuart, Marko Grobelnik, Raghu Santanam, Chen Lu, Paul Carlin, Michaela Black, Johnathan Wallace
Veröffentlicht in: KDD Project Showcase Track, 2018
Herausgeber: KDD

Advancing open innovation in data-driven preventive healthcare

Autoren: Iivari, Marika., Pikkarainen, Minna., Ylén, Peter., Gomes, Julius Francis., Ranta, Jukka.
Veröffentlicht in: 4th World Open Innovation Conference 2017, Ausgabe 14 - 15 December, 2018, 2018
Herausgeber: N/A

Health News Bias and Epidemic Intelligence for Public Health

Autoren: J. Pita Costa, F. Fuart, L. Stopar, M. Grobelnik, D. Mladenić, A. Košmerlj, E. Belayeva, L. Rei, G. Leban, J. Wallace
Veröffentlicht in: SIKDD Conference Proceedings, 2019
Herausgeber: Institute Jozef Stefan

The meaningfulness of open data in Public Health and Healthcare

Autoren: J. Pita Costa, F. Fuart, A. Staines, O.Belar, J. Bidaurrazaga, J. Pääkkönen, G. Epelde, P. Poliwoda, B. Cleland, J. Wallace
Veröffentlicht in: European Public Health Conference, 2019
Herausgeber: EUPHA

How To Manage Privacy In A Database For Biomedical Research Purposes In The Rgpd Framework: An Opportunity For Biobanks

Autoren: Ezkerra Elizalde, I ; Belar Beitia, O; González Lopez, N; Bidaurrazaga Van-Dierdonck, J; Bilbao Urquiola, R
Veröffentlicht in: National Biobank Congress, 2019
Herausgeber: National Biobank Congress

Local-to-global analysis of influenza-like-illness data

Autoren: J. Pita Costa, F. Fuart, L. Stopar, D. Paolotti, M. Hirsch, R. Mexia, Paul Carlin, J. Wallace
Veröffentlicht in: SIKDD Conference Proceedings, 2019
Herausgeber: Institute Jozef Stefan

The MIDAS platform: facilitating the utilisation of healthcare big data in Northern Ireland and beyond (Poster)

Autoren: Rankin, D., Black, M., Mulvenna, M., Bond, R., Cleland, B.
Veröffentlicht in: 8th Translational Medicine Conference (TMED8), Ausgabe September 2017, 2017
Herausgeber: 8th Translational Medicine Conference (TMED8)

Meaningful Integration of Data, Analytics and Services – Finnish Pilot (Poster)

Autoren: Juha Pajula, Mark van Gils
Veröffentlicht in: EMBEC 2017, Ausgabe June 2017, 2017
Herausgeber: EMBEC 2017

A luta europeia contra o coronavirus vista do seu epicentro

Autoren: Joao Pita Costa
Veröffentlicht in: 2020
Herausgeber: Visao

Insights into Antidepressant Prescribing Using Open Health Data

Autoren: Brian Cleland, Jonathan Wallace, Raymond Bond, Michaela Black, Maurice Mulvenna, Deborah Rankin, Austin Tanney
Veröffentlicht in: Big Data Research, 2018, ISSN 2214-5796
Herausgeber: Elsevier Inc.
DOI: 10.1016/j.bdr.2018.02.002

Towards the Integration of Prescription Analytics into Health Policy and General Practice

Autoren: Brian Cleland, Jonathan Wallace, Raymond Bond, Michaela Black, Maurice Mulvenna, Deborah Rankin, Austin Tanney
Veröffentlicht in: Artificial Intelligence XXXIV, Ausgabe 10630, 2017, Seite(n) 193-206, ISBN 978-3-319-71077-8
Herausgeber: Springer International Publishing
DOI: 10.1007/978-3-319-71078-5_18

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