DARE Work Packages

SPOKE 1

WP1
Ecosystem Building
WP1 LEADER: UCSC
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PARTNERS: UNIBO, UNIBA, BI-REX, GIMBE
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WP objectives

The aim is to coordinate technological development, promote participatory approaches, and increase awareness.

TASK SPOKE 1 WP1

Task 1.1 – Identificazione dei criteri rilevanti per misurare l’utilità e l’implementabilità degli interventi digitali di prevenzione

This task will work on harmonizing the procedures for collecting evidence within the pilots in spoke 2 and spoke 3. To this end, we will map and list the relevant process, outcome, and impact indicators for a multidimensional evaluation of digital preventive approaches.  

Task 1.2 – Synthesis of evidence and critical appraisal

This task will take as an input the needs and the requirements coming from the pilots in spoke 2 and spoke 3 and will coordinate the identification and the development of the solutions in WP2, WP3, and WP4.  

Task 1.3 – Identification and creation of a stakeholder network for the co-creation of strategies for personalized digital prevention.

We will identify stakeholders: researchers, funding agencies, policymakers, health authorities, health professionals, patients, citizens, insurance companies, and innovators. A Stakeholder Platform will ensure their active involvement that will serve as a bridge for the actual engagement in the spokes 2-3.  

Task 1.4 – Networking with national, EU, and international actors and projects.

In order to maximise the visibility and enhance synergies, we will establish synergies with relevant initiatives through a mapping exercise and continuous networking across the project life span. 

Task 1.5 – Communication and dissemination

Communication activities and dissemination of results and evidence-based knowledge. Organization of workshops and public events. 

List of Deliverables:
  • D1.1: List of process and outcome indicators, M6
  • D1.2: Stakeholder engagement, M12
  • D1.3: Communication and Dissemination plan, M12
  • D1.4: Evidence synthesis M44
WP2
Legal and Ethical Framework
WP2 LEADER: UNIBO
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PARTNERS: UNIPA, UNIPR, INFN
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WP objectives

The aim is to overcome the barrier to compliance with legal, ethical, and data protection requirements. WP2 will analyse the legal and regulatory landscape in which the pilots in spoke 2 and spoke 3 intend to operate.  

TASK SPOKE 1 WP2

Task 2.1 – Ethical aspects

This task will map the ethical framework applicable to the specific application context and highlight possible critical situations.

Task 2.2 – Privacy and data protection/management.

The analysis will include a focus on privacy and data protection law (GDPR).  

Task 2.3 - Artificial Intelligence regulation and applicable norms

The primary goal is to identify regulatory requirements and legal issues that those responsible for the pilots should be aware of and elaborate on possible solutions.  

Task 2.4 – Civil liability profiles.

This task will verify the civil liability regime which might apply to the cases analysed in light of the European Union's draft laws and International Law on the subject and the possible future development of the legal framework.  

List of Deliverables:
  • D2.1: Inventory of the ethical and legal framework, M12
  • D2.2: Report on the implementation of requirements, M24
  • D2.3: Implementation guidelines, M42
WP3
Interoperability Governance
WP3 LEADER: INFN
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PARTNERS: UNIBO, UNIPA, EXP, ENG
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WP objectives
To enable different information systems, devices, and applications, to access, exchange, integrate, and use data within and between the stakeholders involved in spoke 2 and spoke 3 pilots. 

TASK SPOKE 1 WP3

Task 3.1 – Multi-dimensional governance and coordination

This task will establish a direct link with the parties involved in the pilots in spoke 2 and spoke 3 to ensure effective deployment of the solutions at the pilot sites. The interoperability governance will be applied to solutions provided by external providers and to existing systems involved in the pilots (legacy systems).  

Task 3.2 - Building trust

Governance, organizational aspects, and data curation best practices agree with the FAIR guiding principles for data management. This task will support the end-users by coordinating stakeholders and making data and services available and accessible.  

Task 3.3 – Technical and semantic interoperability

Tools and methods for adopting national and European standards such as HL7 CDA for HER, DICOM, and DICOM-SR for diagnostic images, ICD, SNOMED, and LOINC, as terminology standards, and HL7 FHIR as transport standard.  

List of Deliverables:
  • D3.1: Analysis of the technological framework and interoperability requirements, M12
  • D3.2: Multi-dimensional interoperability strategies and solutions deployed, M36
  • D3.3: Guidelines for interoperability governance, M48
WP4
Technology and Analytics
WP4 LEADER: UNIBO
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PARTNERS: UNIPA, UNIBA, UNIPR, UNIROMA2, INFN, IOR, EXP, ENG
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Uniroma2
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WP objectives

The aim is to identify, develop, adapt, and customize enabling technologies.

TASK SPOKE 1 WP4

Task 4.1 – HPC, HPDA, Cloud and Edge Computing

This task identifies, adapts, and develops computing solutions that are functional to the requirements and needs of the pilots in spoke 2 and spoke 3. This task will work on both on-premise and cloud-based solutions exploiting the three models of SaaS, PaaS, and IaaS. This task will develop software interfaces and integration strategies, in agreement with the specifications defined in Task 3.1, to ensure the solution's successful deployment in spoke 2 and spoke 3.  

Task 4.2 – Model integration and deployment

The success of a machine learning (ML) model, and data-driven methods in general, does not consist exclusively of its accuracy but depends on its integration with non-ML software as part of a sizeable ML-based system. This task aims at defining effective approaches for transitioning ML models, developed by data scientists in Task 4.3, into ML-based software systems, focusing on MLOps and online testing to assure the quality of both data and models after being deployed online.

Task 4.3 – Data Mining, AI, ML, Deep Learning and big data analytics

This task will identify/adapt/develop data-driven tools and methods used in the pilots in spoke 2 and spoke 3, including descriptive and predictive analytics. To overcome the issue of the black-box nature of ML models, both generic and modelling-specific explainable methods will be used whenever relevant. AI-based (semantic) indexing of entities and relations in the data will be developed for the extraction of patterns and correlations, including aid in the searching, browsing, retrieval, and explanation of information to demonstrate tangible value and improved usability of health data for end-users.  

Task 4.4 – Wearable sensors, IoT/IoMT, Apps

This task will focus on identifying and developing embedded/wearable devices, and mobile applications that serve as sensing, feedback, and front-end solutions within spoke 2 and spoke 3 pilots. Activities range from the manufacturing/customization of the devices to firmware and software development.  

List of Deliverables:
  • D4.1: Computing solutions deployment strategy, M12
  • D4.2: Best practices and tools for building ML-based systems; M18
  • D4.3: Report on the development and integration of wearable/portable solutions, M36
  • D4.4: Report on the developed computational models, M36  
WP5
Impact Analysis, Policymaking, Upscaling
WP5 LEADER: UNIROMA2
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PARTNERS: UNIBO, UNIBA, AUSL Romagna, ASL BA
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WP objectives

Starting from the evidence synthesis in spoke 2 and spoke 3, the aim is to understand and anticipate the impact of a new solution and promote its upscaling.  

TASK SPOKE 1 WP5

Task 5.1 – Socio-economic, industrial, and environmental impact analysis

This task will evaluate the impact of proposed innovations in addressing gaps and inefficiencies using digital enabling technologies. Consequently, it will identify the organizational models that could prove to be better. The evaluation will utilize rigorous research design(s) to generate high-quality (valid and reliable) evidence to assist in the subsequent spread and scale up successful innovations. A set of indicators will be identified and collected in spoke 2 and spoke 3 to verify the impact in terms of efficacy and efficiency in a real-world setting.  

Task 5.2 – Development of upscaling strategies

This task will take the outcomes of Task 5.1 and coordinate with Task 1.3 in WP1 to speed up the uptake and strengthen the innovation potential.  

Task 5.3 - Policy evaluation and making

Together with Task 1.3 in WP1, this task will allow the partners and stakeholders to point out eventual loopholes and constraints in the current legislation and organizational models about person-centered digital prevention focused on the well-being and not only on disease control. To nurture the policy debate, this task will result in a set of recommendations on how to remedy regulatory, legal, and policy-related shortcomings, bringing to light the need to reaffirm and reshape “the closeness and distance” between health organizations, patients, individuals, and the society.  

List of Deliverables:
  • D5.1: Definition of the research design and database linkages for individual risk stratification, M12
  • D5.2: Definition of the activities targeted to healthcare professionals for supporting pro-active care approaches and training initiatives, M18
  • D5.3: Results and fine-tuning of the initiatives, M36  
WP6
Education, Training, and Career Paths
WP6 LEADER:
Angela Montanari (UNIBO)
PARTNERS: UCSC, UNIPA, UNIBA, UNIPR, INFN, BI-REX
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WP objectives

The aim is to address the lack of qualified personnel and improve the level of digital skills in the context of health prevention, which employers and employees require.   

TASK SPOKE 1 WP6

Task 6.1 – Establishing education, research, and career pathways

Enhancement of university post-graduate courses and PhD programs focusing on essential and advanced digital and computational skills in healthcare with a particular focus on prevention and health promotion. The target group includes the current workforce, those working in the research setting of real-world data and their applications.  

Task 6.2 – Professional retraining and advanced training courses

This task will develop and deliver advanced post-graduate courses: i) at the individual level to better prepare professionals to hold emerging positions in the digital era, such as Data Stewards and Data Custodians; ii) at the organization level (e.g., ethics committees and local authorities), to bridge the digital divide.  

Task 6.3 – Enhancing and supporting human resources

This task will create career opportunities in academia and industry for the fixed-term staff recruited within this initiative.  

List of Deliverables:
  • D6.1: Plan for enhanced educational programming, M12
  • D6.2: Plan for Advanced Training Courses, M12
  • D6.3: Intermediate update on the educational and training plans, M32
  • D6.4:Report on the established training courses, M48  
WP7
Sustainability, Technology Transfer, and Cascade Funding
WP7 LEADER:
Giuseppe Pirlo (UNIBA)
PARTNERS: UNIBO, UNIPA, UNIPR, BI-REX, EXP, ENG
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WP objectives

This WP aims to ensure the long-term sustainability of spoke 1 and the protection and valorisation/exploitation of the results. Innovative systems and methodologies for the enhancement of intellectual property will be developed in WP7, hence activities will be carried out in coordination with the corresponding WPs of spokes 2 and 3, to maximize the effects on the sustainability of the entire project.  

TASK SPOKE 1 WP7

Task 7.1 – Sustainability management plan

Planning, design, and implementation of all the initiatives that will guarantee the sustainability of the spoke 1, from the stabilization and consolidation of relations to the implementation of intelligent IPR strategies to ensure revenue acquisition and financing.  

Task 7.2 – IPR management and exploitation

Continuous IP inventory, development of joint ownership strategies, protection of IP, and exploitation strategies. Exploitable results will be considered along two sets of criteria: maturity and scalability.

Task 7.3 – Data-Driven approaches for Technology Transfer

AI/ML techniques will be considered to support the maturity and scalability strategies of Task 7.2. Digital Twin models will be applied to Technology Transfer processes to support selecting the most effective approaches.

Task 7.4 – Support for entrepreneurship, spin-offs, and start-ups

Assessment of the opportunity for new business creation based on the research results achieved. The development and scale-up of innovative ideas will be supported. This task will provide incubation services too.  

Task 7.4 – Cascade funding management

This task will collect and address the needs of all WPs in spoke 1 for procuring goods and external services that are functional to WPs activities.  

List of Deliverables:
  • D7.1: Sustainability Management Plan, M12
  • D7.2: IPR management and exploitation services, M12
  • D7.3: Data-Driven approaches to Technology Transfer, M24
  • D7.4:Business-oriented services, M36
  • D7.5:Cascade funding management, M48