This challenge arose directly from conversations prior to the opening of the competition, between a group of Iscte teachers (under the aegis of the IA>AP Competence Center, https://iaap.iscte-iul.pt) and members of the PlanApp board. Among the tasks that were considered interesting for exploring and testing possibilities, the following stood out (in the area of AI / Data Science): 1. Analysis of topics from the outputs of the “Building Bridges” workshops 2. Extraction, processing and analysis of inequality monitoring indicators 3. Extraction of fields in public policy planning documents 4. Analysis of demographic indicators Task 1 aims to test the possibilities of semi-automatic processing of conference output in order to reduce processing time and/or flag up particularly relevant parts for the PlanApp of the documents resulting from the “Science and Public Policy Workshops: How to build bridges?”. In these workshops, participants are invited to write short texts with proposals, difficulties and challenges related to the interaction between academia and public policy, but the manual processing of this amount of text is demanding in terms of reading time for the organizers, and a semi-automatic processing is beneficial, which can not only highlight the most addressed topics, but also point out the most relevant parts (or those that address more original topics). The aim of Task 2 is to help with the implementation of the Inequalities Report, where PlanAPP has developed quantitative (description and simulation) and qualitative analyses of various dimensions of inequality. One of the main difficulties in this process is the continuous need to merge information from different sources. The aim of this task is to map the various sources and organize the process of merging and cleaning data, which will allow for a more stable analysis of these indicators. Task 3 is a task of structuring semi-structured documents. Public policy planning documents are usually semi-structu...

xShare envisions everyone sharing their health data in EEHRxF with a click-of-a-button. The xShare button to be featured across health portals and patient apps and allow people to exercise their data portability rights under GDPR. Hence, the European EHRxF will be the driver for research and innovation in EHDS. xShare will establish the European EHRxF Standards and Policy Hub, the “Hub” partnership of six standards developing organizations (CEN/TC251, HL7 Europe, IHE Europe, SNOMED, CDISC, IEEE) market actors (DIGITAL Europe, MedTech-Europe and EUCROF), supported by competence centers, nationals and regional authorities and European SMEs. xShare will develop: 1) Harmonized common specifications, create and maintain xBundles i.e., collection of common data specifications including FHIR implementation guides, tools and data sets, and educational support for key EHRxF health information domains as noted in the EHDS draft regulation Annex 1. 2) A set of common elements across EHRxF health information domains applicable across EHDS-1 (Xt-EHR), public/population health (EHDS-2), and clinical research. 3) Extended harmonized IPS specification to include care plans and making it fit for the purpose of clinical research use cases i.e. clinical trial eligibility, real world data, patient reported outcomes, and returning clinical research data to patients. 4) xShare feature the xShare Button in 8 adoption settings in Hospital network (Italy), National portal (Greece, Ireland, Cyprus), regional network with emphasis in medical tourism and the connection of the public to the private sector (Catalunya and Madeira), entry of digital health applications to the myHealthSpace ecosystem in France. Care plans will be demonstrated in Denmark. xShare investigate the feasibility and value of the EU xShare Industry label as a vehicle towards implementing the draft EHDS regulation. Lastly open calls at the last year of the project aim to onboard with EHRxF almost 100 settings across Eu...

This study contributes to the knowledge of the reality, the risk assessment and the definition of fraud prevention strategies associated with the use of European funds in Portugal.  The main objectives of this study are: * To collect information, process, systematise and analyse data on European funds in Portugal, particularly regarding situations of irregularities in their use; * To identify opportunities for improvement in the process of data collection, in the management of information systems, and in the sharing of information between the various organisations involved;  * To increase transparency in the use of funds in Portugal.  Entities involved: Iscte, NovaSBE, ADC, IFAP, PGR Project starting date: 1 April 2022 Duration: 12 months

The object of study is the timely prediction of the possibility of non-compliance in terms of timings or financial targets. This research will test the potential of a system capable of generating an alerts for the possibility of non-compliance based on known data at the time of application or at key moments in the project's monitoring. This alert should be substantiated according to the studied variables that are directly involved in this result, in order to support a properly informed decision.   

The project aims to improve incentive management, using machine learning approaches to identify operational and strategic risk levels in the analysis and verification phases of project payment requests.

Project Title: Graduates Advancement and Development of University capacities in Albania (GRADUA)   Duration: 4 years (15/10/2017-15/10-2021)   Project reference number: 585961- EPP-1-2017-1-AL-EPPKA2-CBHE-SP   Programme: Erasmus +   Action: Capacity Building in Higher Education (CBHE)   The project aims at set up in Albania an innovative IT based platform for graduates tracking and employability at support of policy making and HE reform. The platform is different with respect to existent experiences (databases/job intermediaries): it is an integrated and certified demand/supply matching model based on the online DB of Albanian graduates, easily “replicable” in new universities. The platform has a twofold scope:   -enhance university enterprise cooperation and graduates employability in a unifying context of data aggregation, graduates monitoring and university-enterprises cooperation. Online graduates CVS are certified by universities, made available to companies that can check and compare on line by university, faculty and degree course level the graduates to hire according to set of variable (i.e.academic career, language and IT skills, experiences, expectations). Graduates can update their CVs and directly send their candidature to the firms through the platform. The efficacy of AL in job intermediation with respect to other systems is proven by figures (Bargues and Sylos Labini 2009).   -strengthen both the effectiveness/efficiency of the whole HE system through IT based practices and methodology: the platform is conceived to provide  documentary evidence for decision making processes,  new programmes planning and methodology, with particular attention to training activities and services to students (graduate’ profile survey). It is an integrated model as the surveys’ high response rates together with the statistical quality of data depends on the graduates’ fidelization effect achieved thanks to the placement services offered to them.   The pro...