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Integrated Research Infrastructure Services for Climate Change risks

Adaptation to climate change requires in-depth understanding of climate change driven risks, including their determinants (hazards, exposure and vulnerabilities) and impacts to human, production and natural systems. Integrated Research Infrastructure Services for Climate Change Risks (IRISCC) is a consortium of diverse and complementary leading research infrastructures (RIs) covering disciplines from natural sciences to social sciences, across different domains and sectors. IRISCC provides scientific and knowledge services to foster cutting-edge research and evidence-based policymaking to improve Europe's resilience to climate change. IRISCC ensures a “one-stop-shop” for various user communities on climate change risk related RI services by setting up a dedicated Catalogue of services and related access management system both for granting transnational (onsite and remote) and offering virtual access. The Catalogue of services will be built through three consecutive releases, each delivering increasingly integrated services to its user communities. The IRISCC service integration will include Service Design Labs employing co-design and transdisciplinary action, and Service Demonstrators benchmarking the integrated cross-RI services. In addition to services aimed towards the scientific community, IRISCC will offer knowledge services aimed towards policymakers and other stakeholders. This is done together with risk management platforms. The research enabled by IRISCC contributes to future reports on climate change effects (IPCC, IPBES) as well as policy- and decision-making to meet the targets of climate adaptation strategies. IRISCC contributes to training a new generation of scientists to efficiently use RI services and for data stewardship. Data from IRISCC will be open and made available in compliance with FAIR principles and linked to European initiatives such as EOSC. Strong links will be created between IRISCC and current and future efforts under Horizon Europe.

Internal Fortress: Regulating European Freedom of Movement within the Nation-State, 1950-1980

Against the prevailing view that freedom of movement lowered internal barriers to movement while raising walls against outsiders to create a ‘fortress Europe,’ this project investigates how the introduction of freedom of movement may have strengthened national political authority over European migration within the member states of the European Economic Community (EEC). InternalFortress suggests that as governments gradually lifted entry restrictions across the EEC, they also built out new internal administrative machinery to insert ‘Community migrants’ into key areas of social and economic life, placing migrants from outside the bloc at a disadvantage within local communities. The project explores this hypothesis in three key areas: social security, skill development, and union participation. The PI will lead a team of two PhD researchers and one postdoc to deploy a methodologically innovative multi-layered research program that analyses the interplay between national, European, and international institutions, as well as the private NGO networks that flowed between those formal frameworks. In contrast to previous histories of freedom of movement, which explain policy outcomes leading up to today’s regime of European citizenship, InternalFortress makes an important interpretive innovation by focusing squarely on the early process of transition from the 1950s to the 1970s. The project will investigate how the improvised nature of early integration created gaps and tensions that were consolidated in the 1970s as national and regional migration policies settled into more rigid patterns. InternalFortress suggests that policies behind the border matter as much as policies at the border for understanding the acrimonious debates around European migration that continue through the present.

International Platform on Obstetric Violence (IPOV): an innovative tool for a respectful maternity and 
childbirth care

Over-medicalisation and disrespect in maternity and childbirth care have been identified by international research as an urgent global public health topic (WHO 2014, Simonovic 2019, Council of Europe 2019). The IPOV-RESPECTFUL CARE project intends to bring attention to obstetric violence and respectful maternity and childbirth care by implementing a concrete tool—the International Platform on Obstetric Violence—to bridge academic research and public policy, training for health professionals, women’s perspectives and public engagement on the matter. The Platform will be an innovative, international, interdisciplinary, intersectoral and cross-cultural digital and interactive tool for producing, sharing and transferring knowledge, systematising and exchanging good practices, acquiring skills and planning gender -based innovative training packages on respectful maternity and childbirth care among health professionals, health training managers, decision makers, researchers, women and all of society. To achieve these goals, a network of 39 breakthrough experts, from 19 participating organisations and 9 countries (universities, research centres, civil organisations and health maternity care institutions) will be established.

Concept development for a research infrastructure to manage, integrate and sustain large medical cohort studies

The INTEGRATE-LMedC consortium will develop a new concept to guide and support decision-making for the next-generation research infrastructure (RI) to facilitate efficient utilization and harmonization of large medical cohorts (LMedC), and to accelerate scientific and medical breakthroughs in Europe and beyond. Achievement of the ambitious objectives will only be possible through the integration of 11 highly interdisciplinary partners including established ERIC / ESFRI infrastructures such BBMRI,  ECRIN, EIRENE and EBRAINS with unique expertise in conceptualizing and implementing European RIs. The partners will generate a gap analysis to identify what is missing of cohort data and samples, RI tools and services, quality measures, governance models, user needs and the barriers for efficient utilization of these cohorts and RI, including ethical and legal frameworks. To identify IT technologies and architecture for suitable data stewardship and long-term availability of European RIs, the partners will prepare for a feasibility study for federated data analysis of LMedC. The feasibility study will be based on two examples of use-cases: one stroke case using data from medical health registry data and one case using data from longitudinal population-based studies with different technical, legal, and ethical challenges. To ensure availability of data and samples related to existing and future LMedC studies and their re-use for secondary research, the partners will develop a concept outline including a governance plan and guiding principles for data access policies and data protection policy, whilst considering the FAIR principles and ELSI issues. An overarching RI concept to manage, integrate, and sustain LMedC studies will be developed, including an initial financial and operational plan for the implementation of the new RI outlining new services and access opportunities for the research community.

REGULAR AND UNPLANNED CARE ADAPTIVE DASHBOARD FOR CROSS–BORDER EMERGENCIES

During cross-border health emergencies, health and care services may be overwhelmed by high numbers of patients requiring unplanned care. Delays and backlogs in regular care, as a result of the stretched health care system, leave millions of patients with regular care needs unattended, resulting in disastrous healthcare outcomes. If poor healthcare outcomes across the population are to be avoided, healthcare systems must become more resilient and flexible and allow for rapid changes in the care delivery services. RAPIDE’s aim is to develop, validate and demonstrate a portfolio of powerful tools that enable healthcare systems to build in robustness of decisions, resilience of the health care professionals and patients and flexibility in the modalities of care delivery, thereby maintaining access to regular care during health emergencies. 

RAPIDE emphasises opportunities for optimising in-hospital care, but also for relocating care from hospitals to community and home environments without loss of care quality. Thus, the project focuses on two closely-linked challenges – 1: Identifying and predicting how much care, and which care, needs to be moved along the care chain; 2: Identifying and verifying effective, feasible and acceptable ways to make this reconfiguration of care a reality. This will be achieved by (a) resource modelling, which builds comprehensive foresight and forecasting solutions and links them to patient flows optimization, along the whole chain of care, (b) selecting and implementing the best available tools to deliver regular care in new ways. To ensure usability, acceptability and equitable real-world value, RAPIDE will be co-designed and co-validated with stakeholders, from patients, GPs, clinicians and hospital managers to health ministries, pandemic-management and public health agencies. A Table Top Exercise and extensive communication and dissemination will raise awareness of the project’s successes.

Transition to safe & sustainable food systems through new & innovative detection methods & digital solutions for plant-based products derived from new genomic techniques, under a co-creation approach

DARWIN aims to contribute to a fair, healthy, safe and environmentally friendly food system by co-developing an innovative detection strategy by integrating targeted analytical PCR-based methods, untargeted sequencing methods, and digital solutions. A new generation of innovative and reliable DNA-based analytical detection methods, ranging from enhanced PCR methods for NGT detection, identification and quantification in single and multi-target systems, to untargeted sequencing methods related to whole-genome sequencing, laser capture microdissection-based sequencing and high throughput metagenomics sequencing for NGT screening and characterization. DARWIN will bring a cutting-edge approach developing genetic fingerprints using artificial intelligence to overcome challenges related to event-specific targeted methods, unambiguously identifying specific NGT lines. DARWIN also brings innovation in the new application of digital solutions such as data spaces and documentation-based screening to increase the data evidence to NGTs; blockchains to enable transparent and traceable detection along the food chain; AI models; and a Decision Support System to improve accuracy and support the selection of the best fit for purpose detection methods. DARWIN will reach TRL4-5 though validation including in-house, transferability and full trials, and presenting 3 cases representative of real situations relevant for NGT products in the EU agri-food market. After methods validation and the definition of a clear oriented detection strategy, DARWIN will theoretically extrapolate its finding to more complex scenarios encountering the diversity of NGT lines and food products that might reach EU markets. All this, under an interdisciplinary co-creation ecosystem based on Responsible Research and innovation (RRI) principals, empowering a wide variety of stakeholders - including consumers - in Europe and internationally; and robustly contributing to the policy making.

Interoperable applications suite to enhance European identity and document Security and fraud detection

Combatting frauds on identity and travel documents is a key mission of law enforcement agencies and border guards. Industries have been working on new means to combat frauds on identity, and public authorities are using numerous technologies to accomplish their mission, but permanent innovation is required to fight highly skilled defrauders. A number of European innovation projects have tested new ways to combat fraud but few of them reached an operational level.
EINSTEIN objectives is to enhance significantly existing public authorities’ means through innovation, building on technologies proven in the labs but not mature for an operational usage yet. EINSTEIN will deliver six applications essential to fight identity frauds: 1) online ID issuance using a secure cloud-based server for real-time biometric quality checks and fraud detection, 2) mobile document and identity checks using commercially available smartphones, 3) document authentication module to detect fraudulent documents, 4) pre-registration for land-border crossings including biometrics and DTC, 5) EES kiosk with advanced fraud detection using video surveillance, 6) fast track for enrolled travelers using on-the-move face and iris. To ensure TRL7 at a minimum, practitioners will run six different pilot use cases in their own environment. A key objective is also to ensure interoperability and flexibility of all the components developed in the project so that they can be reused in different contexts, possibly by different providers. Design of open, well-defined, standardized interfaces will allow achieving this objective.
Privacy being an essential concern of all European citizens and governments, EINSTEIN will take into account privacy-by-design principles, developing flexible components to ease their customization in order to meet not only the European legislation on data protection but also national legislations on this matter, which vary significantly from one country to the other.


Waste in humanitarian Operations: Reduction and Minimisation

Waste in humanitarian Operations: Reduction and Minimisation (WORM)'s overall objective is designing guidelines and support actions for circular economy in the humanitarian sector. WORM focuses on two selected settings: field hospital deployments, and humanitarian livelihood programmes with a waste picking component. Across these settings, the project focuses on several cross-cutting focus areas: 
•	the integration of bio-based technological innovation solutions in the humanitarian context, 
•	using procurement as a gatekeeper for waste avoidance, and gateway to integrate innovative solutions, 
•	improvements in waste management, and the use of less polluting waste treatment methods, 
•	a specific focus on the sustainable livelihoods of waste pickers, and 
•	policy development, advocacy and a heightened local awareness of improved waste management in the relevant local contexts.
Following a multi-actor approach, WORM brings together medical humanitarian organisations and humanitarian organisations with livelihood programmes with innovation and supplier clusters, procurement service providers, logistics service providers, waste management service providers and academic partners. WORM seeks to involve a myriad of different stakeholders in data collection and policy development, including but not limited to, humanitarian actors positioned in the field during an operation, local waste management companies, start-ups focusing on bio-based solutions, policymakers (both local and global), and research institutions. WORM includes partners from low- and middle-income countries (esp. Kenya, Viet Nam) since humanitarian operations are often implemented in these contexts. WORM will focus on these contexts in their local awareness campaigns for improved waste management.

Supporting Policy Regulations and Interventions to Negate aggravated Global diarrheal disease due to future climate Shocks

BACKGROUND: Global warming and climate extremes such as heavy precipitation, flooding, and drought are increasing risks for waterborne diarrheal disease. While these effects already burden low- and middle-income countries, where diarrheal diseases are the second leading cause of childhood deaths, Europe has shared and underappreciated vulnerabilities. There is an urgent need to prepare and protect our water and communities from these threats.
AIM: To inform key climate, environmental, and health adaptation policies, in order to support and prepare citizens, communities and governments by better measuring the impact of future climate shocks on the burden of water-borne diarrheal diseases.
APPROACH: We bring together scientists from climate, environment, health, and social sciences to collaborate with communities, industry, public authorities and policy makers across socioeconomic settings. We will model the future impact of global climate change, on local water quality and quantity, and diarrheal disease outcomes. In case studies in Ghana, Tanzania, Italy, and Romania, we will measure current interactions of climate, behaviour, and water quality on pathogen-specific diarrheal disease risks and the safety of water supply systems. We will engage individuals and communities to understand situated understandings and practices to improve risk communication and ownership. With policy makers, we will design appraisal structures to assess the economic impact and value of planetary health interventions to prevent climate-related diarrheal disease.
IMPACT: SPRINGS will improve integrated climate and health surveillance, create climate-resilient water supply systems, engage citizens and stakeholders, and use evidence-based value assessments to prioritise interventions to prevent climate-induced diarrheal disease.  Long term adaptive capacity and climate-resilience will increase in Europe and beyond, preventing unnecessary illness and deaths from waterborne diarrheal disease.

COordination MEchanism for Cohorts and Trials

The overall goal of COMECT is to coordinate activities across Europe’s strategic adaptive platform trials (APTs) and cohort studies (CS) on infectious diseases (IDs) with epidemic or pandemic potential, by overseeing and facilitating dialogue, sharing of good practices, promoting collaboration and coordination across studies and providing updated information on initiatives and innovation in ID clinical research.
COMECT will build on and strengthen existing networks and infrastructure. These include EU-funded coordination mechanisms and networks, namely the Trial Coordination Board (TCB), Joint Access Advisory Mechanism (JAAM), the Cohort Coordination Board (CCB), and the ECRAID Coordinating Comittee. COMECT will develop a visible, well-defined coordination mechanism to highlight Europe's capacity and competence as an attractive base for clinical research.

COMECT will deliver:
1) an expanded, combined  European coordination mechanism that will work on harmonizing research initiatives, exchange of good practices, and stakeholder engagement across ID clinical studies in outbreaks and during inter-epidemic phases.
2) a strengthened JAAM to support coordination through independent scientific assessment of compounds/vaccines and recommendations for APTs to evaluate the new compound in new or adapted platform trials.
3) the mapping of stakeholders and their respective activities relevant to APTs and CS
4) a harmonised approach cross-study identification, assessment, and reuse of participant-level data from European APTs and CS
5) coherent communications and stakeholder engagement across all activities
6) a sustainability plan for the continuation of activities beyond the funding period.

COMECT will quickly adapt coordination efforts to a changing research landscape and to new ID threats. COMECT will operate in close collaboration with other emergency preparedness mechanisms, such as HERA, EMA, GLOPiD-R and the European Pandemic Preparedness Partnership.

Midlene fra CL5-Climate, Energy and Mobility fordelt på år

Midlene fra CL5-Climate, Energy and Mobility fordelt på fylker

Midlene fra CL5-Climate, Energy and Mobility fordelt på fagområde

SyntAIr - IMPROVED ATM AUTOMATION AND SIMULATION THROUGH AI-BASED UNIVERSAL MODELS FOR SYNTHETIC DATA GENERATION

The main objective of SynthAIR is to explore and define AI-based methods for synthetic data generation in the domain of ATM system due to the limitation of AI-based tools development by the lack of enough data available (e.g., safety-related data) and the problem of  generalization of those AI-based models. We want to explore data-driven methods for synthetic data generation, since they require 1) less user knowledge expertise (no need to derive the explicit model of the distribution), 2) better generalization capabilities. More in detail, inspired by recent advancement in Computer vision and Language Technology, we propose the concept of Universal Time Series Generator (UTG). A UTG, is a model trained on several different time series, and able to generate a synthetic dataset representing a new dataset, simply conditioned by a compressed representation of it. In aviation domain, this generator can be trained on a certain set of data related, for example to few airports, and be used to generate synthetic data from a new airport. The same principle can be applied to define a universal time series forecaster (UTF) able to do prediction to a new environment (I.e., data from a new airport) without any new training.

Med utviklingen av nye innovative seismiske metoder bør det være mulig å ytterligere å øke oljeutvinningen fra eksisterende felt. Dette er fornuftig fra et miljømessig og et økonomisk perspektiv. Seismiske metoder gjør det  generelt mulig å avbilde sedimentære basseng og reservoarer (knyttet til petroleumsproduksjon, CO2-lagring eller geotermisk energi) basert på  essensielt samme prinsipper som i medisinsk avbilding. 

Begrepet 4D-seismikk refererer til gjentatte seismikkinnsamlinger over tid. Ved help av 4D-seismikk kan man "høre" den dynamiske oppførselen til reservoaret og få hjelp til  reservoarstyringen. Den største verdien av 4D-seismikk er den tilleggsinformasjon man får til å oppdatere en modell av reservoaret, samt hjelp til lokalisering av udrenert olje og strømningsbarriærer, noe som er viktig for brønnplanlegging. 

I det geofysiske fagsamfunnet har full seismisk bølgeformsinversjon (FWI) dukket opp som den endelige og ultimate løsningen til jordens oppløsnings- og avbildings-problem. FWI kan potensielt inneholde en fullstendig numerisk simulering av det virkelige bølgefeltet, hvor observerte bølgeformdata blir reprodusert ved hjelp av invertert modell av undergrunnen. Men FWI står overfor mange utfordringer, inkludert følsomheten til resultatene for valg av startmodell og dens enorme beregningskostnad. 

Vi har i dette prosjektet addressert disse utfordringene og utviklet spredningsteoretiske metoder for Bayesiansk FWI som gir informasjon om usikkerheten samt de mest sannsynlige verdier av endringene i (retningsavhengige) elastiske parametere som bestemmer 4D seismisk respons til et petroleumsreservoar i produksjon. I tillegg har vi utviklet forskjellige strategier for inversjon av 4D seismiske bølgeformsdata og forsket på effekter av elastisitet og anisooropi.  Alt dette er nyttig for en kvantitativ integrering av 4D-seismiske bølgeform og produksjonsdata, som kan gi en bedre reservoarstyring. 

I løpet av prosjektperioden har vi publisert mer enn 15 fagfelle-evaluerte artikler i internasjonale tidsskrift.  I tillegg har vi publisert et tilsvarende antall skriftlige konferansebidrag og gitt mange muntlige foredrag på internasjonale konferanser.  Vi har også vekselvirket med bruker fra industrien for å få tilbakemeldinger  på utviklingen av våre seismiske metoder. 

En PhD-kandidat fikk muligheten til å jobbe med dette prosjektet i samarbeid med prosjektleder fra Universitetet i Bergen, to reservoar-matematikere fra NORCE og ledende internasjonale samarbeidspartnere ved Universitetet i California og the Tsjekkiske vitenskapsakademiet. 

PhD-kandidat Xingguo ble ferdig med doktorgraden et halvt år før tiden og fikk pris for beste kinesiske utenlandsstudent. Som et resultat av dette prosjektet arbeider Xingguo nå som full professor i geofysikk ved et ledende kinesisk universitet. Prosjektet har også bidratt til utdanning av flere mastergradskandidater som enten arbeider med seismikk eller relaterte emner som akustikk.

The principal aim of this project is to develop methods for Bayesian inversion of 4D seismic waveform data that provides information about the uncertainty as well as the most likely values of the inverted seismic or elastic parameters. The main idea behind the project is that we can reduce the computational cost of a Bayesian FWI in time-lapse mode by using a target-oriented scattering-integral approach which is based on an explicit representation of the data sensitivity matrix and compatible with the use of general domain decomposition and renormalization methods for strongly scattering media. We have already significant experience from the development of the scattering-integral approach within the framework of Tikhonov regularization, but more work related to the Bayesian (statistical) approach is needed. The methods we propose to develop will be relevant for both seismic exploration and production monitoring. However, our numerical examples will be biased towards applications within dynamic reservoir characterization. Therefore, we shall also investigate different strategies for dealing with time-lapse seismic waveform data and rock physics models within this scattering-based framework for FWI and seismic history matching.

Bayesian inversion of 4D seismic waveform data for quantitative integration with production data

The principal aim of this project is to develop geophysical methods for better fluid and reservoir characterization. The main idea behind the project is that one can use the same kind of forward and inverse scattering series methods for the modelling and  inversion of seismic waveform and CSEM data. Traditionally, workers in the seismic and electromagnetic geophysical communities have not communicated much with each other, although there is a great potential in the modification of  methods originally devel oped for use in electromagnetic geophysics for use in seismic geophysics. Also, having similar methods allows us to set up a consistent model for the seismic and electromagnetic properties of a reservoir, and to develop more efficient and accurate systems  for joint inversion of seismic and CSEM data. The methods we propose to develop will relevant for both exploration and production, although our numerical experiments may be biased towards applications to geophysical reservoir monitoring.

0 antall prosjekter

PETROMAKS2-Stort program petroleum

Bayesian inversion of 4D seismic waveform data for quantitative integration with production data

Tildelt: kr 6,2 mill.

Prosjektperiode: 2017-2020

Sted: Vestland

PETROMAKS2-Stort program petroleum

Modelling and inversion of seismic waveform and electromagnetic data using integral equation methods

Tildelt: kr 4,4 mill.

Prosjektperiode: 2013-2017

Sted: Vestland