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Implications of digital transformation for migrant labour

Accelerated by the Covid-19 pandemic, rapid digitalisation has fundamentally transformed European working conditions. While its positive consequences are well recognised, digital transformation also puts a sorely needed part of the European workforce at risk of unemployment, poverty and social exclusion. IDILAB (Implications of digital transformation for migrant labour) investigates the impacts that technological progress and subsequent structural changes have on the labour market integration of migrant workers. By developing a new methodological approach, IDILAB shall provide novel evidence on migrants’ exposure to the process of digitalisation, and formulate evidence-based and innovative policy options for the EU and national governments to improve on the scope and adequacy of national and European policy directed at encouraging a fair digital transition for all, including migrants. The proposed project will contribute with new knowledge on migrants’ own perspectives on barriers and enablers for a sustainable integration in a fast-changing labour market. I, the experienced researcher (Dr Olga Gheorghiev, the Czech Republic), will work with a European centre of excellence (the Research Centre for Digitalisation of Public Services and Citizenship (CEDIC, OsloMet, Norway), and the European Trade Union Institute (ETUI, Belgium) for intersectoral knowledge transfer, career development, and European added value.

CULTUral heritage in RurAL remote areas for creative tourism and sustainabilITY

The main objective of the project is to contribute to the promotion of cultural and creative tourism activities, considering the different capacities, resources, and specificities (material, creative, human...) of the territories, as a mean to help with the sustainable development of peripheral rural areas, favoring job creation and population settlement. For this, the potential of its cultural heritage will be researched, taking into account both the artisan material culture (techniques, materials, patterns and decorative elements), as well as the intangible culture (music, oral knowledge and culinary traditions) as a resource.
 
To promote non-seasonal tourism as a form of sustainable development with a stable population settlement we are going to research the crafts linked to the territory and their implications, but we will also carry out a documentation of the productive processes. First and foremost, we are going to cater to the necessities of the local communities and pay attention to aspects related to societal groups at risk of exclusion, such as women, the elderly and the youth.

All this will be developed from a multidisciplinary perspective, for which we will count on the various teams —most of them linked to different countries— that will be part of the consortium. Each of these partners will contribute to the development, as well as to the final result of the project through input directly related to their area of ??expertise: for example, among the collaborators we have intellectual teams specialized in the digitalization of heritage, research, or communication and dissemination, as well as as various institutions that will act as a testing ground for the more practical parts of the proposal. However, if something will characterize our work, it will be the constant collaboration between all parties, as well as the exchange of advice and experiences that will help to enrich collective knowledge and guarantee optimal results.

POWERING ARTISTIC AND CULTURAL ENTREPRENEURSHIP TO DRIVE THE CLIMATE TRANSITION

PACESETTERS responds to the abstract challenge of the climate transitions by shifting from a model of entrepreneurship based on individual, short-term incentives to one that is driven by co-agency and new capacities to act together in sustainable ways. It does so by examining the concrete circumstances, investigating possible support mechanisms and stress-testing instruments that enable art and culture, creativity and heritage to drive the climate transition.
Therefore, PACESETTERS will set out to:
-Create knowledge from collaborative research to keep pace with the transition
-Propose and test creative business models to set the pace of the transition
-Assess strategies of valorisation to push the pace of the transition
 
This approach will identify and analyse advanced practices that run transversally across the cultural and creative sectors; contextualise the outcomes of co-research in real-world laboratories for social imagination; further develop and promote the preliminary results of experiments in iterative support and evaluation frames. The PACESETTERS approach centres on inclusion, participation and iteration in order ensure that gender equity and diversity inform it at every step and on every level.

The result will be a critical evaluation and all-encompassing demonstration of the actual potentials of the CCIs to drive the climate transition while systematically analysing their impact on micro-, meso- and macro-level:
-Understanding the climate transition as a triple transition: green, digital and inclusive
-Innovating aPACESETTERS responds to the abstract challenge of the climate transitions by shifting from a model of entrepreneurship based on individual, short-term incentives to one that is driven by co-agency and new capacities to act together. It does so by examining the concrete circumstances, investigating possible support mechanisms and stress-testing instruments that enable art and culture, creativity and heritage to drive the climate transition.

Strengthening resilience and mental wellbeing through the Support4Resilience toolbox for leaders in elderly care

European elderly care experiences labor shortages, lack of qualified workers and a mismatch between capacity and demands, causing stress, burnout, and reduced mental wellbeing among healthcare workers and informal caregivers. Leaders are crucial in promoting supportive working conditions but lack research-based measures to act upon these challenges.

Support4Resilience (S4R) will develop, implement, and evaluate a research-based Toolbox to support healthcare leaders in improving healthcare workers’ and informal caregivers’ resilience and mental wellbeing in elderly care. S4R will identify resilience and mental wellbeing factors among healthcare workers and informal caregivers; explore their perspectives and needs; develop new theory on the relationship between individual and organizational resilience, and mental wellbeing; and develop recommendations and cost-effective interventions. The Toolbox with tailormade resources for policy and practical use will be available through an open access S4R Resource Bank.

The S4R Toolbox includes three main tools: 1) Mapping and identification, 2) Reflection and education, and 3) Reorganization. Measures are initiated at the organizational level and effects on mental wellbeing and resilience transpire at the frontline of elderly care. The Toolbox covers different situational contexts, types of healthcare providers and health system levels. Elderly care settings in six European countries will implement and evaluate the Toolbox through a process evaluation, effectiveness evaluation, and cost-effectiveness evaluation. 

S4R provides policymakers, decisions-makers and leaders with solutions for taking action to solve specific risks for healthcare workers’ and informal caregivers’ resilience and mental wellbeing. Thus, pertinent to the work programme, S4R will support the development of resilient health systems in European elderly care through improved leadership capabilities, governance structures, and adaptive capacities.

Providing research infrastructure services to support Next Generation EU

This four-year project will harness outputs from key social science RIs in Europe and other reliable sources to support the aims of the ‘Next Generation EU’ programme and to inform EU youth policy. Virtual access will be provided to the outputs through special installations (portals) developed during the project. The core of the proposal is a set of existing research ‘services’, which will be re-purposed and customised to focus directly on the five themes: Make it Green; Make it Digital; Make it Healthy; Make it Strong; and Make it Equal. 

For each area, the consortium will work collaboratively to produce seven sets of resources:

i)	A searchable inventory of relevant variables drawn from multiple cross-national datasets; 

ii)	Analytical summaries, suitable for policy makers and analysts new to the field, as well as interactive resources available through the project portal;

iii)	Harmonised and merged extracts from these datasets that reduce the burden on analysts and increase sample sizes;

iv)	New data collected through the ESS’s established CRONOS web panel infrastructure. Eleven countries will field five waves of the panel, each one dedicated to a NextGenEU theme. Free and rapid access to the data will be available through the CRONOS portal alongside analytical summaries;

v)	In-person and virtual deliberative forums with young people (aged 18-34) in four countries covering the five Next Generation EU’ themes;

vi)	An educational tool (E-NextGen) channelling our data for use in classrooms and by the general public;

vii)	Comprehensive training materials related to all project outputs.


Mapping of Longitudinal data of Inequalities in Education

The MapIE project aims to identify mechanisms causing educational inequalities and policies or interventions compensating for them. We do a systematic review of how these have been studied internationally using longitudinal designs. We map existing longitudinal data that we describe in a public metadata database, and we analyse them to describe the mechanisms of inequalities and to identify effective policies and interventions in different local contexts. We focus on the contextual differences between the Nordic and Central European countries that have structurally different education systems. Within national contexts and using comparative research designs, we look at system-, regional- and school-level policies and practices and individual-level factors (e.g. socioeconomic status, immigrant background, gender, special educational needs) that are associated with the development of educational inequalities and the successful prevention of achievement gaps. We publish and disseminate the empirical results of the project through multiple channels to scientific audiences, policy makers and the wider public. At the end, we create a public framework for studying educational inequalities longitudinally in future studies, acknowledging the role of local contexts but aiming for comparability at the European level. 

We implement the project in seven work packages. Our consortium consists of internationally acknowledged experts in large-scale educational assessment research from Finland, Sweden, Norway, Hungary and Luxembourg/Germany. The partners have a long-standing history of collaboration with each other, European researchers, and national and international education policy makers, and they bring extensive longitudinal datasets to the project. The project will considerably strengthen the knowledge base of what shapes educational outcomes over time, how to best support the learning of all students and how to reduce education inequalities in the short, medium and long term.

Contextualized pathways to reduce housing inequalities in the green and digital transition.

The project Reducing housing inequalities in the green and digital transition (ReHousIn) is committed to better understand the impacts of recent crises on housing inequalities across different European regions, especially with regard to the implementation of the green transition launched by the EU. The overall aim is to explore the mechanisms affecting the (re)production of housing inequalities under recent crisis conditions, and the impacts of the EU induced green transition in different national contexts and along different degrees of urbanisation. Based on a contextualized and comparative understanding of the mechanisms (re)producing housing inequalities, ReHousIn inquiries into multi-level pathways and inclusive local housing initiatives to spark innovative EU, national and local policy solutions towards inclusionary and quality housing, mitigating the possible negative impacts of the EU induced green transition. It conducts a comparative, multi-level analysis in 9 European countries – Austria, France, Hungary, Italy, Norway, Poland, Spain, Switzerland, United Kingdom – focusing on attractive metropolitan regions, middle-sized cities and rural areas by means of a mixed-method project design. A quantitative data analysis on recent trends in housing inequalities and their relation to crises across different levels of urbanization will provide the framework for 27 local cases studies in which the impact of multi-level trajectories of housing-system, welfare regimes and environmental policy instrumentations on the (re)production of local housing inequalities and the emergence of inclusive housing initiatives are analyzed. Based on this, ReHousIn compares mechanisms of differentiation feeding into policy labs, aiming to formulate recommendations on how to tackle negative social externalities related the EU green transition at EU, national and local levels.

Strategies for achieving equity and inclusion in education, training and learning in democratic Europe

STRIDE will provide a new, comprehensive and comparative knowledge-base on effective education reforms, policy initiatives and interventions aimed at reducing inequalities in education, training and learning outcomes in Europe. STRIDE will do this through analyses of education reforms in national and regional systems, existing large-scale educational assessment data and existing longitudinal data on the causal link between educational and other social policies and inequalities in educational achievements. In examining the learning progress of students over time, STRIDE will closely examine to the range of intersectional variables such as socio-economic background, gender, (dis)abilities, migration status, home language, early childhood education and care (ECEC) attendance, which may affect learning outcomes in different ways in different contexts. The project will combine diverse methods, data and disciplines (comparative education, political science, education science, sociology) in innovative ways: mapping at national and regional levels on (1) education reforms in the past 25 years by policy analysis, (2) longitudinal trends of inequalities in educational achievement by quasi-experiment analysis of existing large-scale educational assessment data, and (3) effect of education reforms and interventions by analysis existing longitudinal data and registry data following student cohorts over time combined with a qualitative inquiry into policymakers' perspective. Through the involvement of national and European stakeholders, STRIDE will develop methodology and assessment tools for policy learning offering policymakers a toolbox of enhanced knowledge of what shapes educational outcomes over time and demonstrating the usefulness of longitudinal data in policy-making to reduce educational inequalities in the short, medium and long term.

dialoguing@rts – Advancing Cultural Literacy for Social Inclusion through Dialogical Arts Education

d@rts is a catalyst for increasing social cohesion and inclusion, using embodied performing arts activities to develop cognitive and affective cultural literacy. We recognise that the performing arts encompass mass-market consumer goods, as well as non-linguistic, embodied and social activities, providing massive opportunities for inclusive participation.
Our target groups comprise actors of all ages and social positions, especially in the school system and in community arts initiatives. We will empower these groups to be artistically active, dialogically related and culturally literate, giving them tools and motivation to improve their own situations and those of others within the overall frame of a cohesive European society, informed by global perspectives.
Using the post-colonial insight that culture is necessarily heterogeneous, d@rts has four related objectives:
1. Understand how performing arts activities relate to cultural literacy in official discourse and documents across partner countries
2. Use this understanding to build dialogues and co-create physical and digital actions with heterogeneous groups within our target audience
3. Develop assessment tools for these actions, enabling measurable growth in cultural literacy
4. Use our findings in recommendations for cultural and educational policies that build long-term social cohesion and inclusion
Based on these objectives, the overall outputs comprise:
1. Documentary, survey and participatory research findings
2. Performative DIALOGART actions for cultural literacy
3. Policy and practice recommendations to increase social cohesion via cultural literacy actions inspired by the performing arts
d@rts imagines new futures and creates hope and social cohesion through performing arts education. By creating participatory spaces and facilitating dialogues, we empower voices seldom heard. d@rts thus advances cultural literacy, and enhances social cohesion and resilience, to build an inclusive future for Europe.

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.

RagnaRock Geo develops AI-tools for seismic interpretation

Midlene fra FORNY20-FORNY2020 fordelt på år

Midlene fra FORNY20-FORNY2020 fordelt på fylker

Midlene fra FORNY20-FORNY2020 fordelt på fagområde

Forretningsutvikler

RagnaRock Geo benytter maskinlæring for å utvikle et tolkningsverktøy som skal assisterer lete-eksperter når de tolker 3D-kart av undergrunnen (seismikk). RagnaRock Geo har vist at tolkningsverktøyet deres kan spare 6 måneder av den tradisjonelle tolkningsprosessen. Programvaren har generert stor interesse hos oljeselskaper, fordi den bidrar til å kutte store deler av det tidkrevende repetative arbeidet til lete-ekspertene. Dermed får lete-ekspertene mulighet til å fokusere på de verdiskapende delene av tolkningsarbeidet og mer tid til grundig analyse. Dette tillater også analyse av større og flere områder, hvilket er med på å øke sannsynligheten for at oljeselskapet finner olje og gass. Tidsbesparelsene alene tilsvarer lønnskostnader på omlag NOK 500 000 per lete-ekspert årlig, mens den økte sannsynligheten for olje- og gassfunn har en mye høyere verdi.

Innovasjonsgraden i dette prosjektet er svært høy da RagnaRock Geo  evner å utnytte  det fremste innen forskning på maskinlæring for å løse et kompleks problem innen geologi og geofysikk. Selskapet har bygget opp et team som er i en unik posisjon til å løse nettopp disse utfordingene. RagnaRock Geo sitt fokus på dyp maskinlæringskompetanse gjør at selskapet kan sikte mot en nisje i markedet hvor det er stort behov for gode løsninger, men hvor det er veldig få som har kompetanse til å lage løsningene. Selskapet sparrer ukentlig med verdensledende miljøer fra Institutt for Geovitenskap og Petroleum, NTNUs AI-lab (forskningssenter som tar sikte på å bringe all forskningsinnsats innenfor AI sammen) og NTNUs Entreprenørskole. Forskningsmiljøene bidrar til at RagnaRock Geo kan lage et verdensledende kommersielt produkt, som er sentralt for selskapets vekst og ekspansjon.

RagnaRock Geo utvikler kunstig intelligens verktøy for seismisk tolkning

Under en marin seismisk undersøkelse sendes det ut seismiske bølger nær havoverflaten. Jordens respons overvåkes for å utlede informasjon om geologien i undergrunnen. Dette blir gjort ved å innhente  data over tid fra sensorer plassert på et område. Derfor kan de målte dataene sies å være i tidsdomenet. Dataene blir behandlet for å produsere et kart av undergrunnen, der posisjonene til de geologiske grensene blir fremhevet. Denne databehandlingen innebærer anvendelse av en lang rekke geofysiske metoder, og hele arbeidsflyten blir referert til som seismisk prosessering og avbildning. Seismisk prosessering og avbildning har i hovedsak som mål å fjerne de uønskede signalene fra de registrerte dataene og å flytte den seismiske energien til det stedet der den ble spredt eller reflektert fra. De fleste av de seismiske prosesseringsmetodene blir utført i et annet domene enn tidsdomenet. Flytter man data til et annet domene kreves det ofte relativt kostbar bearbeiding av dataene først. Etter hvert behandlingstrinn flyttes dataene tilbake til det opprinnelige tidsromdomenet for å sjekke kvaliteten på dataene. Derfor er seismisk prosessering og avbildning en lang og grundig arbeidsflyt, noe som resulterer i et kart av undergrunnen i veldig høy kvalitet, men kostbart mhp. menneskelige ressurser og computerkraft. Det er allment akseptert at informasjonen i seismiske data har lavere dimensjonalitet enn selve dataene. Derfor kan de seismiske dataene uttrykkes med et redusert antall parametere sammenlignet med antall dataprøver ved å flytte dataene til et passende komprimert domene. 

I det først år av doktorgraden, har studenten utviklet en metode for seismisk datakomprimering som er basert på ?ordliste læring?, dvs. en datadrevet algoritme for sparsom representasjon. Han har testet komprimeringsmetoden på flere datasett og har vurdert effektiviteten i forhold til flere standard seismiske metoder. Blant alle de studerte metodene var metoden han utviklet den mest effektive for å avlevere høye komprimeringsgrad.  

I det andre året av doktorgraden, har kandidaten utvidet den metoden slik at den trekker ut kinematiske bølgefeltparametere fra de seismiske dataene samtidig som den komprimerer dataene. De kinematiske bølgefeltparametrene kan brukes av behandlingsoperatorer for å utføre trinn i seismisk prosessering og avbildning. Basert på de kinematiske bølgefeltparametrene, har kandidaten begynt å designe operatorer for å utføre bølgefeltseparasjon, dvs. et tidlig trinn i seismisk prosessering og avbildning, i det komprimerte domenet. Ved å bruke disse operatorene har kandidaten foreslåt en ny metode som kan komprimere dataene og å utføre ett trinn i seismisk prosessering og avbildning i det komprimerte domenet.

I løpet av det tredje året av doktorgraden har kandidaten utviklet en metode for å anvende deghosting i det komprimerte domenet. Han har videre foreslått i sin avhandling en ny prosesseringsflyt basert på de tre metodene utviklet i hans PhD-studier for å komprimere seismiske data, og anvende typiske forprosesseringstrinn i komprimeringsdomenet. Den foreslåtte prosesseringsflyt reduserer disk- og dataoverføringskravene, og sparer menneskelig innsats og tid i forhold til den konvensjonelle arbeidsflyten.

Marine seismic surveying aims to acquire adequately sampled data according to Shannon's sampling condition both, in time and space. This aim is due to common requirements of conventionally used processing and imaging tools. Although the spatial sampling condition is not always achieved, this leads, nevertheless, for larger surveys to challenges of data handling, storage, processing and imaging.  

Based on characteristic wavefield information, such data is highly redundant and in a previous industrial PhD project, we have exploited this fact to reconstruct missing data in the crossline direction using constrained dictionary learning. In this project, we will derive and develop a new method of dictionary learning, constrained by Hamilton's characteristic function, with the objectives to 1) extract the kinematic wavefield parameters of seismic data and 2) represent the data in a sparse domain by preserving the inherent wavefield information. In the most general form Hamilton's characteristic function for reflection seismic data is defined by two slowness vectors and three traveltime curvature matrices, a total of 14 kinematic wavefield parameters, associated to one reference position (central ray position). Starting from the new dictionary learning we develop a method for data compression in order to facilitate seismic data storage, and finally by fully exploiting the inherent wavefield information, we build new processing and imaging methods which are specially tailored to run directly in the compressed parameter domain.

0 antall prosjekter

NAERINGSPH-Nærings-phd

Seismic data compression using constrained dictionary learning and imaging in compressed domain

Tildelt: kr 1,7 mill.

Prosjektperiode: 2020-2023

Sted: Oslo