ERC FUNDED PROJECTS

"Considerable investments have been made in Europe and worldwide in research data infrastructures. Instead of a general lack of data about data, it has become apparent that the pivotal factor that drastically constrains the use of data is the absence of contextual knowledge about how data was created and how it has been used. This applies especially to many branches of SSH research where data is highly heterogeneous, both by its kind (e.g. being qualitative, quantitative, naturalistic, purposefully created) and origins (e.g. being historical/contemporary, from different contexts and geographical places). The problem is that there may be enough metadata (data about data) but there is too little paradata (data on the processes of its creation and use). In contrast to the rather straightforward problem of describing the data, the high-risk/high-gain problem no-one has managed to solve, is the lack of comprehensive understanding of what information about the creation and use of research data is needed and how to capture enough of that information to make the data reusable and to avoid the risk that currently collected vast amounts of research data become useless in the future. The wickedness of the problem lies in the practical impossibility to document and keep everything and the difficulty to determine optimal procedures for capturing just enough. With an empirical focus on archaeological and cultural heritage data, which stands out by its extreme heterogeneity and rapid accumulation due to the scale of ongoing development-led archaeological fieldwork, CAPTURE develops an in-depth understanding of how paradata is #1 created and #2 used at the moment, #3 elicits methods for capturing paradata on the basis of the findings of #1-2, #4 tests the new methods in field trials, and #5 synthesises the findings in a reference model to inform the capturing of paradata and enabling data-intensive research using heterogeneous research data stemming from diverse origins. "

1 944 162 €

Start date: 2019-05-01, End date: 2024-04-30

In collisions of heavy nuclei at collider energies, for instance at the Large Hadron Collider (LHC) at CERN, the energy density is so high that an equilibrated Quark-Gluon Plasma (QGP), an exotic state of matter consisting of deconfined quarks and gluons, is formed. In proton-proton (p+p) collisions, on the other hand, the density of produced particles is low. The traditional view on such reactions is that final state particles are free and do not rescatter. This picture is challenged by recent LHC data, which found features in p+p collisions that are indicative of collective behaviour and/or the formation of a hot and dense system. These findings have been taken as signs of QGP formation in p+p reactions. Such an interpretation is complicated by the fact that jets, which are the manifestation of very energetic quarks and gluons, are quenched in heavy ion collisions, but appear to be unmodified in p+p reactions. This is puzzling because collectivity and jet quenching are caused by the same processes. So far there is no consensus about the interpretation of these results, which is also due to a lack of suitable tools. It is the objective of this proposal to address the question whether there are collective effects in p+p collisions. To this end two models capable of describing all relevant aspects of p+p and heavy ion collisions will be developed. They will be obtained by extending a successful description of p+p to heavy ion reactions and vice versa. The answer to these questions will either clarify the long-standing problem how collectivity emerges from fundamental interactions, or it will necessitate qualitative changes to our interpretation of collective phenomena in p+p and/or heavy ion collisions. The PI is in a unique position to accomplish this goal, as she has spent her entire career working on different aspects of p+p and heavy ion collisions. The group in Lund is the ideal host, as it is very active in developing alternative interpretations of the data.

1 500 000 €

Start date: 2019-02-01, End date: 2024-01-31

Pollinator declines in response to land-use intensification have raised concern about the persistence of plant species dependent on insect pollination, in particular by bees, for their reproduction. Recent empirical studies show that reduced pollinator abundance decreases densities of seedlings of insect-pollinated plants and thereby changes the composition of grassland plant communities. Cascading effects on ecosystem functioning and associated organisms are expected, but to which extent and under which conditions this is the case is yet unexplored. Here, I propose a bold, multi-year, landscape-scale experimental assessment of the extent of pollinator-driven plant community changes, their consequences for associated organisms and important ecosystem functions, and their likely contingency on other factors (soil fertility, herbivory). Specifically I will: (1) Set up a network of long-term research plots in landscapes differing in pollinator abundance to measure the changes in plant reproduction over successive years, and assessing experimentally how herbivory and soil fertility mediate these effects. (2) Explore the individual processes linking pollinators, plant communities and ecosystem functioning using long-term experiments controlling pollinator, herbivore and nutrient availability, focusing on a sample of plant species covering both the dominant species and a diversity of functional traits. (3) Assess the context-dependence of pollinator-mediated plant community determination by building and applying process-based models based on observational and experimental data, and combine with existing spatially-explicit pollinator models to demonstrate the applicability to assess agri-environmental measures. This powerful blend of complementary approaches will for the first time shed light on the cornerstone role of this major mutualism in maintaining diverse communities and the functions they support, and pinpoint the risks threatening them and the need for mitigation.

1 998 842 €

Start date: 2019-09-01, End date: 2024-08-31

Previous research has investigated the relationship between unemployment and health from a perspective of an isolated individual. HEALFAM takes a novel approach and examines how transition to unemployment triggers diffusion of ill mental and physical health within families. It investigates how becoming unemployed affects health outcomes of partners, children and elderly parents of the unemployed and whether the magnitudes of these influences differ across families and societies. Thus, instead of viewing the unemployed as functioning in isolation, HEALFAM assesses the consequences of unemployment for family members taking a multi-actor perspective and international comparative approach. Guided by the life course theoretical framework, which views health and well-being as a process rather than a state and calls for considering interrelatedness of individuals, HEALFAM employs longitudinal data that provide information about multiple members of families. In order to analyse these datasets, HEALFAM uses longitudinal dyadic data analysis techniques as well as multilevel models for longitudinal data. HEALFAM aims to open a new frontline of research on health and wellbeing from a life course perspective. It benefits from my knowledge on three interrelated social phenomena: (1) the role of labour market career and experiences of unemployment (2) family structure and intra-family resources (3) social antecedents of health and wellbeing among family members. It draws on high quality register and panel survey data as well as the expertise at the interdisciplinary research centres that I am connected to at Umeå University. Through international collaborations, it brings together experts in multiple disciplines carrying out research taking a life course perspective.

1 477 556 €

Start date: 2019-03-01, End date: 2024-02-29