The proposed project employs a cross-national comparative perspective to provide a more comprehensive understanding of the benefits of marriage for earnings and health. The first aim is to examine the applicability of explanatory models in different national contexts. The second aim is to investigate the gendered nature of the benefits and their dependence on national contexts. The project moves beyond prior work on current marital status by investigating the benefits for people in the full spectrum of marital history. State-of-the-art Bayesian methods will be used to obtain unbiased multilevel coefficients on data from 15 countries.

COSMIC (COmplexity in Spatial dynaMICs) is a proposal linking three research groups (VU, UCL and NUIM) dealing with urban science and geo-spatial analysis. The network will focus on urban dynamic processes using new bottom up, digital data collected for entire populations. We believe that such data will provide dramatically new insights into urban change which manifest themselves in often discontinuous forms which can be articulated using a variety of reaction-diffusion dynamics incorporating catastrophe, chaos, bifurcations, and phase transitions. In cities, such reactions range from the emergence of edge cities to patterns of residential segregation, embodying social exclusion in various forms. We first develop a typology of urban dynamic processes to guide the development of models using new digital data collected in real time from electronic transactions such as phone lines, electronic ticketing, and related geo-sensing. Our unifying focus will be on flow data associated with underlying networks with the models revolving around spatial interaction from labour markets to pedestrian movement. VU will explore methods for estimating dynamic models of labour markets in Germany and urban navigation in Amsterdam, UCL will develop models of movement and location from phone and ticketing data in London, while NUIM will explore movement in small scale environments represented at the building and streetscape scale in Dublin. The network will be supported by three major workshops, exchanges of researchers between sites, and strong external links to other groups, in anticipation that from this pilot project, a proposal for a much wider network will emerge.

Impulsfinanciering voor het opzetten van een Digitaal Competentie Centrum binnen de KNAW, ter verbreding en verdieping van de huidige kennis en expertise binnen de instituten

Employability is at the heart of scientific and public debates concerning the labour market. In these debates, employability is regarded as an important means for workers, employers and governments to deal with the challenges they face due to processes like population ageing and knowledge intensification. In the research project SUSTAINING EMPLOYABILITY, we distinguish three levels of employability. The first level concerns the ?actual? employability of workers; their ability of workers to assert influence over their labour market situation. Secondly, there are employability-enhancing practices through which workers can gain employability. And, thirdly, employers and governments apply formal employability policies, like employment protection and career opportunities. The project SUSTAINING EMPLOYABILITY challenges the implicit assumption that the three levels of employability simply follow each other, by focusing on the following three research objectives: (1) explaining employability practices by acknowledging that interests between the three actors may diverge and that trust problems can arise; (2) examining the effectiveness of employability practices; and (3) understanding how the national context affects the three levels of employability. The three objectives provide the basis of the three subprojects of SUSTAINING EMPLOYABILITY (two PhD projects and one postdoc project). The external partners play a central role. As the consortium consists of representatives of workers, employers and the government, there is a unique opportunity to explore and discuss various viewpoints concerning employability. Furthermore, since several partners are involved in research themselves, joint research is conducted. Finally, knowledge is disseminated through the networks of the partners.

Scientific, technical and medical knowledge is built on research data. It increasingly plays a similar role in the social sciences and humanities. Research datasets are either deposited by researchers or automatically extracted from publications. We propose to create open source search and recommendation solutions for research datasets so as to enable their re-use. The main benefit is that datasets can be more easily found. This way, data re-use is stimulated and redundancy in data collection is avoided. Situated at the interface between the philosophy of science and computer science, the development of innovative algorithmic solutions will be informed by combining three perspectives. First, we will examine the use of datasets in publications, in different disciplines, and for different research tasks, to understand to which extent scientific discovery is based on data-availability and how it is affected by data-sharing cultures. Second, we will contribute semantic technologies to support dataset search, to match research data with user groups, and to generate research dataset search engine result pages. Third, we will develop information retrieval algorithms for unsupervised dataset search and predicting user interactions with dataset search engine results. We will combine these into a self-learning method for searching datasets. Our solutions will be implemented in Elseviers retrieval and recommendation environments. The project will engage the data science community through co-design workshops at critical stages in the research planning, through regular participation in data science and search engine meetups, and by releasing its algorithmic solutions as open source.