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National Academic Research and Collaborations Information System (NARCIS) is the main Dutch national portal for those looking for information about researchers and their work. NARCIS aggregates data from around 30 institutional repositories. Besides researchers, NARCIS is also used by students, journalists and people working in educational and government institutions as well as the business sector.
NARCIS provides access to scientific information, including (open access) publications from the repositories of all the Dutch universities, KNAW, NWO and a number of research institutes, datasets from some data archives as well as descriptions of research projects, researchers and research institutes.
This means that NARCIS cannot be used as an entry point to access complete overviews of publications of researchers (yet). However, there are more institutions that make all their scientific publications accessible via NARCIS. By doing so, it will become possible to create much more complete publication lists of researchers.
In 2004, the development of NARCIS started as a cooperation project of KNAW Research Information, NWO, VSNU and METIS, as part of the development of services within the DARE programme of SURFfoundation. This project resulted in the NARCIS portal, in which the DAREnet service was incorporated in January 2007. NARCIS has been part of DANS since 2011.
DANS - Data Archiving and Networked Services - is the Netherlands Institute for permanent access to digital research resources. DANS encourages researchers to make their digital research data and related outputs Findable, Accessible, Interoperable and Reusable.
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Displaying 331 - 335 of 1863Duurzaam bodembeheer maïs : projectresultaten uit 2013
Hoe kunnen veetelers met minder input meer resultaten halen bij snijmaïsteelt? Wageningen UR en het Louis Bolk Instituut onderzoeken van 2012 tot 2014 in opdracht van het ministerie van EZ duurzame en praktisch haalbare verbeteringen en vernieuwingen. Teeltsystemen die zorgen voor een gezonde bodem worden daarbij gezien als sleutel tot duurzame teelt. Op drie locaties worden diverse teeltsystemen vergeleken in meerjarige proeven uitgevoerd op zand- en kleigrond.
Changing Climate, Changing Behavior: Adaptive Economic Behavior and Housing Markets Responses to Flood Risks
Spatial econometrics and analytical spatial economic modeling advanced significantly in the recent years. Yet, methodologically they are designed to tackle marginal changes in the underlying dynamics of spatial urban systems. In the world with climate change, however, abrupt sudden non-marginal changes in economic system are expected. This is especially relevant for urban development in coastal and delta areas where the probabilities of natural hazards such as catastrophic floods and hurricanes increase dramatically with climate change.
A framework to resolve spatio-temporal misalignment in component-based modelling
Process-based spatio-temporal component models simulate real world processes, using encapsulated process representations that operate at individual spatial and temporal discretisations. These component models act as building blocks in the construction of multi-disciplinary, multi-scale integrated models. Coupling these independent component models, however, involves aggregation or disaggregation of the exchanged variables at model runtime, since each of the component models exposes potentially different spatial and temporal discretisations.
Ontwikkeling bodemvruchtbaarheid op Koeien & Kansen-bedrijven : fosfaat en organische stof
Op de melkveebedrijven die deelnemen aan het project ‘Koeien & Kansen’ werd onderzoek uitgevoerd naar de ontwikkeling van bodemvruchtbaarheid. Er was behoefte aan dit onderzoek om in beeld te krijgen of de maatregelen, die worden genomen op de bedrijven om de nutriënten (N en P) op efficiënte wijze te benutten, niet strijdig zijn met het behouden of verhogen van de bodemvruchtbaarheid. Een ander motief voor dit onderzoek is dat een goede bodemvruchtbaarheid van belang is als basis voor een efficiënt gebruik van nutriënten.
Identifying a land use change cellular automaton by Bayesian data assimilation
We present a Bayesian method that simultaneously identifies the model structure and calibrates the parameters of a cellular automaton (CA). The method entails sequential assimilation of observations, using a particle filter. It employs prior knowledge of experts to define which processes might be important in the system, and uses empirical information from observations to identify which ones really are and how these processes should be parameterized.