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Found 16 result(s)
The Infrared Space Observatory (ISO) is designed to provide detailed infrared properties of selected Galactic and extragalactic sources. The sensitivity of the telescopic system is about one thousand times superior to that of the Infrared Astronomical Satellite (IRAS), since the ISO telescope enables integration of infrared flux from a source for several hours. Density waves in the interstellar medium, its role in star formation, the giant planets, asteroids, and comets of the solar system are among the objects of investigation. ISO was operated as an observatory with the majority of its observing time being distributed to the general astronomical community. One of the consequences of this is that the data set is not homogeneous, as would be expected from a survey. The observational data underwent sophisticated data processing, including validation and accuracy analysis. In total, the ISO Data Archive contains about 30,000 standard observations, 120,000 parallel, serendipity and calibration observations and 17,000 engineering measurements. In addition to the observational data products, the archive also contains satellite data, documentation, data of historic aspects and externally derived products, for a total of more than 400 GBytes stored on magnetic disks. The ISO Data Archive is constantly being improved both in contents and functionality throughout the Active Archive Phase, ending in December 2006.
The Longitudinal Aging Study Amsterdam (LASA) at the VU University and VU University Medical Centre is initiated by the Ministry of Health, Welfare and Sports in 1991 to determine predictors and consequences of ageing. LASA focuses on, physical, emotional, cognitive and social functioning in late life, the connections between these aspects, and the changes that occur in the course of time
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Since the first discovery of RNA pseudoknots more and many more pseudoknots have been found. However, not all of those pseudoknot data are easy to trace. Sometimes the information is hidden in a publication where the title gives no hint that pseudoknot information is there. This was the first reason that we thought that a general accessible information source for pseudoknots would be handy.
SACA&D is developed as part of the Digitisasi Data Historis (Didah) project. This project is focusing on the digitization and use of high-resolution historical climate data from Indonesia and other Southeast Asian countries
TRAILS is a prospective cohort study, which started in 2001 with population cohort and 2004 with a clinical cohort (CC). Since then, a group of 2500 young people from the Northern part of the Netherlands has been closely monitored in order to chart and explain their mental, physical, and social development. These TRAILS participants have been measured every two to three years, by means of questionnaires, interviews, and all kinds of tests. By now, we have collected information that spans the total period from preadolescence up until young adulthood. One of the main goals of TRAILS is to contribute to the knowledge of the development of emotional and behavioral problems and the (social) functioning of preadolescents into adulthood, their determinants, and underlying mechanisms.
***<<<!!!>>> *** Stated 2017-08-28: To accommodate a wider scope of ophthalmic data, we launched our new Rotterdam Ophthalmic Data Repository. Please visit http://www.rodrep.com/ for all data sets. *** The ORGIDS site will no longer be updated! ***<<<!!!>>>***Through this portal, we will make data sets available that result from our glaucoma research. This includes visual fields, various imaging modalities and other data from both glaucomatous and normal subjects.The data was acquired during more than a decade.
KDP has replaced the KNMI Data Centre (KDC), which was turned off on the 27th of July 2020. Not only a change of name, but also a transition to new technologies. Initially, the KDP will be more primitive than KDC. To fulfill future ambitions, a digital KNMI transformation has been initiated. Part of this transition is the development of a new KDP as a successor of the KDC. All data on the KNMI Data Platform is free to use. For some datasets a service agreement is available, which is indicated on the page of the dataset. The KNMI Data platform provides access to KNMI data on weather, climate and seismology. Here you will find KNMI data on various subjects such as the most recent 10-minute observations, historical series, data about meteorological measuring stations, model calculations, earthquake data and satellite products. In addition to KNMI datasets, we also make datasets from other parties available, such as ECMWF, ECOMET, EUMETSAT and WMO.
SeaDataNet is a standardized system for managing the large and diverse data sets collected by the oceanographic fleets and the automatic observation systems. The SeaDataNet infrastructure network and enhance the currently existing infrastructures, which are the national oceanographic data centres of 35 countries, active in data collection. The networking of these professional data centres, in a unique virtual data management system provide integrated data sets of standardized quality on-line. As a research infrastructure, SeaDataNet contributes to build research excellence in Europe.
The Emissions Database for Global Atmospheric Research (EDGAR) provides independent estimates of the global anthropogenic emissions and emission trends, based on publicly available statistics, for the atmospheric modeling community as well as for policy makers. This scientific independent emission inventory is characterized by a coherent world historical trend from 1970 to year x-3, including emissions of all greenhouse gases, air pollutants and aerosols. Data are presented for all countries, with emissions provided per main source category, and spatially allocated on a 0.1x0.1 grid over the globe.
Presented is information on changes in weather and climate extremes, as well as the daily dataset needed to monitor and analyse these extremes. map of participating countries. Today, ECA&D is receiving data from 59 participants for 62 countries and the ECA dataset contains 33265 series of observations for 12 elements at 7512 meteorological stations throughout Europe and the Mediterranean (see Daily data > Data dictionary). 51% of these series is public, which means downloadable from this website for non-commercial research. Participation to ECA&D is open to anyone maintaining daily station data
Maddison's work contains the Project Dataset with estimates of GDP per capita for all countries in the world between 1820 and 2010 in a format amenable to analysis in R. The database was last updated in January 2013. The update incorporates much of the latest research in the field, and presents new estimates of economic growth in the world economic between AD 1 and 2010 The Maddison Project database presented builts on Angus Maddison's original dataset. The original estimates are kept intact, and only revised or adjusted when there is more and better information available. Angus Maddison's unaltered final dataset remains available on the Original Maddison Homepage https://www.rug.nl/ggdc/historicaldevelopment/maddison/original-maddison
The Rotterdam Ophthalmic Data Repository (ROD-Rep) contains data sets related to ophthalmology that the Rotterdam Ophthalmic Institute has made freely available for researchers worldwide. This portal is an initiative of the Rotterdam Ophthalmic Institute, which is the research institute of the Rotterdam Eye Hospital. It provides the datasets from ophthalmic research (includes measurements such as visual fields and various imaging modalities, grades, etc.) for sharing and re-use to accelerate multi-disciplinary research, resulting in better ophthalmic care. The portal is the successor of the ORGIDS (or Open Rotterdam Glaucoma Imaging Data Sets site); which was an initiative of Koen Vermeer, Hans Lemij and Netty Dorrestijn and initial financial support was provided by Stichting Glaucoomfonds (The Netherlands).
OpenML is an open ecosystem for machine learning. By organizing all resources and results online, research becomes more efficient, useful and fun. OpenML is a platform to share detailed experimental results with the community at large and organize them for future reuse. Moreover, it will be directly integrated in today’s most popular data mining tools (for now: R, KNIME, RapidMiner and WEKA). Such an easy and free exchange of experiments has tremendous potential to speed up machine learning research, to engender larger, more detailed studies and to offer accurate advice to practitioners. Finally, it will also be a valuable resource for education in machine learning and data mining.