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The Network for the Detection of Atmospheric Composition Change (NDACC), a major contributor to the worldwide atmospheric research effort, consists of a set of globally distributed research stations providing consistent, standardized, long-term measurements of atmospheric trace gases, particles, spectral UV radiation reaching the Earth's surface, and physical parameters, centered around the following priorities.
This is a compilation of approximately 923,000 allowed, intercombination and forbidden atomic transitions with wavelengths in the range from 0.5 Å to 1000 µm. It's primary intention is to allow the identification of observed atomic absorption or emission features. The wavelengths in this list are all calculated from the difference between the energy of the upper and lower level of the transition. No attempt has been made to include observed wavelengths. Most of the atomic energy level data have been taken from the Atomic Spectra Database provided by the National Institute of Standards and Technology (NIST).
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The Flanders Marine Institute (VLIZ) is a centre for marine and coastal research. As a partner in various projects and networks it promotes and supports the international image of Flemish marine scientific research and international marine education. In its capacity as a coordination and information platform, the Flanders Marine Institute (VLIZ) supports some thousand marine scientists in Flanders by disseminating their knowledge to policymakers, educators, the general public and scientists.
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.
The Satellite Application Facility on Climate Monitoring (CM SAF) develops, produces, archives and disseminates satellite-data-based products in support to climate monitoring. The product suite mainly covers parameters related to the energy & water cycle and addresses many of the Essential Climate Variables as defined by GCOS (GCOS 138). The CM SAF produces both Enviromental Data Records and Climate Data Records.
This is the KONECT project, a project in the area of network science with the goal to collect network datasets, analyse them, and make available all analyses online. KONECT stands for Koblenz Network Collection, as the project has roots at the University of Koblenz–Landau in Germany. All source code is made available as Free Software, and includes a network analysis toolbox for GNU Octave, a network extraction library, as well as code to generate these web pages, including all statistics and plots. KONECT contains over a hundred network datasets of various types, including directed, undirected, bipartite, weighted, unweighted, signed and rating networks. The networks of KONECT are collected from many diverse areas such as social networks, hyperlink networks, authorship networks, physical networks, interaction networks and communication networks. The KONECT project has developed network analysis tools which are used to compute network statistics, to draw plots and to implement various link prediction algorithms. The result of these analyses are presented on these pages. Whenever we are allowed to do so, we provide a download of the networks.