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SODHA is the federal Belgian data archive for social sciences and the digital humanities. SODHA is a new service of the State Archives of Belgium and acts as the Belgian service provider for the Consortium of European Social Science Data Archives (CESSDA).
WikiPathways was established to facilitate the contribution and maintenance of pathway information by the biology community. WikiPathways is an open, collaborative platform dedicated to the curation of biological pathways. WikiPathways thus presents a new model for pathway databases that enhances and complements ongoing efforts, such as KEGG, Reactome and Pathway Commons. Building on the same MediaWiki software that powers Wikipedia, we added a custom graphical pathway editing tool and integrated databases covering major gene, protein, and small-molecule systems. The familiar web-based format of WikiPathways greatly reduces the barrier to participate in pathway curation. More importantly, the open, public approach of WikiPathways allows for broader participation by the entire community, ranging from students to senior experts in each field. This approach also shifts the bulk of peer review, editorial curation, and maintenance to the community.
The aim of the Freshwater Biodiversity Data Portal is to integrate and provide open and free access to freshwater biodiversity data from all possible sources. To this end, we offer tools and support for scientists interested in documenting/advertising their dataset in the metadatabase, in submitting or publishing their primary biodiversity data (i.e. species occurrence records) or having their dataset linked to the Freshwater Biodiversity Data Portal. This information portal serves as a data discovery tool, and allows scientists and managers to complement, integrate, and analyse distribution data to elucidate patterns in freshwater biodiversity. The Freshwater Biodiversity Data Portal was initiated under the EU FP7 BioFresh project and continued through the Freshwater Information Platform (http://www.freshwaterplatform.eu). To ensure the broad availability of biodiversity data and integration in the global GBIF index, we strongly encourages scientists to submit any primary biodiversity data published in a scientific paper to national nodes of GBIF or to thematic initiatives such as the Freshwater Biodiversity Data Portal.
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.