{"id":170448,"date":"2010-03-12T11:52:48","date_gmt":"2010-03-12T11:52:48","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/project\/scientific-dataset\/"},"modified":"2023-04-19T01:45:46","modified_gmt":"2023-04-19T08:45:46","slug":"scientific-dataset","status":"publish","type":"msr-project","link":"https:\/\/www.microsoft.com\/en-us\/research\/project\/scientific-dataset\/","title":{"rendered":"Scientific DataSet"},"content":{"rendered":"<p class=\"asset-content\"><img loading=\"lazy\" decoding=\"async\" class=\"alignleft\" src=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2016\/02\/scientific-dataset-2.png\" alt=\"SDS logo\" width=\"128\" height=\"115\" \/>Scientific DataSet (SDS) is a managed library for reading, writing and sharing array-oriented scientific data, such as time series, matrices, satellite or medical imagery, and multidimensional numerical grids.<\/p>\n<p>&nbsp;<\/p>\n<h4>It features:<\/h4>\n<ul>\n<li>Rich metadata to create self-descriptive data packages.<\/li>\n<li>Support for several common data formats, such as comma-separated values (CSV), network common data form (NetCDF), and hierarchical data format (HDF5).<\/li>\n<li>The ability to scale up from simple text files to multi-terabyte Windows Azure archives.<\/li>\n<li>Concurrent access to the data from multiple computing agents in multicore and distributed settings.<\/li>\n<li>Consistency checks and transactional updates.<\/li>\n<\/ul>\n<p>A lighter package that treats NetCDF library as an external dependency is at <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" title=\"\" href=\"http:\/\/github.com\/predictionmachines\/sdslite\" target=\"_self\" rel=\"noopener\">http:\/\/github.com\/predictionmachines\/sdslite<\/a>. This package is also available via <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/www.nuget.org\/packages\/\/sdsLite\/\" target=\"_self\" rel=\"noopener\">NuGet<\/a>.<\/p>\n<p>The library was developed in\u00a0collaboration between <a href=\"https:\/\/www.microsoft.com\/en-us\/research\/lab\/microsoft-research-cambridge\/\" target=\"_self\" rel=\"noopener\">MSR Computational Science lab in Cambridge, UK <\/a>and the <a class=\"msr-external-link glyph-append glyph-append-open-in-new-tab glyph-append-xsmall\" href=\"https:\/\/cs.msu.ru\/en\">Computer Science department, Moscow State University<\/a>.<\/p>\n<p>You can read more about the library and how to get started in the <a href=\"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2010\/03\/Introduction-to-Scientific-DataSet-1.3.pdf\">Introduction to Scientific DataSet<\/a>\u00a0document.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Scientific DataSet (SDS) is a managed library for reading, writing and sharing array-oriented scientific data, such as time series, matrices, satellite or medical imagery, and multidimensional numerical grids. &nbsp; It features: Rich metadata to create self-descriptive data packages. Support for several common data formats, such as comma-separated values (CSV), network common data form (NetCDF), and [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"research-area":[13563,198583,13546],"msr-locale":[268875],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-170448","msr-project","type-msr-project","status-publish","hentry","msr-research-area-data-platform-analytics","msr-research-area-ecology-environment","msr-research-area-computational-sciences-mathematics","msr-locale-en_us","msr-archive-status-active"],"msr_project_start":"2010-03-12","related-publications":[],"related-downloads":[234959],"related-videos":[],"related-groups":[],"related-events":[],"related-opportunities":[],"related-posts":[],"related-articles":[],"tab-content":[],"slides":[],"related-researchers":[{"type":"user_nicename","display_name":"Vassily Lyutsarev","user_id":34498,"people_section":"Group 1","alias":"vassilyl"}],"msr_research_lab":[],"msr_impact_theme":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/170448"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-project"}],"version-history":[{"count":6,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/170448\/revisions"}],"predecessor-version":[{"id":935646,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/170448\/revisions\/935646"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=170448"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=170448"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=170448"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=170448"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=170448"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}