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The tree of life links all biodiversity through a shared evolutionary history. This project will produce the first online, comprehensive first-draft tree of all 1.8 million named species, accessible to both the public and scientific communities. Assembly of the tree will incorporate previously-published results, with strong collaborations between computational and empirical biologists to develop, test and improve methods of data synthesis. This initial tree of life will not be static; instead, we will develop tools for scientists to update and revise the tree as new data come in. Early release of the tree and tools will motivate data sharing and facilitate ongoing synthesis of knowledge.
The Keck Observatory Archive (KOA)is a collaboration between the NASA Exoplanet Science Institute (NExScI) and the W. M. Keck Observatory (WMKO). This collaboration is founded by the NASA. KOA has been archiving data from the High Resolution Echelle Spectrograph (HIRES) since August 2004 and data acquired with the Near InfraRed echelle SPECtrograph (NIRSPEC) since May 2010. The archived data extend back to 1994 for HIRES and 1999 for NIRSPEC. The W. M. Keck Observatory Archive (KOA) ingests and curates data from the following instruments: DEIMOS, ESI, HIRES, KI, LRIS, MOSFIRE, NIRC2, and NIRSPEC.
eBird is among the world’s largest biodiversity-related science projects, with more than 1 billion records, more than 100 million bird sightings contributed annually by eBirders around the world, and an average participation growth rate of approximately 20% year over year. A collaborative enterprise with hundreds of partner organizations, thousands of regional experts, and hundreds of thousands of users, eBird is managed by the Cornell Lab of Ornithology. eBird data document bird distribution, abundance, habitat use, and trends through checklist data collected within a simple, scientific framework. Birders enter when, where, and how they went birding, and then fill out a checklist of all the birds seen and heard during the outing. Data can be accessed from the Science tab on the website.
The Earth System Grid Federation (ESGF) is an international collaboration with a current focus on serving the World Climate Research Programme's (WCRP) Coupled Model Intercomparison Project (CMIP) and supporting climate and environmental science in general. Data is searchable and available for download at the Federated ESGF-CoG Nodes https://esgf.llnl.gov/nodes.html
The CDHA assists researchers to create, document, and distribute public use microdata on health and aging for secondary analysis. Major research themes include: midlife development and aging; economics of population aging; inequalities in health and aging; international comparative studies of health and aging; and the investigation of linkages between social-demographic and biomedical research in population aging. The CDHA is one of fourteen demography centers on aging sponsored by the National Institute on Aging.
The KNB Data Repository is an international repository intended to facilitate ecological, environmental and earth science research in the broadest senses. For scientists, the KNB Data Repository is an efficient way to share, discover, access and interpret complex ecological, environmental, earth science, and sociological data and the software used to create and manage those data. Due to rich contextual information provided with data in the KNB, scientists are able to integrate and analyze data with less effort. The data originate from a highly-distributed set of field stations, laboratories, research sites, and individual researchers. The KNB supports rich, detailed metadata to promote data discovery as well as automated and manual integration of data into new projects. The KNB supports a rich set of modern repository services, including the ability to assign Digital Object Identifiers (DOIs) so data sets can be confidently referenced in any publication, the ability to track the versions of datasets as they evolve through time, and metadata to establish the provenance relationships between source and derived data.
The Open Science Framework (OSF) is part network of research materials, part version control system, and part collaboration software. The purpose of the software is to support the scientist's workflow and help increase the alignment between scientific values and scientific practices. Document and archive studies. Move the organization and management of study materials from the desktop into the cloud. Labs can organize, share, and archive study materials among team members. Web-based project management reduces the likelihood of losing study materials due to computer malfunction, changing personnel, or just forgetting where you put the damn thing. Share and find materials. With a click, make study materials public so that other researchers can find, use and cite them. Find materials by other researchers to avoid reinventing something that already exists. Detail individual contribution. Assign citable, contributor credit to any research material - tools, analysis scripts, methods, measures, data. Increase transparency. Make as much of the scientific workflow public as desired - as it is developed or after publication of reports. Find public projects here. Registration. Registering materials can certify what was done in advance of data analysis, or confirm the exact state of the project at important points of the lifecycle such as manuscript submission or at the onset of data collection. Discover public registrations here. Manage scientific workflow. A structured, flexible system can provide efficiency gain to workflow and clarity to project objectives, as pictured.
>>>!!!<<< caArray Retirement Announcement >>>!!!<<< The National Cancer Institute (NCI) Center for Biomedical Informatics and Information Technology (CBIIT) instance of the caArray database was retired on March 31st, 2015. All publicly-accessible caArray data and annotations will be archived and will remain available via FTP download https://wiki.nci.nih.gov/x/UYHeDQ and is also available at GEO http://www.ncbi.nlm.nih.gov/geo/ . >>>!!!<<< While NCI will not be able to provide technical support for the caArray software after the retirement, the source code is available on GitHub https://github.com/NCIP/caarray , and we encourage continued community development. Molecular Analysis of Brain Neoplasia (Rembrandt fine-00037) gene expression data has been loaded into ArrayExpress: http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-3073 >>>!!!<<< caArray is an open-source, web and programmatically accessible microarray data management system that supports the annotation of microarray data using MAGE-TAB and web-based forms. Data and annotations may be kept private to the owner, shared with user-defined collaboration groups, or made public. The NCI instance of caArray hosts many cancer-related public datasets available for download.