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Found 78 result(s)

SilkPathDB

Silkworm Pathogen Database

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Silkworm Pathogen Database (SilkPathDB) is a comprehensive resource for studying on pathogens of silkworm, including microsporidia, fungi, bacteria and virus. SilkPathDB provides access to not only genomic data including functional annotation of genes and gene products, but also extensive biological information for gene expression data and corresponding researches. SilkPathDB will be help with researches on pathogens of silkworm as well as other Lepidoptera insects.

Health Atlas

Leipzig Health Atlas

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The Health Atlas is an alliance of medical ontologists, medical systems biologists and clinical trials groups to design and implement a multi-functional and quality-assured atlas. It provides models, data and metadata on specific use cases from medical research projects from the partner institutions.

Port Moody's Open Data Portal

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Port Moody's Open Data Portal gives access to data, statistics, and information about your city government. By making data accessible, we aim to promote public collaboration, increase government transparency, and spark innovation. This information will be used to inform local decision-making and will help us better plan for the future. Our data portal contains a lot of information. You can search through past and current permit, licence, and business applications. Review demographic information about program registration, find information about the location of businesses within Port Moody and filter the business directory by the type of business or service.

GRO.data

Göttingen Research Online

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GRO.data is a research data repository for the Göttingen Campus. Belonging researchers can use it for free. It serves different purposes such as: to simply preserve datasets, to keep track of changes across several versions, to share data with colleagues, to make data itself publicly available, to receive a persistent identifier upon publications.

Stanford Network Analysis Project

SNAP

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Stanford Network Analysis Platform (SNAP) is a general purpose network analysis and graph mining library. It is written in C++ and easily scales to massive networks with hundreds of millions of nodes, and billions of edges. It efficiently manipulates large graphs, calculates structural properties, generates regular and random graphs, and supports attributes on nodes and edges. SNAP is also available through the NodeXL which is a graphical front-end that integrates network analysis into Microsoft Office and Excel. The SNAP library is being actively developed since 2004 and is organically growing as a result of our research pursuits in analysis of large social and information networks. Largest network we analyzed so far using the library was the Microsoft Instant Messenger network from 2006 with 240 million nodes and 1.3 billion edges. The datasets available on the website were mostly collected (scraped) for the purposes of our research. The website was launched in July 2009.

nanoHUB

nanoHUB.org

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nanoHUB.org is the premier place for computational nanotechnology research, education, and collaboration. Our site hosts a rapidly growing collection of Simulation Programs for nanoscale phenomena that run in the cloud and are accessible through a web browser. In addition to simulation devices, nanoHUB provides Online Presentations, Courses, Learning Modules, Podcasts, Animations, Teaching Materials, and more. These resources help users learn about our simulation programs and about nanotechnology in general. Our site offers researchers a venue to explore, collaborate, and publish content, as well. Much of these collaborative efforts occur via Workspaces and User groups.

Spiral

Spiral digital repository

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The Spiral Digital Repository is the Imperial College London institutional open access repository. This system allows you, as an author, to make your research documents open access without incurring additional publication costs. When you self-archive a research document in Spiral it becomes free for anyone to read. You can upload copies of your publications to Spiral using Symplectic Elements. All deposited content becomes searchable online.

Barbara A. Mikulski Archive for Space Telescopes

MAST

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The Mikulski Archive for Space Telescopes (MAST) is a NASA funded project to support and provide to the astronomical community a variety of astronomical data archives, with the primary focus on scientifically related data sets in the optical, ultraviolet, and near-infrared parts of the spectrum. MAST is located at the Space Telescope Science Institute (STScI).

Canadian Astronomy Data Centre

Centre canadien de données astronomiques

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The Canadian Astronomy Data Centre (CADC) was established in 1986 by the National Research Council of Canada (NRC), through a grant provided by the Canadian Space Agency (CSA). Over the past 30 years the CADC has evolved from an archiving centre---hosting data from Hubble Space Telescope, Canada-France-Hawaii Telescope, the Gemini observatories, and the James Clerk Maxwell Telescope---into a Science Platform for data-intensive astronomy. The CADC, in partnership with Shared Services Canada, Compute Canada, CANARIE and the university community (funded through the Canadian Foundation for Innovation), offers cloud computing, user-managed storage, group management, and data publication services, in addition to its ongoing mission to provide permanent storage for major data collections. Located at NRC Herzberg Astronomy and Astrophysics Research Centre in Victoria, BC, the CADC staff consists of professional astronomers, software developers, and operations staff who work with the community to develop and deliver leading-edge services to advance Canadian research. The CADC plays a leading role in international efforts to improve the scientific/technical landscape that supports data intensive science. This includes leadership roles in the International Virtual Observatory Alliance and participation in organizations like the Research Data Alliance, CODATA, and the World Data Systems. CADC also contributes significantly to future Canadian projects like the Square Kilometre Array and TMT. In 2019, the Canadian Astronomy Data Centre (CADC) delivered over 2 Petabytes of data (over 200 million individual files) to thousands of astronomers in Canada and in over 80 other countries. The cloud processing system completed over 6 million jobs (over 1100 core years) in 2019.

Monash Bridges

monash.figshare (formerly)

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Bridges is Monash University's repository for research data, collections, and research activity outputs. It is also the home of the University's online archive of PhD and Masters by Research theses.

Repository CLARIN-D Centre CEDIFOR

Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences

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The CLARIN-D Centre CEDIFOR provides a repository for long-term storage of resources and meta-data. Resources hosted in the repository stem from research of members as well as associated research projects of CEDIFOR. This includes software and web-services as well as corpora of text, lexicons, images and other data.

WBG Open Finances

World Bank Group Finances Open Finances

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WBG Finances is a World Bank Group digital platform that provides our clients and partners access to public financial data and portfolio information from across all Group entities in one place. WBG Finances simplifies the presentation of financial information in an ‘easy to consume’ and in the context of Country and Portfolio across WBG. Open Finances makes World Bank Group’s financials available for everybody to explore. All the data presented is available to everybody to analyze, visualize, and share with others. We invite you to explore the numerous tools, build your own visualizations or download the data in multiple formats. If you are a developer, connect to it through the APIs associated with all the datasets.

Données Québec

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An open data sharing platform resulting from collaboration between cities and the Government of Quebec.

MathRepo

Mathematical Research-Data Repository

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MathRepo is a repository of the Max Planck Institute for Mathematics in the Sciences in Leipzig, dedicated to mathematical research data. Research data are all digital objects that arise during the process of doing research or are a result thereof. In particular, the purpose of this repository is to collect scripts and code, to explain applications of mathematical software, to showcase additional examples to paper publications, and more generally to host supplementary material developed for research projects or discussed in workshops.

PSLC DataShop

Pittsburgh Science of Learning Center DataShop

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PSLC DataShop houses datasets in the areas of learning science and educational software. The site also provides online tools for analyzing and reporting the data.

EUR Data Repository

Erasmus University Rotterdam Data Repository

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The EUR Data Repository [EDR] is the institutional data repository from the Erasmus University Rotterdam. The EUR Data Repository is an online platform where you showcase your research and make it findable, citable, and reusable for others.

Deposita Dados

Repositório Comum de Dados de Pesquisa

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The Common Research Data Repository (Deposita Dados) is a database for archiving, publishing, disseminating, preserving and sharing digital research data and its mission is to promote, support and facilitate the adoption of open access to the datasets of Brazilian researchers linked to scientific institutions that do not yet have their own research data repositories and/or of Brazilian researchers who have executed their datasets through scientific collaboration in foreign teaching and research institutions.

Kaggle

Your home for data science

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Kaggle is a platform for predictive modelling and analytics competitions in which statisticians and data miners compete to produce the best models for predicting and describing the datasets uploaded by companies and users. This crowdsourcing approach relies on the fact that there are countless strategies that can be applied to any predictive modelling task and it is impossible to know beforehand which technique or analyst will be most effective.

GAVO Data Centre

German Astrophysical Virtual Observatory Data Centre

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The GAVO data centre at Zentrum für Astronomie Heidelberg publishes astronomical data of all kinds – e.g., catalogues, images, spectra, time series, simulation results – in accordance with Virtual Observatory standards, making them findable and immediately usable through popular clients like TOPCAT, Aladin, or programatically through the astropy-affiliated package pyVO or the Java library STIL. We pay particular attention to providing thorough metadata to the VO Registry in order to facilitate discovery and reuse. While we have a clear focus on data produced with German contributions, we will usually publish data of other provenance, too. See https://docs.g-vo.org/DaCHS/data_checklist.html for an overview of what resource-level metadata we ask for; contact us for further information on how to publish through the German Astronomical Virtual Observatory.

CSISA Data Repository

Cereal Systems Initiative for South Asia (CSISA) Research Data

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In keeping with the open data policies of the U.S. Agency for International Development (USAID) and Bill & Melinda Gates Foundation, the Cereal Systems Initiative for South Asia (CSISA) has launched the CSISA Data Repository to ensure public accessibility to key data sets, including crop cut data- directly observed, crop yield estimates, on-station and on-farm research trial data and socioeconomic surveys. CSISA is a science-driven and impact-oriented regional initiative for increasing the productivity of cereal-based cropping systems in Bangladesh, India and Nepal, thus improving food security and farmers’ livelihoods. CSISA generates data that is of value and interest to a diverse audience of researchers, policymakers and the public. CSISA’s data repository is hosted on Dataverse, an open source web application developed at Harvard University to share, preserve, cite, explore and analyze research data. CSISA’s repository contains rich datasets, including on-station trial data from 2009–17 about crop and resource management practices for sustainable future cereal-based cropping systems. Collection of this data occurred during the long-term, on-station research trials conducted at the Indian Council of Agricultural Research – Research Complex for the Eastern Region in Bihar, India. The data include information on agronomic management for the sustainable intensification of cropping systems, mechanization, diversification, futuristic approaches to sustainable intensification, long-term effects of conservation agriculture practices on soil health and the pest spectrum. Additional trial data in the repository includes nutrient omission plot technique trials from Bihar, eastern Uttar Pradesh and Odisha, India, covering 2012–15, which help determine the indigenous nutrient supplying ability of the soil. This data helps develop precision nutrient management approaches that would be most effective in different types of soils. CSISA’s most popular dataset thus far includes crop cut data on maize in Odisha, India and rice in Nepal. Crop cut datasets provide ground-truthed yield estimates, as well as valuable information on relevant agronomic and socioeconomic practices affecting production practices and yield. A variety of research data on wheat systems are also available from Bangladesh and India. Additional crop cut data will also be coming online soon. Cropping system-related data and socioeconomic data are in the repository, some of which are cross-listed with a Dataverse run by the International Food Policy Research Institute. The socioeconomic datasets contain baseline information that is crucial for technology targeting, as well as to assess the adoption and performance of CSISA-supported technologies under smallholder farmers’ constrained conditions, representing the ultimate litmus test of their potential for change at scale. Other highly interesting datasets include farm composition and productive trajectory information, based on a 20-year panel dataset, and numerous wheat crop cut and maize nutrient omission trial data from across Bangladesh.

City of Greater Sudbury Open Data Portal

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This portal provides access to available open data from the City of Greater Sudbury.

IEEE DataPort

DataPort

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IEEE DataPort™ is a universally accessible online data repository created, owned, and supported by IEEE, the world’s largest technical professional organization. It enables all researchers and data owners to upload their dataset without cost. IEEE DataPort makes data available in three ways: standard datasets, open access datasets, and data competition datasets. By default, all "standard" datasets that are uploaded are accessible to paid IEEE DataPort subscribers. Data owners have an option to pay a fee to make their dataset “open access”, so it is available to all IEEE DataPort users (no subscription required). The third option is to host a "data competition" and make a dataset accessible for free for a specific duration with instructions for the data competition and how to participate. IEEE DataPort provides workflows for uploading data, searching, and accessing data, and initiating or participating in data competitions. All datasets are stored on Amazon AWS S3, and each dataset uploaded by an individual can be up to 2TB in size. Institutional subscriptions are available to the platform to make it easy for all members of a given institution to utilize the platform and upload datasets.

Academic Torrents

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Academic Torrents is a distributed data repository. The academic torrents network is built for researchers, by researchers. Its distributed peer-to-peer library system automatically replicates your datasets on many servers, so you don't have to worry about managing your own servers or file availability. Everyone who has data becomes a mirror for those data so the system is fault-tolerant.

DataHub Figshare

University of Hong Kong Data Repository

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Provided by the University Libraries, DataHub is the comprehensive institutional repository for research data and scholarly outputs produced by the researchers and students in the University of Hong Kong and their collaborators.

OpenWorm

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OpenWorm aims to build the first comprehensive computational model of the Caenorhabditis elegans (C. elegans), a microscopic roundworm. With only a thousand cells, it solves basic problems such as feeding, mate-finding and predator avoidance. Despite being extremely well studied in biology, this organism still eludes a deep, principled understanding of its biology. We are using a bottom-up approach, aimed at observing the worm behaviour emerge from a simulation of data derived from scientific experiments carried out over the past decade. To do so we are incorporating the data available in the scientific community into software models. We are engineering Geppetto and Sibernetic, open-source simulation platforms, to be able to run these different models in concert. We are also forging new collaborations with universities and research institutes to collect data that fill in the gaps All the code we produce in the OpenWorm project is Open Source and available on GitHub.