Filter
Reset all

Subjects

Content Types

Countries

AID systems

API

Data access

Data access restrictions

Database access

Database access restrictions

Database licenses

Data licenses

Data upload

Data upload restrictions

Enhanced publication

Institution responsibility type

Institution type

Keywords

Metadata standards

PID systems

Provider types

Quality management

Repository languages

Software

Syndications

Repository types

Versioning

  • * at the end of a keyword allows wildcard searches
  • " quotes can be used for searching phrases
  • + represents an AND search (default)
  • | represents an OR search
  • - represents a NOT operation
  • ( and ) implies priority
  • ~N after a word specifies the desired edit distance (fuzziness)
  • ~N after a phrase specifies the desired slop amount
  • 1 (current)
Found 11 result(s)
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.
<<<!!!<<< This repository is no longer available. >>>!!!>>> TeachingWithData.org is a portal where faculty can find resources and ideas to reduce the challenges of bringing real data into post-secondary classes. It allows faculty to introduce and build students' quantitative reasoning abilities with readily available, user-friendly, data-driven teaching materials.
!!! >>> the repository is offline, data can be found here: https://osf.io/gjp53/ <<< !!! Our lab investigates how cognition manifests in, and is influenced by, the social contexts in which it occurs. We focus: 1) on how conversational interactions can reshape memory, by promoting shared remembering and shared forgetting, and 2) on how socio-cognitive processes affect the formation of collective memories and beliefs, and the dynamics of collective decisions. In exploring these issues, while maintaining high ecological validity, our lab integrates a wide range of methodologies, including laboratory experiments, field studies, social network analysis, and agent-based simulations.
The World Values Survey (WVS) is a worldwide network of social scientists studying changing values and their impact on social and political life. The WVS in collaboration with EVS (European Values Study) carried out representative national surveys in more than 100 countries containing almost 90 percent of the world's population. These surveys show pervasive changes in what people want out of life and what they believe. In order to monitor these changes, the EVS/WVS has executed six waves of surveys, from 1981 to 2013.
Cell phones have become an important platform for the understanding of social dynamics and influence, because of their pervasiveness, sensing capabilities, and computational power. Many applications have emerged in recent years in mobile health, mobile banking, location based services, media democracy, and social movements. With these new capabilities, we can potentially be able to identify exact points and times of infection for diseases, determine who most influences us to gain weight or become healthier, know exactly how information flows among employees and productivity emerges in our work spaces, and understand how rumors spread. In an attempt to address these challenges, we release several mobile data sets here in "Reality Commons" that contain the dynamics of several communities of about 100 people each. We invite researchers to propose and submit their own applications of the data to demonstrate the scientific and business values of these data sets, suggest how to meaningfully extend these experiments to larger populations, and develop the math that fits agent-based models or systems dynamics models to larger populations. These data sets were collected with tools developed in the MIT Human Dynamics Lab and are now available as open source projects or at cost.
Quetelet-Progedo-Diffusion allows searching and accessing data from national public statistics (major surveys, censuses, databases) and large surveys from French research. - Major data, censuses and other databases of French National Statistics - Major French research data - Privileged access to international data
Country
sciencedata.dk is a research data store provided by DTU, the Danish Technical University, specifically aimed at researchers and scientists at Danish academic institutions. The service is intended for working with and sharing active research data as well as for safekeeping of large datasets. The data can be accessed and manipulated via a web interface, synchronization clients, file transfer clients or the command line. The service is built on and with open-source software from the ground up: FreeBSD, ZFS, Apache, PHP, ownCloud/Nextcloud. DTU is actively engaged in community efforts on developing research-specific functionality for data stores. Our servers are attached directly to the 10-Gigabit backbone of "Forskningsnettet" (the National Research and Education Network of Denmark) - implying that up and download speed from Danish academic institutions is in principle comparable to those of an external USB hard drive. Data store for research data allowing private sharing and sharing via links / persistent URLs.
<<<!!!<<< The repository is no longer available. >>>!!!>>> Selected TOXMAP data can be accesse from the following sites: U.S. EPA Toxics Release Program (TRI) (https://www.epa.gov/toxics-release-inventory-tri-program) U.S. EPA Superfund Program (https://www.epa.gov/superfund) U.S. EPA Facilities Registry System (FRS) (https://www.epa.gov/frs) U.S. EPA Clean Air Markets Program (https://www.epa.gov/airmarkets) U.S. EPA Geospatial Applications (https://www.epa.gov/geospatial/epa-geospatial-applications) U.S. NIH NCI Surveillance, Epidemiology, and End Results Program (SEER) (https://seer.cancer.gov/) Government of Canada National Pollutant Release Inventory (NPRI) (https://www.canada.ca/en/services/environment/pollution-waste-management/national-pollutant-release-inventory.html) U.S. Census Bureau (https://www.census.gov/) U.S. Nuclear Regulatory Commission (NRC) (https://www.nrc.gov/) >>>!!!>>>
Country
The German Central Health Study Hub is a platform that serves two different kinds of users. First, it allows scientists and data holding organizations (data producers) to publish their project characteristics, documents and data related to their research endeavour in a FAIR manner. Obviously, patient-level data cannot be shared publicly, however, metadata describing the patient-level data along with information about data access can be shared via the platform (preservation description information). The other kind of user is a scientist or researcher (data consumer) that likes to find information about past and ongoing studies and is interested in reusing existing patient-level data for their project. To summarize, the platforms connect data providers with data consumers in the domain of clinical, public health and epidemiologic health research to foster reuse. The platform aggregates and harmonizes information already entered in various public repositories such as DRKS, clinicaltrials.gov, WHO ICTRP to provide a holistic view of the German research landscape in the aforementioned research areas. In addition, data stewards actively collect available information from (public) resources such as websites that cannot be automatically integrated. The service started during the COVID-19 pandemic.