The Portal Project Teaching Database is a simplified version of the Portal Project Database designed for teaching. It provides a real world example of life-history, population, and ecological data, with sufficient complexity to teach many aspects of data analysis and management, but with many complexities removed to allow students to focus on the core ideas and skills being taught. The database is currently available in csv, json, and sqlite. This database is not designed for research as it intentionally removes some of the real-world complexities. The original database is published at Ecological Archives(http://esapubs.org/archive/ecol/E090/118/) and this version of the database should be used for research purposes. The Python code used for converting the original database to this teach version is included as 'create_portal_teach_dataset.py'. Suggested changes or additions to this dataset can be requested or contributed in the project GitHub repository(https://github.com/weecology/portal-teachingdb).

This dataset lists suggestions received through the CT Open Data Dataset Suggestion survey here: https://data.ct.gov/stories/s/eivh-c3ze.

The California Health and Human Services Agency (CHHS) has launched its Open Data Portal initiative in order to increase public access to one of the State’s most valuable assets – non-confidential health and human services data. Its goals are to spark innovation, promote research and economic opportunities, engage public participation in government, increase transparency, and inform decision-making. "Open Data" describes data that are freely available, machine-readable, and formatted according to national technical standards to facilitate visibility and reuse of published data.

The Texas Open Data Portal Resource Guide 2025 is produced by the Texas Department of Information Resources to assist publishing organizations in their use of the Open Data Portal. While not exhaustive, this document serves as a guide in establishing an open data governance framework, creating an open data inventory, and publishing open data in an efficient and standardized manner.

DAPSTOM (integrated database and portal for fish stomach records) is an ongoing initiative (supported by Defra and the EU) to digitise and make available fish stomach content records spanning the past 100 years. In this latest iteration (Version 6.3) an additional 26,767 records for 122,137 individual predator stomachs have been added to the dataset (including 31,488 cod stomachs), bringing the total up to 283,121 records from 481,476 stomachs and 741 distinct research cruises/sampling campaigns. Data are available for 210 predator species and a huge swathe of the Northeast Atlantic, but particularly the North Sea, Celtic Sea, Irish Sea and area around Spitzbergen. Records span the period 1836 to 2023, and the database encompasses individuals ranging in size from 0.1 cm (a herring larva) to 768 cm for a basking shark caught in 1947.

The DAPSTOM database (version 1) was originally created in 2007. It has been used to parameterise multispecies fisheries models and to develop ecosystem indicators, with a focus on ‘food-webs’, as well as basic investigations into the underlying biology of particular species. Most datasets were derived from scientists log-books or reports contained within the Cefas archive, others were donated by ‘partners’ or were digitised from published peer-reviewed papers, with specific relevance to the British Isles. This update to DAPSTOM has been funded via the European Union under project “SC10 – Study on stomach content of fish to update databases and analyse possible changes in diet or food webs interactions” (EASME/EMFF/2018/011). The intention is that the DAPSTOM Version 6.3 database will be made searchable and freely available to users via a dedicated R-shiny interface.

The City of Detroit Open Data Style Guide details standards that, when implemented, improve the public understandability and accessibility of the City's open data. The Style Guide is broken up into two sections. The dataset section outlines best practices for data formatting, quality, and accessibility. The metadata section provides guidance on creating rich and informative dataset descriptions, column-level descriptions, and more. Eventually, all items on the Open Data Portal will adhere to the Style Guide.

A. SUMMARY This dataset is used to report on public dataset access and usage within the open data portal. Each row sums the amount of users who access a dataset each day, grouped by access type (API Read, Download, Page View, etc).

B. HOW THE DATASET IS CREATED This dataset is created by joining two internal analytics datasets generated by the SF Open Data Portal. We remove non-public information during the process.

C. UPDATE PROCESS This dataset is scheduled to update every 7 days via ETL.

D. HOW TO USE THIS DATASET This dataset can help you identify stale datasets, highlight the most popular datasets and calculate other metrics around the performance and usage in the open data portal.

Please note a special call-out for two fields: - "derived": This field shows if an asset is an original source (derived = "False") or if it is made from another asset though filtering (derived = "True"). Essentially, if it is derived from another source or not. - "provenance": This field shows if an asset is "official" (created by someone in the city of San Francisco) or "community" (created by a member of the community, not official). All community assets are derived as members of the community cannot add data to the open data portal.

This is a PDF document created by the Department of Information Technology (DoIT) and the Governor's Office of Performance Improvement to assist training Maryland state employees on use of the Open Data Portal, https://opendata.maryland.gov. This document covers direct data entry, uploading Excel spreadsheets, connecting source databases, and transposing data. Please note that this tutorial is intended for use by state employees, as non-state users cannot upload datasets to the Open Data Portal.

The Water Quality Portal (WQP) is a cooperative service sponsored by the United States Geological Survey (USGS), the Environmental Protection Agency (EPA), and the National Water Quality Monitoring Council (NWQMC). It serves data collected by over 400 state, federal, tribal, and local agencies. Water quality data can be downloaded in Excel, CSV, TSV, and KML formats. Fourteen site types are found in the WQP: aggregate groundwater use, aggregate surface water use, atmosphere, estuary, facility, glacier, lake, land, ocean, spring, stream, subsurface, well, and wetland. Water quality characteristic groups include physical conditions, chemical and bacteriological water analyses, chemical analyses of fish tissue, taxon abundance data, toxicity data, habitat assessment scores, and biological index scores, among others. Within these groups, thousands of water quality variables registered in the EPA Substance Registry Service (https://iaspub.epa.gov/sor_internet/registry/substreg/home/overview/home.do) and the Integrated Taxonomic Information System (https://www.itis.gov/) are represented. Across all site types, physical characteristics (e.g., temperature and water level) are the most common water quality result type in the system. The Water Quality Exchange data model (WQX; http://www.exchangenetwork.net/data-exchange/wqx/), initially developed by the Environmental Information Exchange Network, was adapted by EPA to support submission of water quality records to the EPA STORET Data Warehouse [USEPA, 2016], and has subsequently become the standard data model for the WQP. Contributing organizations: ACWI The Advisory Committee on Water Information (ACWI) represents the interests of water information users and professionals in advising the federal government on federal water information programs and their effectiveness in meeting the nation's water information needs. ARS The Agricultural Research Service (ARS) is the U.S. Department of Agriculture's chief in-house scientific research agency, whose job is finding solutions to agricultural problems that affect Americans every day, from field to table. ARS conducts research to develop and transfer solutions to agricultural problems of high national priority and provide information access and dissemination to, among other topics, enhance the natural resource base and the environment. Water quality data from STEWARDS, the primary database for the USDA/ARS Conservation Effects Assessment Project (CEAP) are ingested into WQP via a web service. EPA The Environmental Protection Agency (EPA) gathers and distributes water quality monitoring data collected by states, tribes, watershed groups, other federal agencies, volunteer groups, and universities through the Water Quality Exchange framework in the STORET Warehouse. NWQMC The National Water Quality Monitoring Council (NWQMC) provides a national forum for coordination of comparable and scientifically defensible methods and strategies to improve water quality monitoring, assessment, and reporting. It also promotes partnerships to foster collaboration, advance the science, and improve management within all elements of the water quality monitoring community. USGS The United States Geological Survey (USGS) investigates the occurrence, quantity, quality, distribution, and movement of surface waters and ground waters and disseminates the data to the public, state, and local governments, public and private utilities, and other federal agencies involved with managing the United States' water resources. Resources in this dataset:Resource Title: Website Pointer for Water Quality Portal. File Name: Web Page, url: https://www.waterqualitydata.us/ The Water Quality Portal (WQP) is a cooperative service sponsored by the United States Geological Survey (USGS), the Environmental Protection Agency (EPA), and the National Water Quality Monitoring Council (NWQMC). It serves data collected by over 400 state, federal, tribal, and local agencies. Links to Download Data, User Guide, Contributing Organizations, National coverage by state.

A site analytics story page discussing data freshness on the Maryland Open Data Portal with links to the State's Data Freshness Homepage.

This web page leads to a database of images and information about the 150 major impact craters on Ganymede and is updated semi-regularly based on continuing analysis of Voyager 2 images.

These instructional videos walk users through the portal and its different features.

Database portal containing replicate experiments of different assays and samples

Portal created to help openly explore and share NF datasets, analysis tools, resources, and publications related to neurofibromatosis and schwannomatosis.Public data repository that stores and shares data generated by multiple collaborative research programs focused on neurofibromatosis diseases.

The ImmPort system serves as a long-term, sustainable archive of immunology research data generated by investigators mainly funded through the NIAID/DAIT. The core component of the ImmPort system is an extensive data warehouse containing an integration of experimental data and clinical trial data. The ImmPort system also provides data analysis tools and an immunology-focused ontology. The analytical tools created and integrated as part of the ImmPort system are available to any researcher within ImmPort after registration and approval by DAIT. Additionally, the data provided mainly by NIAID/DAIT funded researchers in ImmPort will be available to all registered users after the appropriate embargo time.

A document on how to access Fisheries New Zealand’s Commercial Fisheries Management Areas spatial data. This document provide a step-by-step guide to aid you with downloading the updated datasets listed above. You will be able to download the datasets in a variety of format.This document can be found by MPI staff here.

1. Website usage instructions2. Website usage case instructions3. Website unit introduction

License agreements with summary table and user guide for PICs Environmental Data Portals

The World Bank's Gender Data Portal makes the latest gender statistics accessible through compelling narratives and data visualizations to improve the understanding of gender data and facilitate analyses that inform policy choices.

They include:

• Population
• SDGs
• Children 0-14
• Youth 15-24
• Assets
• Education
• Employment and Time Use
• Entrepreneurship
• Environment
• Health
• Leadership
• Norms and Decision-making
• Technology
• Violence

The specifications and guidelines in this Data Management Plan will improve data consistency and availability of information. It will ensure that all levels of government and the public have access to the most up-to-date information; reduce or eliminate overlapping data requests and redundant data maintenance; ensure metadata is consistently created; and ensure that data services can be displayed by the consumer with the output of its choice.