Where can you find reliable open spatial data for GIS?

Even if you can access and use open source GIS data but still you're not sure about the accuracy of data. So the most important thing in using the open source spatial data is the reliability of the source itself. Most importantly finding qualitative information is itself costly.

1. Governmental Agencies: NGA, USGS, NASA, and national data portals offer comprehensive datasets. 2. Non-Governmental Sources: Explore OSM, Natural Earth, Diva-GIS, GeoNames, and GADM. 3. Academic Institutions: Access GIS datasets from universities and research repositories. 4. Commercial Providers: Esri's ArcGIS Hub and CartoDB's Data Observatory offer free and premium data. 5. QGIS and ArcGIS provide sample datasets for learning. 6. Find domain-specific data for environment, transportation, and more. 7. UN and World Bank provide global development and economic datasets. 8. Data.gov, Earthdata, and ESA's Earth Online offer a wealth of resources. Remember to review licensing and metadata, ensuring proper attribution and data quality.

Open spatial data transcends data that can be explicitly linked to a location. Rather, open spatial data includes data that have an implicit location. Some examples of data with implicit location include zip/postal codes, addresses, IP addresses, country codes, language and dialect, timezone information, currency etc. With this broader definition of open spatial data, a geographic information systems (GIS) specialist has a larger pool of sources to get data. Finally, datasets of this nature (implicit location) require additional processing before they can be directly linked to a point or area on the Earth's surface. Therefore, a GIS practitioner must ensure that the dataset is worth the extra time, resources, effort and skills.

If you are looking for open spatial data from beyond the USA (eg. Australia) I can recommend data.gov.au which also provides access to metadata for spatial/attribute reliability, etc.

In recent days, we have found numerous reliable open-source raster data, such as USGS, Jaxa, ESRI and one most powerful source, Google Earth Engine. But it might be tricky when it comes to the vector data. Usually, I provide vector geographic data like slope, precipitation, land cover, et cetera, from raster data processing. But others, like administration, road, or spatial structure, I collect them from NGOs and government. But, their data mostly are low quality (topologically chaotic, patchy area, datum miss match). Therefore, there is no 100% reliable source of data, so we should check the data quality before using it for any analysis purposes.

Decisions about usability should primarily be based on data quality and applicability, not on availability status. The quality of the user experience and the final product should come first. If open data can deliver sufficient value, that's great; if not, it should not restrict us to using only that data source.

Using open spatial data for GIS offers several advantages. It promotes collaboration, allows for broader access to information, and fosters community-driven data updates. Open spatial data is often freely available, reducing costs for individuals and organizations. It encourages innovation and the development of diverse applications. Moreover, it contributes to transparency and supports a more democratic approach to data access and usage in various fields, including environmental monitoring, urban planning, and disaster response.

In terms of quality, a reliable open spatial data is typically linked to a scientific article that includes the data development framework, data collection, data spatial-temporal coverage, and statistical validation. It may help the user because the data is assessed by the scientific community.

In my opinion, open spatial data, that is, information that has no obstacles or restrictions to publish, will be the most useful for people, and most importantly, people and their interest in this information can be used to update information. So this information is the main foundation of spatial systems even if we don't have any other information.

When you have limited budget and limited source to work on GIS related application. Best way to make crowd sourcing to validate data and to make prototype of application.

It all depends on what type of spatial data you're looking for. In general, you're going to want to find the "authoritative" dataset, and your best bet is to go directly to the source of the data. Looking for spatial data in a town/city/county? Go directly to their government webpage; that data should be accessible there. You can also find data through the ArcGIS Portal (with an ESRI subscription...), but if the data is not listed as authoritative it shouldn't be trusted. And of course, there are federal agencies that share data such as the USDA, USGS, NAIP, etc. Other notable places to find data that I use: - USGS National Map - Data.gov - HIFLD Open Data - Local DOT GIS webpage - USDA Geospatial Data Gateway

The INSPIRE Geoportal is the central European access point to the data provided by EU Member States and several EFTA countries under the INSPIRE Directive.

There are many data types and sources. A reliable place to start is ESRI ArcGIS Online Living Atlas. Going straight to the source is, in my experience, the most reliable method. For instance, if we’re looking for floodplain data, FEMA is the data source; if it’s wetlands data, US Fish and Wildlife Service provides the National Wetlands Inventory; if it’s parcel data, local County agencies (usually Assessor’s) provide such data. They’re also vendors who can provide data at a cost.

Crowdsourcing open GIS data is a powerful concept. It leverages the collective efforts of a diverse community to gather, update, and maintain geographic information. This approach not only accelerates data collection but also ensures its accuracy and comprehensiveness. By openly sharing this data, we promote transparency and enable a wide range of applications, from urban planning to disaster management. Such initiatives empower individuals and organizations to make informed decisions and contribute to the betterment of our communities and the environment.

Many state and provincial government agencies collect geospatial data at various intervals. These sources are often considered "autoritative" meaning that a high degree of due dilligance has been performed to verify the integrity, accuracy and source of the data. You should start by looking on the website of the respective agency for the area of interest. The data can often be downloaded directly and is provided with metadata which contains any disclamers, licences and quality reports which will help you understand how applicable the data is to your needs.

The difficulty is not just validating that the data is from an authoritative source, it’s ensuring that the end user understands the limitations on legitimacy. Once data is in the hands of the end user they will often accept it as authoritative without taking into consideration any caveats provided.

- Overlay digital data on the source map, not just against other digital sets. - Ensure metadata is available, detailing data sources and authoritative agencies. - Confirm there's a detailed modification date history for each polygon, clarifying when and which aspects were altered. - Obtain white papers outlining digitization methods. - Check attributes for consistency, ensuring capabilities like dissolving based on specific criteria.

Very good points and thanks for your response, off course the accuracy of data is the key, however, how to evaluate the accuracy, Unless using them and see how close are the results to our expectations of reality on the ground.

Confirm that the data is available in a format compatible with your GIS software and tools. Common formats include shapefiles, KML, and raster formats like GeoTIFF.

Another question to ask should be where do the data providers get their data from. Some sources do get the data from areas or authorities where data wasn't verified.

CloudCompare is a powerful, open source and free to use software that allows you to open, modify and export many types of geospatial data including point cloud, vector and mesh data types. It has an active community with many plug-ins available for specific analysis.

Use it as the open source license allows, don’t forget to read T&C. Even open data might have terms of usage that provide specific reuse information.

Google Earth Engine is web based software for geoprocessing workflows, Google Earth Pro is a desktop application, primarily for visualization, although it has a few simple geometry construction tools.

Integrate the open spatial data with your existing GIS datasets, if applicable. Ensure that the data aligns in terms of coordinate systems, attributes, and data structure. Use GIS software tools to perform data joins, merges, or spatial overlays as needed.

Open spatial data may easily be available from different sources. The questions usually asked by practitioners and policy makers is on the legitimacy and accuracy of the data. This can be traced from the institutions/organizations generating the data and may include looking into the tools, methodology, and objectives of the data collection.

I strongly agree with @Arkadiusz comments. Take a long, hard look at the freely available data as to its suitability to the problem you are trying to solve. WIth some exceptions, my experience is that many agencies and organizations neither budget for nor take seriously the extremely important tasks of updating, maintaining, edge matching, and improving their data.

One thing to consider about open spatial data is the initial purpose. What was the purpose for producing this data? The purpose is/will inform about the quality/accuracy/fitness as well as the scale of the data, as indicated under the evaluation section....