How do you keep GIS data secure when sharing with others?

I think sharing via API would be the best way to protect data privacy. While defining the API, we can protect specific groups, users or communities. One of the best examples of such a data sharing portal is GeoNode. Otherwise, password-protected zip files would be good.

Selecting the right GIS data format depends on data complexity. Shapefiles suit complex vector data with intricate geometries, while GeoTIFF works for complex raster data like satellite imagery. GeoJSON is ideal for simple vector data, and geodatabases are versatile, handling both vector and raster. Compression is vital for reducing file sizes while maintaining quality; GeoTIFF and geodatabases excel in this, while shapefiles lack compression. Tailor your choice to your use case and data type.

Shapefiles are a good option as the format is platform agnostic. The main issue however is the field character limit, so organisations need to be creative and have succinct 'short' field name descriptions but also provide a data catalogue that includes the full field name and explanation of what said field means (if it isn't already evident from the original field name provided)

GIS data sharing and dissemination is crucial and critical especially when it comes to web or online platforms. Some Open Geospatial Consortium (OGC) data exchange formats such as WMS, WCS and WFS exist to ensure enteroperability between different data formats such as KML, shapefile etc. OGC often sets standards for geospatial data sharing and dissemination. If the data is shared via the web, it needs to be safeguarded against illegal access, use or manipulation. For big organization generating or consuming GIS data, the data sharing policies need to be in place and should be reviewed periodically.

I think when you are talking about data formats in reference to data security, you have to focus on making sure the data is usable when it reaches who you are sharing with. This ties in with the level of security. Open standards should rule, as everyone can use them. For public data shared on the web, use OGC WFS and WMS. For non spatial, tabular data, send CSV. Easily read by any software. Easy to send field definition file to specify field types. Spatial data to send interagency or interpersonal, use OGC GeoPackage. Open standard, Spatial SQL database contained in single file. Supported by all major GIS packages. Shapefiles had their day, but the format is old, and has major data limitations. In general, open standards for the win.

The most effective ways are user rights and password protection but it's still important to have your maps or cartography work reference as well as acknowledge the source of data etc

In modern Cloud based data sharing and publishing methods. It is recommended practice to create separate data buckets for each customer, secure database segregation where exchange is not necessary.

Data format, size, and weight must be considered when sharing. Also, we need to understand that we are in the era of modern technology with data type or file extension no longer matter. The best approach which is lighter and can easily be fed into several systems, technology, and apps for developers as well as users is JSON or GEOJSON which can be feed by anyone who needs it via APIs.

Encrypting and password-protecting your GIS data ensures that only authorized users can access it. Use encryption tools to secure the data file, and set strong, unique passwords to prevent unauthorized access. Regularly update passwords and encryption methods to maintain robust security.

hare GIS data through a secure platform like a cloud service with end-to-end encryption, using HTTPS for data transfer. Ensure all software is updated to protect against potential security threats.

Shapefiles are more efficient when it comes t data sharing in simple format that can be easily accessed y many, however its important also o create password to protect the data from unauthorized users. It is also important to think on how secure is the data sharing platform before making a decision on which data sharing platform is to be used.

One another way to share geospatial data is through APIs. The users can only request data there are authorized to and also , it helps keeping a track of all their activity.

Certainly. In data sharing, security is paramount. I lean towards secure platforms like GeoServer or robust cloud-based systems. They provide comprehensive options, allowing specific user permissions and varied access rules. While Dropbox and Google Drive offer convenience, they lack stringent security. Even with encryption, vulnerabilities exist; if one's password is compromised, encrypted files can be accessed. In summary, for optimal security in data sharing, cloud-based systems or tools like GeoServer and ArcGIS Cloud are preferred.

When sharing GIS (Geographic Information Systems) data with others, it is critical to secure it in order to preserve sensitive information, maintain data integrity, and ensure compliance with privacy and security standards. Here are some best practices for sharing GIS data with others while keeping it secure: 1. Access Control 2. Authentication and Authorization 3. Encryption 4. Data Masking and Redaction 5. Secure File Formats 6. Data Retention Policies By applying these security practices and remaining educated about evolving security concerns, you may help safeguard GIS data when sharing it with others while also maintaining the confidentiality, integrity, and availability of your geographical data.

Once dealing with sensitive data I recommend to Implement Privileged Access Management (PAM) for your GIS system. It’s the cybersecurity strategies and technologies for exerting control over the elevated (“privileged”) access and permissions for users, accounts, processes, and systems across an IT environment.

Creating and maintaining Metadata is one aspect of geospatial workflow that we often frown upon and overlook but is a necessary step for any organization's data management processes. Although it may take time to write metadata, it will ultimately save time in the future when revisiting your work. Furthermore, it will also allow other people to understand your data more clearly and reduce unnecessary meetings and back-and-forth conversations between members of your organization just to identify what, when, and how the spatial data was made.

Highlight what the data was originally created and intended for, so that end-users can evaluate whether it is fit-for-use and its potential limitations. While it is important to maintain a comprehensive metadata, it is equally important to remind end-users to read it!

The above are true but very generic. For spatial data, an important consideration is the choice of scale and spatial aggregation. Careful deliberation is require on the spatially granularity of the data and how it relates to the categorical granularity. It is also important to understand the spatial boundaries used and actual real world context it contains.

Simple. Forward looking, but eventually graph databases will become the primary structures because it is the only way to map User Access Control typologies across federated systems onto hierarchical data structures like octrees and vector objects.

- Privacy and Security: Protect sensitive data. - Legal Compliance: Verify data usage rights. - Collaboration: Set data sharing rules. - Cultural Sensitivity: Respect local cultures. - Accessibility: Ensure inclusive access. - Scalability: Plan for future growth. - Ethical Awareness: Address potential biases.

For sensitive or secret data consider on-prem (offline) data deployments. 2FA and MFA is a must for security and compliance.