Frequently Asked Questions

Datacash is a 501(c)(3) nonprofit educational organization dedicated to improving public understanding of personal data, digital privacy, and the data economy. Through educational resources, research, workshops, and public-interest tools, Datacash helps individuals understand the information they generate, how it is collected and used, and the choices available to them regarding their data.

People deserve to understand the data systems they participate in. Datacash turns complex topics into accessible public education for students, educators, families, community organizations, researchers, journalists, and people with limited technical knowledge.

Devo Wright founded Datacash. The About page introduces the contributors and their educational roles.

Information can relate to a person directly or through context. Names, account identifiers, location history, activity records, and inferred interests can all be relevant.

Observed data records activity, such as a click, a visit, or a device event. It differs from information someone deliberately enters into a form.

An inference is a conclusion drawn from other information, such as an estimated interest. It can be uncertain or incorrect even when the underlying observations are accurate.

No. Datacash aims to explain unfamiliar concepts in plain language, using examples people can connect to everyday digital life.

Start with one familiar service. Identify the information you provide, the activity it can observe, and the privacy controls it offers.

Educators, libraries, families, and community organizations are among the audiences Datacash aims to serve. Contact us about a learning activity or resource request.

Organizations use information for functions such as recommendations, advertising, research, risk assessment, and service improvement. The purpose and value vary by context.

No universal cash value applies to a person’s information. Revenue averages and market estimates do not establish an individual payment amount.

This nonprofit’s role is education. Its resources and public-interest tools do not promise earnings or operate as a personal-data marketplace.

Private browsing mainly affects some records saved locally by the browser. Websites, signed-in services, and network operators can still have visibility into activity.

Usually these are separate actions. Check the provider’s account closure, deletion, and retention instructions.

Consider what a feature needs and what you want it to do. Explainable, relevant choices are more useful than changes that break essential functions without understanding why.

Claims are matched to suitable evidence, including primary documentation, research, and direct observation when appropriate. Sources, dates, definitions, and limitations matter.

Send the page address, the statement at issue, and a supporting source to support@datacash.app.

Material support should be disclosed, and it must not purchase research findings or editorial conclusions.

The Organization and Funding policy explains the transparency standard. Project-specific material support should be disclosed where relevant.

No. General policies describe standards for possible arrangements; they do not establish a named donor, sponsor, or active program.

Advertising and sponsored material should be distinguishable from independent educational content and follow the site’s disclosure standards.

Questions and source-based discussion about personal data, digital privacy, research, educational tools, and the data economy.

Do not post passwords, identity documents, private messages, account archives, or identifying information about another person.

They can illustrate a question or provide context. Broad claims require evidence suited to their scope, with limitations explained.

Datacash’s public educational resources are intended to be accessible so financial circumstances do not determine access to basic data education.

Contact support@datacash.app with the page, the task, and the barrier. Include relevant assistive technology or browser details if useful.

Fictional examples are usually better for teaching. They reduce the chance of exposing information about participants or other people.

A question aimed at improving public understanding, such as how people interpret consent choices or how data practices are explained.

Not necessarily. Recruitment, sample size, missing groups, and method limit which conclusions can be drawn.

No. Plans for workshops, reports, datasets, or tools should be distinguished from work that has been carried out and published.

After major account or device changes, when you stop using a service, and at a manageable interval for important accounts.

Services that have been authorized to access an account or some of its information. Access may continue until it expires or is revoked.

Keep it private, protect the device, avoid public sharing links, and remove working copies when no longer needed.

Many services offer downloads or request processes. Availability and legal scope depend on the service, location, and information involved.

Not necessarily. Active records, backups, security logs, and legal retention obligations may have different processes.

Export and import formats differ. Some content, settings, and relationships may not transfer even when a download is available.

Combining records into summaries such as counts or averages. The privacy implications depend on the detail retained and whether individuals can still be identified.

Replacing direct identifiers with other values while information may remain linkable using additional data. It is different from a guarantee of anonymity.

A way to transform information so it can be read with the appropriate key. Its protection depends on where it is applied and who can access keys or readable copies.

Not necessarily. Rollouts can depend on region, platform, account type, and timing.

Check adoption, effective dates, jurisdiction, definitions, and exemptions through official sources.

Sources, instructions, and scope should be reviewed when relevant changes or reader reports identify a need for revision.

Email support@datacash.app or call +1-843-996-7780. The Contact page provides a message option.

6650 Rivers Ave, North Charleston, SC, 29405. EIN: 41-2520862. DUNS: 144888707.

The official website is https://datacash.app. The supplied social handle is @datacashapp; the Social directory provides platform links.