JLINC provides data provenance.
Significant business risk arises from not having a clear view of data, what came in, from where, for what purpose, and on what terms, and most importantly, where did it then go from here. JLINC enables the automated logging of data lineage and provenance with permissions, which allows data risk to be actively managed.
Compliance with many of today's regulations require an audit trail that shows exactly how that data has been derived. JLINC automates this process by logging every data transaction, categorizing it and making that validation available for all relevant parties to inspect should they want or need to do so.
Customers need transparency and control of their data to move beyond the technically and legally opaque models for data sharing most widely in use today. JLINC gives all parties both transparency and control before and after they share their data, thus providing a platform for truly trustworthy data exchange.
Each party has a cloud service that holds and manages all of its contracts. Human-readable (and therefore legally-binding) contracts, expressed in JSON, are signed using standard public key cryptography with audit proof recorded on any database, log, ledger or blockchain.
A term borrowed from the chain-of-custody for art –– proves where data came from, where it was reposted, and by whom.
Each individual can set their own data sharing permissions and preferences and assign them as their one-click default.
Voluntarily shared and maintained data is far more accurate, at lower cost, and forms the basis of trust-based marketing relationships.
Self-validating human readable contracts automate complex data exchange between enterprises under existing legal agreements.
Individual control over the data gathered by their devices can be a crucial differentiator for adoption once people have a choice.
People in the EU, and all global corporations that do business there, need a functional way to manage personal data under GDPR.
A signed automated data exchange layer provides data integrity and validation across systems with or without any blockchain.
Permissioned data provides the high quality automated information flows required for machine learning to be effective.
The $3.1T cost of inaccurate data in the US alone actually represents twelve times the value of global digital advertising.