Data classification and licensing (DatCLic)****

Malatest及其主要负责人经常与试图与合作伙伴达成数据共享协议的政府和行业机构进行咨询。Malatest有兴趣研究和开发概念、流程和工具，以实现更有效的数据共享协议的控制、审计和执行。规定了管理规则库、资产共享协议和数据监测要求。*此Engage项目的重点将有两个：*首先，研究人员将研究机器学习技术在根据管理规则库中规定的类别自动对现有数据资产进行分类的问题上的应用。*第二，需要监控许可数据资产(及其派生的)的持续使用情况，并允许一致地传播未来许可证和管理规则的任何更新。研究人员将调查将区块链技术应用于许可证分发和使用监控的分布式分类账的可能性。*该研究项目将产生一个概念证明原型，以应对上述两个挑战。*该项目的结果将为加拿大直接受益，因为它为我们的政府部委、政府合作机构和机构提供了实现数据共享的工具，同时有效地执行所有相关的数据共享协议和法规。

Malatest and its key principals frequently consult with government and industry agencies which are attempting to reach data sharing agreements with partners. Malatest is interested in researching and developing concepts, processes and tools for enabling more effective control, auditing and enforcement of data sharing agreements. A management rule base and asset sharing protocols and data monitoring requirements have been specified. ****The focus of this Engage project will be twofold: ****Firstly, researchers will investigate the application of machine-learning techniques to the problem of automatically classifying existing data assets according to the categories set out in the management rule base.****Secondly, the ongoing use of licensed data assets (and derivations thereof) needs to be monitored and also allow for the consistent propagation of any future updates of licenses and management rules. The researchers will investigate the potential for adapting Blockchain technology as a distributed ledger for license distribution and usage monitoring.****The research project will produce a proof of concepts prototype that addresses the above two challenges.****The project results will directly benefit Canada by providing our government ministries, crown cooperations and agencies with tools that enable data sharing while effectively enforcing all relevant data sharing agreements and regulations.