Data management platform
AssigneeHelios Data Inc.
InventorsFei Zou, Huiyu Zhang, Yi Sun
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AssigneeHelios Data Inc.
InventorsFei Zou, Huiyu Zhang, Yi Sun
Estimating the term…
Techniques are disclosed relating to the management of data. A data provider computer system may store particular data of a user. The data provider computer system may commence sharing of a portion of the particular data with a data consumer computer system. The data provider computer system may continue sharing additional portions of the particular data with the data consumer computer system in response to receiving a report from a verification environment indicating that the particular data is being utilized by the data consumer computer system in accordance with a specified usage policy.
A method, comprising:
A non-transitory computer-readable medium having program instructions stored thereon that are executable by a computer system to perform operations comprising:
A method, comprising:
Dependencies are inferred from the claim text.
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License processing; Key processing: logging; Metering
Network architectures or network communication protocols for network security: for managing network security; network security policies in general
Updating: ensuring data consistency and integrity
Computing arrangements using knowledge-based models: inference or reasoning models
About 14 years 2 months of term left · ends 2 Jan 2041 (estimated)
This disclosure relates generally to a data management platform.
Many companies collect and store data about their users. Such data may include, without limitation, any manner of information, such as user profile information, financial information, medical information, and user activity information (e.g., location data). The creation of such data is growing at an unprecedented rate. Companies often use data to help improve their own systems (e.g., by analyzing the data), or they provide that data to other companies that use the data for some particular purpose. For example, a telecommunication company may analyze geolocation data in order to improve quality of service. Accordingly, data is often considered a valuable resource and thus it is desirable to collect and store. Furthermore, data collected by one entity (e.g., geolocation data collected by a telecommunications company) may often be valuable to another entity (e.g., a retail company that wishes to use the geolocation data to market goods to the user). For this reason, there has been motivation for one company, a “data provider,” to share data of a user or “data subject” with another company, a “data consumer”—an exchange which may be termed a “data economy.”
The collection and management of such data is often problematic for companies, however. Companies are often not aware of all the different types of user data that they have on their systems and even where that data is stored. Thus, it may be extremely difficult for many companies to identify and locate all data of individual customers/users stored across myriad computers and networks within an entity. Accordingly, in many cases, companies cannot benefit from their data if they are not completely aware of it. Still further, even assuming such data can be properly located, ensuring proper internal and external usage of the data—that is, usage that corresponds to company policies for that data—can also be very difficult. As a result, data is often a hindrance to companies, particularly when it is necessary or desirable to share data with another company. The result is that data breaches or misuses are growing increasingly common, and reflect poorly upon the companies that act as the data custodian.
FIG. 1 is a block diagram illustrating example elements of a system that includes a data-defined network (DDN) system, according to some embodiments.
FIG. 2 is a block diagram illustrating example elements of a DDN system, according to some embodiments.
FIG. 3 is a block diagram illustrating example elements of a DDN data structure and a data collection engine of a DDN system, according to some embodiments.
This disclosure includes references to “one embodiment” or “an embodiment.” The appearances of the phrases “in one embodiment” or “in an embodiment” do not necessarily refer to the same embodiment. Particular features, structures, or characteristics may be combined in any suitable manner consistent with this disclosure.
Within this disclosure, different entities (which may variously be referred to as “units,” “circuits,” other components, etc.) may be described or claimed as “configured” to perform one or more tasks or operations. This formulation—[entity] configured to [perform one or more tasks]—is used herein to refer to structure (i.e., something physical, such as an electronic circuit). More specifically, this formulation is used to indicate that this structure is arranged to perform the one or more tasks during operation. A structure can be said to be “configured to” perform some task even if the structure is not currently being operated. A “network interface configured to communicate over a network” is intended to cover, for example, an integrated circuit that has circuitry that performs this function during operation, even if the integrated circuit in question is not currently being used (e.g., a power supply is not connected to it). Thus, an entity described or recited as “configured to” perform some task refers to something physical, such as a device, circuit, memory storing program instructions executable to implement the task, etc. This phrase is not used herein to refer to something intangible. Thus, the “configured to” construct is not used herein to refer to a software entity such as an application programming interface (API).
The term “configured to” is not intended to mean “configurable to.” An unprogrammed FPGA, for example, would not be considered to be “configured to” perform some specific function, although it may be “configurable to” perform that function and may be “configured to” perform the function after programming.