Abstract: A method and system for obtaining representative sample of automotive data records for data scoring is provided herein. The method may include the following steps: applying a sampling operator to unique IDs of automotive data records space associated with connected vehicles represented by said unique IDs and respective automotive data sources, wherein the sampling operator is selected such that it preserve the proportions in the sample compared with the space; deriving a sample of automotive data records from said automotive data records by selecting a subset of the unique IDs with the sampling operator applied thereto, based on a sampling factor; verifying that the sample of automotive data records is a valid sample of the automotive data records space; and scoring the data records and or the data sources of the sample of automotive data records based on data scoring schemes.

Abstract: A method and a system for detecting a change of ownership of a connected vehicle are provided here. The method may include: obtaining, a plurality of automotive data records associated with connected vehicles having respective drivers; creating, responsive to an explicit indication of a driver association of a specific driver, to a specific connected vehicle of the connected vehicles, a unique driver profile which includes driver parameters being a subset of the automotive data records that are associated with an identity of the specific driver; learning, over a training stage, values of the driver parameters representative of the specific driver; monitoring, over a detection stage, values of the driver parameters of the specific driver, to detect an event of change of ownership of said specific driver related to the specific vehicle, in view of the learnt and monitored driver parameters, and in view of change of ownership criteria.

Abstract: A method and a system for establishing and applying a digital right management (DRM) of data relating to connected cars and obtained from a plurality of sources are provided herein. The method may include the following steps: obtaining a plurality of data entries relating to connected cars and obtained directly from the connected cars; analyzing a plurality of use cases applicable for each of the obtained data entries; automatically selecting, from a plurality of DRM policies, a most suitable DRM policy for the determined use cases; executing the DRM policy of said data entry, using a computer processor. wherein the execution of the DRM Policy on the data entry includes: owner-guardian contractual relationship; permissions, and data section.

Abstract: A method and a system for recognizing trips of vehicles from a plurality of vehicle related activity are provided herein. The method may include the following steps: scanning vehicle data recorders (VDRs) associated with respective vehicles in a specified time range, to determine indications for trip start and trip end indications; filtering out indications for trip start and trip end indications that are irrelevant; grouping trip start and trip end indications into sessions; and filtering out sessions that are not trips, to yield a list of trips. The system implements the method in a server client configuration.

Abstract: A method and a system for multi-tiering of automotive data for complying with privacy regulations are provided herein. The method may include the following steps: receiving a plurality of processed automotive data records; simultaneously storing the data records on three different data tiers in a data store based on privacy tiering rules; managing the data records on the data tiers responsive to ongoing revocation of consent for some of the data records; and providing data records to approved data consumers based on queries in accordance with the privacy tiering rules. The system may implement the method over a server in a client-server configuration.

Abstract: A method and a system for generating a machine learning model for reducing a location error of readings of road signs sensed by connected vehicles, said method comprising: obtaining an incoming stream of readings of road signs captured by connected vehicles traveling along roads, wherein each reading contains a location of a road sign and road sign metadata associated therewith; applying a clustering algorithm to group together readings associated with a common road sign in separate groups; comparing the locations of each group to respective tagged road-signs dataset associated with a correct location, to yield a correction vector for each cluster; and training a machine learning model to correct the location of the readings in each group by learning the correction vectors.

Abstract: A method and a system for matching contracts between automotive data providers and consumers are provided herein. The method may include the following steps: obtaining a plurality of automotive data records and storing in a data store; obtaining data consumers requirements from the data consumers; obtaining data providers requirements from the data providers; and applying a contract matching function to said data consumers requirements and said data providers requirements to yield contact matching between at particular data providers and data consumers.

Abstract: A method and a system for normalizing data and data format of automotive data associated with connected vehicles and obtained from a plurality of sources are provided herein. The system may include: a data collector configured to obtain a plurality of data entries relating to connected vehicles and presented in different data formats from a plurality of sources; a data manipulating platform configured to enable a user to select and order a plurality of manipulating modules configured to manipulate data or data format of the data entries; a computer processor configured to execute the manipulating modules, in the selected order on the data entries, to yield a plurality of respective data entries that are normalized in accordance with a predefined data and data format, wherein the manipulation includes in the selected order at least manipulation of the following: a data type, data name, data format, and data content.

Abstract: A method and system for generating aggregation from a plurality of sets of regulations are disclosed herein. The method may include the following steps: collecting a plurality of set of regulations, wherein a number of regulations in each set of regulations is significantly higher than a set of objects to which the regulations apply; generating a regulations and restriction in a form of a network of the collected sets of regulations; and applying a user defined inference algorithm to derive an applied aggregation responsive to a user-defined use case.

Abstract: A method and a system for aggregating users' consents for use of automotive data by data services are provided herein. The method may include the following steps: obtaining, from a plurality of data sources, a plurality of automotive data records associated with connected vehicles having respective users; determining for each request for automotive data made by said data services, which of the data records require consent; aggregating consent data for each data records, responsive to an indication that the respective user have been authenticated by the data sources; and providing the data services with access to automotive data based on the aggregated consent data. The system may implement the aforementioned steps in a form of a server on a computer network.

Abstract: A system and a method for bundling data insights, in accordance with respective use cases are provided herein. The method may include the following steps: obtaining a plurality of data insights relating to data originated from a plurality of data sources; maintaining a use cases database, holding a plurality of use cases, each affiliated with a respective blend of said data insights; receiving one or more requests from clients for data insights, each request associated with respective business requirements; and providing the clients with a respective one of the bundles according to the respective business requirements and responsive to the requests and based on the use cases database.

Abstract: A method and a system for restricting access to automotive data in a regulated automotive data distribution network are provided herein. The method may include the following steps: receiving a plurality of automotive data sharing rules from automotive data sharing regulations; receiving data sharing restrictions applicable to at least some of the automotive data; generating a data sharing policy based on the automotive data sharing rules and the data sharing restrictions; and applying the data sharing policy to the automotive data to restrict one or more data consumers from accessing all or portions of the automotive data. The system may implement the steps of the aforementioned method using a regulated data distribution server such as a neutral server for automotive data.

Abstract: A system and a method for bundling data features relating to connected vehicles, in accordance with respective use cases are provided herein. The method may include the following steps: obtaining a plurality of data features relating to connected vehicles originated from a plurality of data sources; maintaining a use cases database, holding a plurality of use cases, each affiliated with a respective blend of said data features; receiving one or more requests from clients for data features, each request associated with respective business requirements; and providing said clients with a respective one of said bundles according to the respective business requirements and responsive to the requests and based on the use cases database.

Abstract: A method and a system for overcoming tagged automotive data shortage using machine learning. The system may be implemented over an online automotive data marketplace and may include: a data processing module implemented on a computer processor which receives a set of tagging functions and required automotive data features; a dataset generator implemented on said computer processor which creates custom training sets for a plurality of machine learning algorithms, without tagged data, based on processed automotive data; and a machine learning algorithm generator implemented on said computer processor which trains the machine learning algorithms using the custom training sets, to yield a trained model.

Abstract: A method and a system for selecting an anonymized subset of parameters from datasets of network-connected devices are provided herein. The method may include: obtaining a plurality of datasets, comprising a set of parameters related to one of a plurality of network-connected devices; automatically selecting a subset of parameters from at least one of the datasets, wherein the selecting is based on specified selection criteria; calculating an autocorrelation of the selected subset of parameters; calculating a correlation of the selected subset of parameters and one or more subsets of parameters selected from the datasets relating to network-connected devices other than said one of the plurality of network-connected devices; and applying the correlation and the autocorrelation to a decision function to determine whether the selected subset of parameters is an anonymized subset that is insufficient for determining an identity of the one of the plurality of the network-connected devices.

Abstract: A method and a system for extracting automotive data on demand are provided herein. The method may include the following steps: analyzing automotive data requests issued by automotive data consumers, to determine demand for automotive data; extracting automotive data from the automotive data providers; and adjusting said extracting, based on the demand for the automotive data by said data consumers. The system may implement the aforementioned method over an electronic automotive data marketplace.

Abstract: A method and a system for selecting an anonymized subset of parameters from datasets of network-connected devices are provided herein. The method may include: obtaining a plurality of datasets, comprising a set of parameters related to one of a plurality of network-connected devices; automatically selecting a subset of parameters from at least one of the datasets, wherein the selecting is based on specified selection criteria; calculating an autocorrelation of the selected subset of parameters; calculating a correlation of the selected subset of parameters and one or more subsets of parameters selected from the datasets relating to network-connected devices other than said one of the plurality of network-connected devices; and applying the correlation and the autocorrelation to a decision function to determine whether the selected subset of parameters is an anonymized subset that is insufficient for determining an identity of the one of the plurality of the network-connected devices.

Abstract: A method and a system for establishing and managing a virtual fleet of connected vehicles are provided herein. The system may include: a computer processor associated with an automotive data server; a data storage associated with said automotive data server, wherein the computer processor is configured to obtain a request to form a virtual fleet being an association of two or more connected vehicles, wherein each of the connected vehicles is communicating with said automotive data server that manages a plurality of connected vehicles wherein automotive data thereof is stored in an anonymized form on said data storage, and wherein the computer processor is further configured to establish a virtual fleet of said two or more connected vehicles, responsive to said request, wherein managing said virtual fleet is carried out via said automotive data server.

Abstract: A method and a system for normalizing data and data format of automotive data associated with connected vehicles and obtained from a plurality of sources are provided herein. The system may include: a data collector configured to obtain a plurality of data entries relating to connected vehicles and presented in different data formats from a plurality of sources; a data manipulating platform configured to enable a user to select and order a plurality of manipulating modules configured to manipulate data or data format of the data entries; a computer processor configured to execute the manipulating modules, in the selected order on the data entries, to yield a plurality of respective data entries that are normalized in accordance with a predefined data and data format, wherein the manipulation includes in the selected order at least manipulation of the following: a data type, data name, data format, and data content.

Abstract: A method and a system for aggregating users' consents for use of automotive data by data services are provided herein. The method may include the following steps: obtaining, from a plurality of data sources, a plurality of automotive data records associated with connected vehicles having respective users; determining for each request for automotive data made by said data services, which of the data records require consent; aggregating consent data for each data records, responsive to an indication that the respective user have been authenticated by the data sources; and providing the data services with access to automotive data based on the aggregated consent data. The system may implement the aforementioned steps in a form of a server on a computer network.