DATA EXPLOITATION Sample Clauses

DATA EXPLOITATION. The Licensee owns all the Data. The Licensee is solely responsible for the quality, lawfulness and relevance of the Data that it transmits to the Processor as well as for their use with the Application Service and the results thereof. In addition, the Licensee guarantees to be the owner of all rights (including intellectual property rights and authorization of third parties) allowing him/her to use the Data. The Licensee guarantees that the Data does not violate the laws and regulations in force, the rights of third parties and is free from any virus or malicious code likely to harm the Solution or the Application Service. If the Processor becomes aware that an element of the Data violates the above stipulations, the Processor is entitled to remove or render unavailable such an element. The Licensee guarantees the Processor in the event of failure to comply with the stipulations of this article. The Licensee undertakes to defend the Processor at its own expense and indemnify the Processor against any costs, claims or damages incurred by the Processor or for which the Processor may be liable due to the Licensee's default.

DATA EXPLOITATION. The Customer owns all the Data.

DATA EXPLOITATION. The Business Model of Data Collection – Data flow: The channel where data is transferred from one entity to another. A dataset is shared across several repositories. Each repository holds an 1. An example of the management flow and data flow: Let Company A be offering a service via mobile app, in which it is necessary to collect sensitive data, e.g. face and voice. This company has an service-level-agreement (SLA) with Company B, which stores and processes the datasets for Company A. At time t = t0, Company A creates an electronic consent (e-consent) for the data subject who agrees the processing of his/hers dataset. Later, at time t = t1, Company A creates new agreements with another Company C to carry out their business, selling their solutions on processing data. As new actors come into the scenario, their actions may affect the current agreement between the data subject and Company A. instance of this dataset. Each instance is a derivative of the original dataset. Formally, the formula can be described as follows: d∗ = f2(dj = f1(d, P1), P2) , where d is the original dataset, functions f1, f2 are transformation functions (e.g. pseudonymisation operations), and P1, P2 sets of policies applied to d and dj, respectively. The ideal situation is setting an equilibrium between parties. Within this exchange context, the value of a dataset to the data subject is balanced with the value of that dataset to the aggregated data processor within its domain. Therefore, the service or tool value offered is proportional to the value of the dataset exchanged along with the related costs. An important factor that aims 8 ▇. ▇▇▇▇▇▇▇▇-▇▇▇▇▇ et al. this equilibrium are the data regulations, which are forcing companies to enforce transparency, and accountability regarding customers’ privacy. For this purpose, they relay on data subject consent and privacy policies. Hence, privacy policies and the user’s consent are static entities that determines the relationship, actions and conditions between the actors of the dynamic system.

DATA EXPLOITATION