Data principles establish a clear standard that promotes public trust in our data management and provides high-quality, inclusive and reliable statistics. Data principles help create the data conditions for delivering the data strategy and are supported by data and statistical policies and data standards. According to the principle of data minimization, personal data must be adequate, relevant and limited to what is necessary in relation to the purposes for which they are processed. This means that data that is not necessary to achieve the intended purpose cannot be legally collected, stored, or processed.
Therefore, this principle is largely incompatible with data-intensive operations performed with personal data, in which all data is valuable, but none (or very few) are actually necessary to achieve the intended purpose. Conduct impartial and inclusive consultations Maintaining Member States' trust in data requires an impartial and inclusive process of consultation with Member States before WHO uses their data. WHO will maintain the trust placed in it by Member States when the Organization processes data that Member States have shared with it and are under the control of WHO. Adapt to specific contexts When necessary, WHO will consider adapting approaches and methods to report rare events or data from Member States with low populations.
Cloudian storage devices are easy to implement and use, allowing data to be stored at a petabyte scale and accessed instantly. Cloudian supports high-speed backup and restore with parallel data transfer (18 TB per hour writes with 16 nodes). HyperStore gives you the power to share files in the cloud on a local device and the control to protect your data in any cloud environment. The General Data Protection Regulation (GDPR) defines the principles for the legal management of personal information.
The personal data collected must be adequate for the purpose established by the organization, be accurate and up to date. In other words, the purpose of the processing will be specified before the processing begins and will be respected throughout the life cycle of the personal data. Common security measures include protecting physical facilities, encrypting data at rest and in transit, and keeping a backup copy of personal information at an external location. In HyperStore, storage takes place behind the firewall, you can configure geographical limits for data access and define policies for data synchronization between user devices.
As human beings increasingly rely on the computational support of machines, FAIR data can allow computer systems to find, access, interoperate and reuse data without human intervention or with minimal human intervention. This must be evaluated on a case-by-case basis, taking into account elements such as the category of the data being processed, the reasonable expectations of the interested party and the safeguards implemented (such as pseudonymization). These security measures are always necessary when processing personal data; in addition, in certain specific cases, more stringent regulations may apply. Exceptions to the obligation to provide information are very few and should be interpreted strictly, but it is useful to know that one of these exceptions occurs when the data is not collected directly from the data subject and it is likely that the provision of the information would seriously impair or impair the objectives of the processing.