Club Deportivo Tuilla is a Spanish football team based in Tuilla, a small village in the municipality of Langreo, in the autonomous community of Asturias. Founded in 1952, it plays in Tercera División – Group 2, holding home matches at Estadio El Candín, which has a capacity of 2,800 spectators. After winning the 2010 FIFA World Cup in South Africa and the 2011 UEFA Champions League Final, International footballer David Villa, born in Tuilla and enjoyed individual success with Sporting de Gijón, Real Zaragoza, Valencia CF, FC Barcelona, Atlético Madrid, Spain, waved a CD Tuilla scarf at the crowd. In 2007, Tuilla won the regional stage of the Copa Federación by the first time and reached the semi-finals in the 2007–08 National stage, after beating Laguna and San Sebastián de los Reyes, before being eliminated by Ourense due to the away goals rule. Tuilla repeated the Regional success in 2011 and 2012, but in both editions was eliminated in the Round of 32 of the National stage. In the 2012–13 season, Tuilla finished as champion of the Asturian group of Tercera División, but failed in its third attempt of promoting to Segunda División B.
In 2013, Tuilla played for the first time in its history the Copa del Rey. In the first round, the team beat CD Tropezón by 0–1 in the overtime, in a game where Tuilla finished with nine players. Tuilla was eliminated in the second round by Burgos CF which won at El Candín by 0–3. In the 2017-18 season the club finished 7th in the Tercera División, Group 2. In May 2019 Julio Llanos was appointed manager of the club. 22 seasons in Tercera División Tercera División: 2012–13 Copa RFEF: 2007, 2011, 2012 Abelardo Fernández Ricardo Bango Official website Futbolme team profile
Pseudonymization is a data management and de-identification procedure by which identifiable information fields within a data record are replaced by one or more artificial identifiers, or pseudonyms. A single pseudonym for each replaced field or collection of replaced fields makes the data record less identifiable while remaining suitable for data analysis and data processing Pseudonymization can be one way to comply with the European Union's new General Data Protection Regulation demands for secure data storage of personal information. Pseudonymized data can be restored to its original state with the addition of information which allows individuals to be re-identified, while anonymized data can never be restored to its original state; the choice of which data fields are to be pseudonymized is subjective. Less selective fields, such as Birth Date or Postal Code are also included because they are available from other sources and therefore make a record easier to identify. Pseudonymizing these less identifying fields removes most of their analytic value and is therefore accompanied by the introduction of new derived and less identifying forms, such as year of birth or a larger postal code region.
Data fields that are less identifying, such as date of attendance, are not pseudonymized. It is important to realize that this is because too much statistical utility is lost in doing so, not because the data cannot be identified. For example, given prior knowledge of a few attendance dates it is easy to identify someone's data in a pseudonymized dataset by selecting only those people with that pattern of dates; this is an example of an inference attack. The weakness of pre-GDPR pseudonymized data to inference attacks is overlooked. A famous example is the AOL search data scandal; the AOL example of unauthorized re-identification did not require access to separately kept “additional information”, under the control of the data controller as is now required for GDPR compliant Pseudonymisation. See New Definition of Pseudonymization Under GDPR below. Protecting statistically useful pseudonymized data from re-identification requires: a sound information security base controlling the risk that the analysts, researchers or other data workers cause a privacy breachThe pseudonym allows tracking back of data to its origins, which distinguishes pseudonymization from anonymization, where all person-related data that could allow backtracking has been purged.
Pseudonymization is an issue in, for example, patient-related data that has to be passed on securely between clinical centers. The application of pseudonymization to e-health intends to preserve the patient's privacy and data confidentiality, it allows primary use of medical records by authorized health care providers and privacy preserving secondary use by researchers. In the US, HIPAA provides guidelines on how health care data must be handled and data de-identification or pseudonymization is one way to simplify HIPAA compliance. However, plain pseudonymization for privacy preservation reaches its limits when genetic data are involved. Due to the identifying nature of genetic data, depersonalization is not sufficient to hide the corresponding person. Potential solutions are the combination of pseudonymization with encryption. An example of application of pseudonymization procedure is creation of datasets for de-identification research by replacing identifying words with words from the same category, however, in this case it is in general not possible to track data back to its origins.
Effective as of May 25, 2018, the EU General Data Protection Regulation defines pseudonymization for the first time at the EU level in Article 4. Under Article 4 definitional requirements, data is pseudonymized if it cannot be attributed to a specific data subject without the use of separately kept "additional information.” Pseudonymized data embodies the state of the art in Data Protection by Design and by Default because it requires protection of both direct and indirect identifiers. GDPR Data Protection by Design and by Default principles as embodied in pseudonymization require protection of both direct and indirect identifiers so that personal data is not cross-referenceable via the Mosaic Effect without access to “additional information”, kept separately by the controller; because access to separately kept “additional information” is required for re-identification, attribution of data to a specific data subject can be limited by the controller to support lawful purposes only. GDPR Article 25 identifies pseudonymization as an “appropriate technical and organizational measure” and Article 25 requires controllers to: “…implement appropriate technical and organizational measures for ensuring that, by default, only personal data which are necessary for each specific purpose of the processing are processed.
That obligation applies to the amount of personal data collected, the extent of their processing, the period of their storage and their accessibility. In particular, such measures shall ensure that by default personal data are not made accessible without the individual's intervention to an indefinite number of natural persons.” A central core of Data Protection by Design and by Default under GDPR Article 25 is enforcement of technology controls that support appropriate uses and the ability to demonstrate that you can, in fact, keep your promises. Technologies like pseudonymization that enforce Data Protection by Design and by Default show individual data subjects that in addition to coming up with new ways to derive value from data, organizations are pursuing innovative technical