Types of Data. 1.1 Raw: data submitted by Participants (e.g., DITL);
Types of Data. Institution Data may include, but information, contact details, professional activities and affiliations, professional qualifications, education and training, financial information on the educational grant provided by Medtronic to Institution, and bank account information. In case Institution provides unsolicited additional information, including personal preferences, Medtronic will process such data in accordance with this data protection clause. Medtronic may identify certain characteristics, or traits on the basis of which Medtronic may create or compile professional, compromiso entre las partes respecto al objeto del mismo y sustituye a todos los acuerdos o compromisos anteriores celebrados entre las partes en relación con su objeto.
Types of Data. For the purposes of this set of documents there are essentially three classes of data as defined by the Act itself listed below:
Types of Data. Almost 3.000 data attributes can be exchanged via My Product Manager. These attributes are determined by leading retailers and suppliers/manufacturers in the Benelux do-it-yourself industry. The attributes can roughly be divided into several groups, based on their relevance and purpose: - Common attributes - eCommerce attributes - Attributes for dangerous goods and environmental legislation You will find more information about these group of attributes in the next sections.
Types of Data. Data will be gathered to establish baseline conditions, evaluate impacts of Covered Activities on Covered Species, and develop conservation strategies and measures for Covered Species. Data needed to accomplish these tasks may include, but will not necessarily be limited to: species’ life histories, species’ occurrence, population abundance and distribution, population trends, population genetics, habitat locations and conditions, barrier and hazard types and locations, habitat connectivity, and ecological threats and stressors.
Types of Data. Institution Data may include, but are not limited to, individuals’ basic identity information, contact details, professional activities and affiliations, professional qualifications, education and training, financial information on the educational grant provided by Medtronic to Institution, and bank account information. In case Institution provides unsolicited additional information, including personal preferences, Medtronic will process such data in accordance with this data protection clause. Medtronic may identify certain characteristics, or traits on the basis of which Medtronic may create or compile professional, compromiso entre las partes respecto al objeto del mismo y sustituye a todos los acuerdos o compromisos anteriores celebrados entre las partes en relación con su objeto.
Types of Data. Data collected as evidence of teacher practice may be quantitative, qualitative, or a combination of both. Quantitative data includes frequencies, distributions and other counts or tallies. For example the observer could use a checklist to tally how many questions were asked of children in the front row or children who had their hands raised versus not. The evaluator might also chart the types of questions asked (higher versus lower levels). Qualitative data can include scripted notes detailing patterns of activities, vocabulary used, and events observed. In both cases accuracy is essential to ensure the credibility of the process and the evaluator.
Types of Data. CY 2016 cost report data for the Opt-Out program served as the foundation for the CY 2018 capitation rate development for the MyCare program. The following data sources were utilized to inform adjustments to the plan-submitted cost report data and population stratifications: • Historical eligibility files provided by ODM; • Encounter data submitted by the MCOPs; • Re-priced inpatient and outpatient hospital claims experience provided by ODM; • Fee-for-service (FFS) data for dual eligible in counties outside of MyCare regions; • CY 2016 Managed Care Survey completed by each MCOP; and, • Statutory financial statement data.
Types of Data. Under this Agreement, the College and the School District agree to share individual student records on all their students past and present within the limits established in this document. Individual student records are limited to data that are available and to the following: • Identifiers: student name; date of birth; Texas Student Data System ID; Xxx College ID; Social Security Number. • Contact Information: home address; email addresses; phone numbers. • Demographics: race/ethnicity; gender; citizenship status. 1 Privacy laws include, but are not limited to the Family Educational Rights and Privacy Act (FERPA). See the Family Educational Rights and Privacy Act Guidance for Reasonable Methods and Written Agreements: xxxxx://xxx0.xx.xxx/policy/gen/guid/fpco/pdf/reasonablemtd agreement.pdf accessed on 5/30/18. • Academic Records: transcripts showing classes taken, the start and end dates of those classes and the grades in those classes; class attendance; grade point averages; scores on standardized tests; declarations of areas of study such as endorsements, majors and minors; awards representing the completion of educational programs such as diplomas, degrees, and certificates. • Financial Information: participation in subsidized meal programs; family income; expected family contribution (from FAFSA). • Family Information: number of siblings; educational level of parents; family structure. • Safety and Security Records: video and audio recordings of students; records of complaints involving students; records of disciplinary action involving students. In addition, the College and the School District agree to share information that is created by aggregating the data from individual student records within the limits established in this document.
Types of Data. ☐ The type of personal data used is defined in the attached service agreement. or ☒ The subject matter of processing personal data pertains to the following data types/categories (list/ description of data categories) ☐ Personal identifiable data ☐ Communication data (e.g. telephone, e-mail, IP address) ☐ Contract reference data (contractual relationship, product or contractual interest) ☐ Customer history ☐ Contract billing and payment data ☐ Planning and operating data ☐ Disclosed information (from third parties, e.g. credit agencies, or from public directories) ☒ Within the scope of support service (remote or on-site maintenance), insight into any conceiv- able form of personal data can arise for a short period of time, which is determined by customer behaviour.
