Detail of GB/T 26316-2023

Introduction of GB/T 26316-2023

Market, opinion and social research, including insights and data analytics - Vocabulary and service requirements 1 Scope This document establishes terms, definitions and service requirements for service providers conducting market, opinion and social research, including insights and data analytics (hereinafter referred to as “service providers”). Non-market research activities, such as direct marketing, are outside the scope of this document. 2 Normative references There are no normative references in this document. 3 Terms and definitions For the purposes of this document, the following terms and definitions apply. 3.1 access panel sample (3.86) database of potential participants (3.64) who declare that they will cooperate for future data collection if selected Note: This does not include continuously reporting panels (e.g. TV-rating panels) or re-contact databases (asking for permission for follow-ups). 3.2 accuracy degree of closeness between the estimate and the agreed parameter value [SOURCE: GB/T 26315-2010, 5.2.30] 3.3 active panel member panel member (3.61) who, within the last 12 months, has participated in at least one research study if requested, updated their profile data, or registered to join the access panel (3.1) 3.4 ad impression display of an advertisement on a device 3.5 algorithm process or set of rules to be followed in calculations or other problem solving operations 3.6 anonymize remove, obscure, aggregate or alter identifiers with the aim of preventing the identification of individuals to whom data originally related 3.7 appraisal process of monitoring the competency of an individual or group of individuals in carrying out their work 3.8 attestation declaration of conformity by the service provider (3.92) related to the statement of applicability (SoA) 3.9 audit systematic, independent and documented process for obtaining evidence and evaluating it objectively to determine the extent to which a standard’s requirements are fulfilled 3.10 auditor person with the competence to conduct an audit (3.9) 3.11 automated coding form of coding where manual coding is replaced, totally or in part, by various forms of computer coding or computer-assisted coding using computer-stored code lists, dictionaries, automated systems, machine learning, artificial intelligence or other technologies 3.12 bias systematic deviation between the estimate and the agreed parameter value 3.13 bot autonomous software that operates as an agent for a user or a program or simulates a human activity 3.14 client individual, organization, department or division, whether it is internal or external, that requests or commissions a research project 3.15 code character or combination of numeric, alphabetic or other types of characters associated with each response category 3.16 code frame list of categories with associated codes (3.15) for classifying responses 3.17 completion rate number of participants (3.62) who fully complete a research project divided by the number of participants who were invited to participate 3.18 computer-assisted interviewing; CAI interviews where responses are keyed directly into a computer and where the administration of the interview is managed by a specifically designed program. Example Computer-assisted personal interviewing (CAPI); computer-assisted telephone interviewing (CATI); computer-assisted self-interviewing (CASI); computer-assisted interviewing via web/internet (CAWI). 3.19 confidentiality requirement that information, materials and data collected are protected from unauthorized access 3.20 consent freely given agreements based on adequate information obtained prior to the collection/use of participant (3.62) data 3.21 cookie small piece of information (i.e. program code) that is stored on a browser for the purpose of identifying that browser during activities and between visits or sessions 3.22 dashboard software application with which a number of mini-applications can be reviewed or managed and reported Example: Mini-applications could include app to export data or allow API access. 3.23 data cleaning process of identifying, correcting or removing unneeded or inaccurate data for research quality purposes 3.24 data collection instrument tool created for the purpose of gathering information from participants (3.62) Example: Questionnaire, discussion guide, biometric device, webscraping technology, camera. 3.25 data editing set of methods for verifying the collected data and, if necessary, correcting the data 3.26 data entry process step where data collected are converted into computer-readable form or other types of standardized forms Note 1: Simple data entry is data entry containing no built-in logic checks. Note 2: Logic data entry is a data entry process that uses automated checks for the logic of data on elements such as data types, filters, question skips and response options. 3.27 data processing management and converting of data from their raw state through to a required output 3.28 data record set of data derived from a reporting or observed unit 3.29 de-duplication process to remove data records (3.28) corresponding to a participant (3.62) or record (3.76) that appears more than once in a research dataset or access panel (3.1) 3.30 depth interview semi-structured or unstructured interview conducted to understand the underlying motivations, beliefs, attitudes behaviours and feelings of a participant (3.62) 3.31 derived data item data item calculated or recoded from one or more sources and/or categories 3.32 device ID device identification

Contents of GB/T 26316-2023