ISO 8000-2:2020 pdf download – Data quality

03-06-2022 comment

ISO 8000-2:2020 pdf download – Data quality
3.6.1 data dictionary entry
description of an entity (3.3.3) type containing, at a minimum, an unambiguous identifier (3.3.1), a term and a definition Note 1 to entry: In the ISO 8000 data (3.2.2) architecture, a property need not be associated with a specific data type in a data dictionary (3.6.2). The association between a property and a data type can be made in a data specification (3.6.3). Note 2 to entry: In order to exchange a value corresponding to a data dictionary entry, more information (3.2.1) than an identifier, a name and a definition could be needed. For a property, a data type is needed. Depending on the kind of property, other data elements (e.g. unit of measure, language) could also be needed. These elements can be given in the data dictionary, in a data specification that references the data dictionary entry, or directly associated with the data. Note 3 to entry: In the ISO 13584 data architecture, the dictionary entry for a property is required to reference a specific data type. Thus, an ISO 13584 dictionary entry is a special case of the more general concept, as it includes elements of a data specification. [SOURCE: ISO 22745-2:2010, B.2.17, modified — The spelling of “datatype” has been changed to “data type” to be consistent with other terms in this document and Note 2 to entry has been modified.]
3.6.3 data specification
set of requirements (3.1.2) covering the characteristics of data (3.2.2) being fit for one or more particular purposes Note 1 to entry: ISO 8000-110 requires a data specification to describe how items belong to a particular class by using entries from a data dictionary (3.6.2). Note 2 to entry: In collaborative relationships, the supplier of data and the user of that data agree the content of the data specification in order to ensure the collaboration will be successful (i.e. the supplier can supply conforming data and the user is able to exploit the data for the intended purposes). Note 3 to entry: An effective data specification is one where the creator of the specification intends for the requirements to be necessary and sufficient for the data to meet the particular purposes. Note 4 to entry: All stakeholders will be able to understand the data specification more effectively if there is an explicit statement of the intended purposes for the data.
3.8.12 data completeness
quality (3.1.3) of a data set (3.2.4) in respect of the content being all that is necessary for an intended purpose EXAMPLE 1 When creating a data specification (3.6.3) that addresses data completeness considerations, an organization includes in the specification a requirement (3.1.2) for a data set to identify explicitly the applicable unit of measure for each physical quantity in the set. EXAMPLE 2 When calculating the average speed of a journey, a user decides to use the start and end times of the journey and the total distance travelled. This decision determines the basis for data completeness of the required data set. EXAMPLE 3 When calculating the maximum speed during a journey, a user decides to use a list of points in time and, for each point, the distance travelled to that point. The user decides an appropriate duration between each point in time. This duration being longer makes the calculation less accurate but prevents the data set becoming inappropriately large. These decisions determine the basis for data completeness of the required data set. EXAMPLE 4 A buyer wants a supplier to send a list of all products (3.5.1) that are available for purchase. The supplier uses ISO 8000-140, which specifies how to provide a statement to confirm the supplier has created a data set representing a list that meets the buyer’s requirement.

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