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Understandability

Characteristic Name: Understandability
Dimension: Usability and Interpretability
Description: The data is understandable
Granularity: Information object
Implementation Type: Process-based approach
Characteristic Type: Usage

Verification Metric:

The number of tasks failed or under performed due to the lack of understandability of data
The number of complaints received due to the lack of understandability of data

GuidelinesExamplesDefinitons

The implementation guidelines are guidelines to follow in regard to the characteristic. The scenarios are examples of the implementation

Guidelines: Scenario:
Ensure that appropriate signs/language is used to strenthen the readers understanding about the information object (1) Poor, good, excellent is more suitable than 1, 2,3 as ratings to compare two factors
Avoid any possibility of ambiguity in understanding data with the inclusion of footnotes, legend etc. (1) Footnote : Total price includes GST.
Provide supplements to understand the content of non-text and non-numeral information (e.g.. Images) (1) A location in a plan can be identified by the coordinates
Ensure that data are concisely represented without being overwhelmed (1) Focussed on one topic
Convenient and user friendly (more natural) formats are used for structured attributes like dates, time, telephone number, tax ID number, product code, and currency amounts (1) U.S. phone number formats [+1(555)999-1234]
Appropriate fonts and styles are used to improve the clarity of the content (1) Headings are marked in bold letters, Totals figures are are marked with bold numbers

Validation Metric:

How mature is the process to maintain the understandability of data

These are examples of how the characteristic might occur in a database.

Example: Source:
a Social Security number must consist of nine numeric digits. If this is your only definition, you will find that all values that are blank, contain characters other than numeric or contain less than or more than nine digits. However, you can go further in your definition. The government employs a scheme of assigning numbers that allows you to examine the value in more detail to determine if it is valid or not. Using the larger rule has the potential for finding more inaccurate values. J. E. Olson, “Data Quality: The Accuracy Dimension”, Morgan Kaufmann Publishers, 9 January 2003.

The Definitions are examples of the characteristic that appear in the sources provided.

Definition: Source:
The data element is used only for its intended purpose, that is, the degree to which the data characteristics are well understood and correctly utilized. B. BYRNE, J. K., D. MCCARTY, G. SAUTER, H. SMITH, P WORCESTER 2008. The information perspective of SOA design Part 6:The value of applying the data quality analysis pattern in SOA. IBM corporation.
1) Periodic Reports, such as Financial Statements, Annual Reports, and Policy and Procedure Manuals should have a standard format with a style sheet that presents the information in a consistent and easily read and understood format.

2) The Characteristic in which Information is presented in a way that clearly communicates the truth of the data. Information is presented with clear labels, footnotes, and/or other explanatory notes, with references or links to definitions or documentation the clearly communicates the meaning and any anomalies in the Information.

ENGLISH, L. P. 2009. Information quality applied: Best practices for improving business information, processes and systems, Wiley Publishing.
Usability of data refers to the extent to which data can be accessed and understood. HIQA 2011. International Review of Data Quality Health Information and Quality Authority (HIQA), Ireland. http://www.hiqa.ie/press-release/2011-04-28-international-review-data-quality.
A good presentation provides the user with everything required for the correct interpretation of information. When there is any possibility of ambiguity, a key or legend should be included. LOSHIN, D. 2001. Enterprise knowledge management: The data quality approach, Morgan Kaufmann Pub.
Is the information understandable or comprehensible to the target group? LOSHIN, D. 2006. Monitoring Data quality Performance using Data Quality Metrics. Informatica Corporation.
1) The extent to which the content of an object is focused on one topic.

2) The extent of cognitive complexity of an information object measured by some index or indices.

3) The extent to which the model or schema and content of an information object are expressed by conventional, typified terms and forms according to some general-purpose reference source.

STVILIA, B., GASSER, L., TWIDALE, M. B. & SMITH, L. C. 2007. A framework for information quality assessment. Journal of the American Society for Information Science and Technology, 58, 1720-1733.
1) Data are compactly represented without being overwhelmed.

2) Data are clear without ambiguity and easily comprehended.

WANG, R. Y. & STRONG, D. M. 1996. Beyond accuracy: What data quality means to data consumers. Journal of management information systems, 5-33.

 

Appropriate presentation

Characteristic Name: Appropriate presentation
Dimension: Usability and Interpretability
Description: The data presentation is aligned with its use
Granularity: Information object
Implementation Type: Process-based approach
Characteristic Type: Usage

Verification Metric:

The number of tasks failed or under performed due to the lack of appropriate presentation of data
The number of complaints received due to the lack of appropriate presentation of data

GuidelinesExamplesDefinitons

The implementation guidelines are guidelines to follow in regard to the characteristic. The scenarios are examples of the implementation

Guidelines: Scenario:
Ensure that Universally accepted standard formats are used to maintain the compatibility of information across organisations and across time (1) A patients diagnostic card generated in one hospital is compatible with another hospital.
Ensure that information can be aggregated or combined through the use of compatible formats (1) Product wise monthly sales report can be generated by combining the sales reports of three subsidiaries
Ensure that the data presentations are familiar to the users even if the application platform is changed. (1) A quotation created in one system is sent to another system through an EDI message and displayed in the same presentation format
Ensure the media of presentation is appropriate for the target group (1) A step by step written instruction list in a documents appropriate for a software engineer. (2) A video display is appropriate for a mechanic
Ensure that the presentation formats are flexible to accommodate changes easily (1) An invoice document may require additional space to mansion authorisation evidence

Validation Metric:

How mature is the process to maintain appropriate presentation of data

These are examples of how the characteristic might occur in a database.

Example: Source:
my birth date is December 13, 1941. If a personnel database has a BIRTH_DATE data element that expects dates in USA format, a date of 12/13/1941 would be correct. A date of 12/14/1941 would be inaccurate because it is the wrong value. A date of 13/12/1941 would be wrong because it is a European representation instead of a USA representation. J. E. Olson, “Data Quality: The Accuracy Dimension”, Morgan Kaufmann Publishers, 9 January 2003.

The Definitions are examples of the characteristic that appear in the sources provided.

Definition: Source:
A measure of how information is presented to and collected from those who utilize it. Format and appearance support appropriate use of information. D. McGilvray, “Executing Data Quality Projects: Ten Steps to Quality Data and Trusted Information”, Morgan Kaufmann Publishers, 2008.
1) The Characteristic in which formatted data is presented consistently in a standardized or consistent way across different media, such as in computer screens, reports, or manually prepared reports.

2) The Characteristic of Information being presented in the right technology Media, such as online, hardcopy report, audio, or video.

3) The degree to which Information is presented in a way Intuitive and appropriate for the task at hand. The Presentation Quality of Information will vary by the individual purposes for which it is required. Some users require concise presentation, whereas others require a complete, detailed presentation, and yet others require graphic, color, or other highlighting techniques.

ENGLISH, L. P. 2009. Information quality applied: Best practices for improving business information, processes and systems, Wiley Publishing.
1) Appropriateness is the dimension we use to categorize how well the format and presentation of the data match the user needs. In our example, there is a difference between a high-level monthly sales report that is supplied to senior management and the daily product manifests that are handed to the shipping department for product packaging.

2) Flexibility in presentation describes the ability of the system to adapt to changes in both the represented information and in user requirements for presentation of information. For example, a system that display different counties; currencies may need to have the screen presentation change to allow for more significant digits for prices to be displayed when there is a steep devaluation in one county’s currency.

3) In an environment that makes use of different kinds of systems and applications, a portable interface is important so that as applications are migrated from one platform to another, the presentation of data is familiar to the users. Also, when dealing with a system designed for international use, the user of international standards as well as universally recognized icons is a sign of system designed with presentation portability in mind.

LOSHIN, D. 2001. Enterprise knowledge management: The data quality approach, Morgan Kaufmann Pub.
1) Data is presented in an intelligible manner.

2) Data is presented in a manner appropriate for its use, with respect to format, precision, and units.

PRICE, R. J. & SHANKS, G. Empirical refinement of a semiotic information quality framework. System Sciences, 2005. HICSS'05. Proceedings of the 38th Annual Hawaii International Conference on, 2005. IEEE, 216a-216a.
Good format, like good views, are flexible so that changes in user need and recording medium can be accommodated. REDMAN, T. C. 1997. Data quality for the information age, Artech House, Inc.
Data are always presented in the same format and are compatible with the previous data. WANG, R. Y. & STRONG, D. M. 1996. Beyond accuracy: What data quality means to data consumers. Journal of management information systems, 5-33.