Traceability
| Characteristic Name: | Traceability |
| Dimension: | Reliability and Credibility |
| Description: | The lineage of the data is verifiable |
| Granularity: | Record |
| Implementation Type: | Process-based approach |
| Characteristic Type: | Usage |
Verification Metric:
| The number of tasks failed or under performed due to lack of traceability in data |
| The number of complaints received due to lack of traceability in data |
The implementation guidelines are guidelines to follow in regard to the characteristic. The scenarios are examples of the implementation
| Guidelines: | Scenario: |
|---|---|
| Maintain provenance records for the events such as creation, update,transcription, abstraction, validation and transforming ownership, if the data are dynamic. | (1) Inventory system shows the current stocks and keep records for all the transactions that the stocks are subjected to |
| In case of multiple sources are available for same data/information, implement a traceability mechanism to view all versions from multiple sources | (1) Content management systems |
| Maintain proper protocols/standards/policy to archive data | (1) Every invoice is archived after 120 days of payments. |
| Maintain versions of data records where necessary | (1) Customer versions |
Validation Metric:
| How mature is the process to maintain traceability in data |
These are examples of how the characteristic might occur in a database.
| Example: | Source: |
|---|---|
| minutes of a meeting will be produced in draft form and reviewed by the members of the committee before being approved. Once this process of creation is finished the record must be fixed and must not be susceptible to change. If a record is changed or manipulated in some way, it no longer provides evidence of the transaction it originally documented. For example, if someone alters the minutes of a meeting after they have been approved, the minutes can no longer be considered an accurate record of the meeting. This is another issue that becomes more important in an electronic context. | K. Smith, “Public Sector Records Management: A Practical Guide”, Ashgate, 2007. |
The Definitions are examples of the characteristic that appear in the sources provided.
| Definition: | Source: |
|---|---|
| Is the background of the information visible (author, date etc.)? | EPPLER, M. J. 2006. Managing information quality: increasing the value of information in knowledge-intensive products and processes, Springer. |
| A data provanance record can include information about creation, update, transcription, abstraction, validation and transforming ownership of data. | ISO 2012. ISO 8000-2 Data Quality-Part 2-Vocabulary. ISO. |
| The extent to which the correctness of information is verifiable or provable in the context of a particular activity. | 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. |
Continuity of data access
| Characteristic Name: | Continuity of data access |
| Dimension: | Availability and Accessability |
| Description: | The technology infrastructure should not prohibit the speed and continuity of access to the data for the users |
| Granularity: | Information object |
| Implementation Type: | Process-bases approacd |
| Characteristic Type: | Usage |
Verification Metric:
| The number of tasks failed or under performed due to the lack of continuity in data access |
| The number of complaints received due to lack of continuity in data access |
The implementation guidelines are guidelines to follow in regard to the characteristic. The scenarios are examples of the implementation
| Guidelines: | Scenario: |
|---|---|
| Convenient and efficient platform should be made available to access data depending on the task at hand | (1) For a sales person, a web based interface run on a smart device is more suitable to quickly access data |
| Speed of the data retrieval should be acceptable for users working pace | (1) For an online customer care executive, speedy retrieval of information is necessary since the customer cannot be kept waiting (2) With the growth of the database reports become slower (Anti example) |
| Continuous and unobstructed connectivity should be ensured for data retrievals | (1) Connection lost while accessing reports (Anti example) |
| Proper concurrency control has been implemented | (1) Controlling access to data by locks |
| Technological changes in the infrastructure/system should be handled in such a way that they should not make data inaccessible | (1) New version of the software does not provide access to " X out orders" since the new version does not allow the function "X out" |
Validation Metric:
| How mature is the process of maintaining an infrastructure for data access |
These are examples of how the characteristic might occur in a database.
| Example: | Source: |
|---|---|
| 1) For example, recording the age and race in medical records may be appropriate.
However, it may be illegal to collect this information in human resources departments. 2) For example, the best and easiest method to obtain demographic information may be to obtain it from an existing system. Another method may be to assign data collection by the expertise of each team member. For example, the admission staff collects demographic data, the nursing staff collects symptoms, and the HIM staff assigns codes. Team members should be assigned accordingly. |
B. Cassidy, et al., “Practice Brief: Data Quality Management Model” in Journal of AHIMA, 1998, 69(6). |
The Definitions are examples of the characteristic that appear in the sources provided.
| Definition: | Source: |
|---|---|
| 1) Is there a continuous and unobstructed way to get to the information?
2) Can the infrastructure match the user’s working pace? |
EPPLER, M. J. 2006. Managing information quality: increasing the value of information in knowledge-intensive products and processes, Springer. |
| Data is easy and quick to retrieve. | 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. |
| 1) availability of a data source or a system.
2) Accessibility expresses how much data are available or quickly retrievable. 3) The frequency of failures of a system, its fault tolerance. |
SCANNAPIECO, M. & CATARCI, T. 2002. Data quality under a computer science perspective. Archivi & Computer, 2, 1-15. |