Domain 3: Data and Information Management

Question 1

Define “data collection.”

Domain 3:301

Answer 1

Data collection is the process of gathering, validating and measuring information on variables of interest in an established systematic fashion that enables one to answer stated research questions, test hypothesis, and evaluate outcomes.

Question 2

What are the basic principles of data collection?

Domain 3:302

Answer 2

Keep things as simple as possible.
Plan the entire process of data selection, collection, analysis, and use from the start.
Ensure that any data collected are valid, reliable, and credible.
Consider ethical issues, such as alternatives to animal testing and human testing consent.

Question 3

What are the basic steps of a data reliability assessment?

Domain 3:303

Answer 3

Interviews, data testing, tracing to and from source documents, and reviewing data documentation.

Question 4

What are the common types of data that product stewards work with regularly?

Domain 3:304

Answer 4

Composition information, finished product information, and sales and marketing data.

Question 5

Define “effectiveness.”

Domain 3:305

Answer 5

‘Effectiveness” describes the degree of success in producing desired results and meeting organizational objectives.

Prof practices p. 383

Question 6

Define “data storage.”

Domain 3:306

Answer 6

Data storage is the collective methods and technologies that capture and retain digital information on electromagnetic, optical, or silicon-based storage media.

Question 7

What do businesses use maturity modeling for?

Domain 3:307

Answer 7

Businesses use maturity modeling to benchmark their capabilities, identify strengths and gaps, and leverage their data assets to improve business performance.

Question 8

Define “data governance.”

Domain 3:308

Answer 8

The framework of guidance to manage data as an asset.
A program and business discipline, not a project, which needs ongoing investment, support, and exposure.
The foundation of all enterprise information initiatives.

Question 9

Define “data reliability.”

Domain 3:309

Answer 9

Data reliability refers to a measure’s consistency and repeatability.

Prof practices p. 71

Question 10

Define the Klimisch score “reliable without restriction.”

Domain 3:310

Answer 10

“Reliable without restriction” describes data from studies carried out or generated according to generally valid and/or internationally accepted testing guidelines (preferably according to Good Laboratory Practice [GLP]) or in which the test parameters documented are based on a specific (national) testing guideline or in which all parameters described are closely related/comparable to a guideline method.

Question 11

Define the Klimisch score “reliable with restriction.”

Domain 3:311

Answer 11

“Reliable with restriction” describes data from studies mostly not performed according to Good Laboratory Practice (GLP), in which the test parameters documented do not totally comply with the testing guideline but are sufficient to accept the data or in which investigations are described that cannot be subsumed under a testing guideline but are nevertheless well documented and scientifically acceptable.

Question 12

Define the Klimisch score “not reliable.”

Domain 3:312

Answer 12

“Not reliable” describes data from studies in which there are interferences between the measuring system and the test substance or in which organisms/test systems were used that are not relevant in relation to the exposure or that were carried out or generated according to a method that is not acceptable, the documentation of which is not sufficient for an assessment, and which is not convincing for an expert judgment.

Question 13

Define the Kliimisch score “not assignable.”

Domain 3:313

Answer 13

“Not assignable” describes data that do not give sufficient experimental details and are only listed in short abstracts or secondary literature.

Question 14

What question(s) should be asked when evaluating a resource for “timeliness”?

Domain 3:314

Answer 14

Was the resource published recently enough to be relevant to my topic?

Question 15

What question(s) should be asked when evaluating a resource for “authority”?

Domain 3:315

Answer 15

Does the information come from an author or organization with authority to speak on my topic? Is the information peer-reviewed? Are credentials cited?

Question 16

What question(s) should be asked when evaluating a resource for “audience”?

Domain 3:316

Answer 16

Who are the intended readers and what is the publication’s purpose?

Question 17

What question(s) should be asked when evaluating a resource for “relevance”?

Domain 3:317

Answer 17

Does this article relate to my topic? What connection can be made between the information that is presented and my thesis or topic?

Question 18

What question(s) should be asked when evaluating a resource for “perspective”?

Domain 3:318

Answer 18

Is the resource biased? If so, can I identify resources that help me understand the other side of the argument as well?

Question 19

Define “data management.”

Domain 3:319

Answer 19

Data management is an administrative process that includes acquiring, validating, storing, protecting, and processing required data to ensure the accessibility, reliability, and timeliness of the data for users.

Question 20

What are the four key components of an effective product stewardship measures program?

Domain 3:320

Answer 20

1. Clearly defined objectives
2. Carefully selected measures targeted to the objectives
3. Efficient and reliable data collection process that collects information at appropriate intervials
4. Reporting and communications that summarize product stewardship performance and business value in a transparent and useful manner for business leadership/other audiences.

Full business value p. 57

Question 21

What are the key elements of product stewardship?

Domain 3:321

Answer 21

Protecting workers, customers, end users, and the environment.
Ensuring regulatory compliance.
Fulfilling external commitments.
Meeting market and business expectations.

Full business value p. 57

Question 22

What is the importance of “Product Stewardship Metrics”?

Domain 3:322

Answer 22

Metrics are important to track the health of the management system and, more importantly, to identify areas to continuously improve the overall system. The key is to identify the appropriate metrics that will meet the end goal.

Prof practices p. 383

Question 23

What are the three complications with benchmarking?

Domain 3:323

Answer 23

1. Difficulty identifying true peers
2. Difficulty establishing shared data between competitors
   3., Managing legal concerns

Full business value p. 70

Question 24

What are some important considerations when planning for data storage?

Domain 3:324

Answer 24

1. Protecting proprietary information/appropriate levels of access
2. Accessibility by all team members who need the data (regardless of geography or business unit)
3. Single source of truth for key information
4. Adequate resources to maintain the data on a regular basis (data-cleansing activities)
5. Regulatory record retention requirements (and the associated volume of data that must be stored)

Question 25

What are the seven principles of the EU General Data Protection Regulation (GDPR)?

Domain 3:325

Answer 25

1. Lawfulness, fairness, and transparency
2. Purpose limitation
3. Data minimization
4. Accuracy
5. Storage limitation
6. Integrity and confidentiality (security)
7. Accountability