Data Source Validity and Verification

Vocabulary flashcards covering data source validity, the five pillars of data verification, four validity lenses, diagnostic matrix indicators, and the five-step evaluation protocol.

Data Source Validity

The level of accuracy and reliability of data, representing its ability to describe actual conditions as a foundation for trustworthy information.

Accurate (Data Verification Pillar)

The property of data being true, error-free, reflecting actual facts, and free from misleading information.

Actual (Data Verification Pillar)

The requirement that data represents current conditions rather than using outdated or obsolete information.

Source Credibility (Data Verification Pillar)

The degree of trust placed in the origin of information, such as official institutions (BPS, Kemendikbud, BRIN) or scientific journals.

Relevance (Data Verification Pillar)

The requirement that data directly aligns with the specific purpose, goal, or problem being analyzed.

Reliability (Data Verification Pillar)

The property of data being consistent and dependable, producing identical results when retested multiple times.

Internal Validity

A type of validity testing that proves a true cause-and-effect relationship exists between variables without interference from confounding factors.

External Validity

A type of validity testing showing that research findings can be applied or generalized to a broader context or population.

Construct Validity

A type of validity testing that assesses whether an instrument truly measures the intended theoretical concept.

Content Validity

A type of validity testing that evaluates whether all relevant dimensions or aspects of a concept are fully covered by the measurement tool.

Job Satisfaction Questionnaire (Content Validity Example)

An assessment tool that must include all four specified elements: salary, work environment, coworkers, and career development.

Step 1: Identify Source (Verification Protocol)

The evaluation step aimed at verifying the origin of the data, which relates to Source Credibility.

Step 2: Analyze Method (Verification Protocol)

The evaluation step that examines the data collection procedures used.

Step 3: Check Quality (Verification Protocol)

The evaluation step that tests the facts and precision of the information, which relates to Accuracy.

Step 4: Evaluate Date (Verification Protocol)

The evaluation step that verifies the publication timestamp of the data, which relates to Actualness.

Step 5: Compare (Verification Protocol)

The evaluation step involving cross-referencing information with other trusted sources, which relates to Reliability.