1. Define, discuss and give examples of data, information and knowledge. Have students generate their own examples.
2. Discuss how computer scientists and informaticians differ, in terms of their approach and goals.
3. Discuss the conceptual and computational models and now they relate to data. Also, define semantics and interoperability.
4. Discuss clinical data warehouses and why they are important in healthcare. Compare and contrast structured and unstructured data.
5. Discuss natural language and natural language processing (NLP). Discuss biomedical concept extraction.
6. Enumerate the factors that contribute to the difference and level of complexity, such as incomplete, uncertain, imprecise, vague and inconsistent information.