In this module, you will be able to compare forms of communication and describe why people us ontologies to describe the world. You'll be able to describe the evolution of standardized railroads in the US and recognize why the evolution of railroad tracks also applies to medical terminologies. You'll be able to analyze a dataset with disease codes and also be able to select which codes refer to specific diseases. You'll be able to match different terminologies with different descriptive domains as well as be able to contrast the different ways of organizing information into hierarchies or other categories.

In this module, you will be able to identify different types of medical processes and be able to explain why specific data formats emerged from these varied processes. You'll be able to list numerous data types that are found within EHRs and link specific clinical processes that created these outputs. You'll be able to trace why various types of administrative data are collected and describe the value of this data for analytics. You'll be able to identify the common ways that gene sequences are stored in computer readable files and be able to describe how big data formats are different than common relational database technologies that require a lot of data modeling and planning.

In this module, you will be able to tell leaders and coworkers why they should invest time in creating data dictionaries and other meta-data. You'll be able to describe why one burn registry had data fragmentation issues, and how a variety of standardization and centralization processes helped to achieve data harmony. You'll be able to answer why it is necessary to integrate data, even though the data is coming from disparate sources. You'll be able to perform data mapping as well as communicate the technical terms used to describe and perform record linkages.