Slide 1

GOVERNANCE

HISTORY/CONTEXT

VIRTUAL WAREHOUSING

Application

META-DATA

Capture

Information

Raw Data

Elements of Data Capture and Management

•Meta data:

–Provision of well-documented data environment

•Virtual warehousing:

–Supports access to data environment and forum for collaboration

•History/context:

–Objectives of data assembly

•Governance:

–Rules under which data environment can be accessed and procedures for resolving disputes

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Data Environment


	Next we will look at the elements of data capture and management. The orange globe represents data environment consisting of high quality data.

	The value of high-quality data is limited if it is not well documented, if there is no supporting meta data, if data users have to spend time and resources figuring out the content and structure of the data environment. So a key element is the provision of a well documented data environment.

	Next we need a mechanism to access the data, to allow data users to collaborate with each other, and to get their questions answered. The intent here is not to build a giant, federal database. We will try to identify the most logical way of supplying data that meets specific needs. One approach is to have individual streams of data maintained by those who capture the data, and then use virtual warehousing techniques to combine data from multiple locations on the fly to serve particular applications or researchers.

	Next we need the history or context of data capture. Why was the data collected?

	Finally, like all good data environments we need to have a governing structure, the rules of engagement. Who can put data in? Who can use it? What are the rights and responsibilities of the data contributors and the data users? The rules might change from one data environment to another.