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The role of governance has been described both as a function (Chapter 3) and in relation to each Knowledge Area

Data is both an interpretation of the objects it represents and an object that must be interpreted (Sebastian-Coleman, 2013).

Data is both an interpretation of the objects it represents and an object that must be interpreted (Sebastian-Coleman, 2013). This is another way of saying that we need context for data to be meaningful.

Often a layered pyramid is used to describe the relationship between data (at the base), information, knowledge, and wisdom (at the very top).

While the pyramid can be helpful in describing why data needs to be well-managed, this representation presents several challenges for data management.

It is based on the assumption that data simply exists. But data does not simply exist. Data has to be created.
By describing a linear sequence from data through wisdom, it fails to recognize that it takes knowledge to create data in the first place.
It implies that data and information are separate things, when in reality, the two concepts are intertwined with and dependent on each other. Data is a form of information and information is a form of data.

value of data can and should be expressed in economic terms: Calling data an asset implies that it has value. While there are techniques for measuring data’s qualitative and quantitative value, there are not yet standards for doing so. Organizations that want to make better decisions about their data should develop consistent ways to quantify that value. They should also measure both the costs of low quality data and the benefits of high quality data.

Managing data means managing the quality of data: Ensuring that data is fit for purpose is a primary goal of data management.

Ensuring that data is of high quality is central to data management.