# (2) From Metadata to Missing Data
###### tags: `session-3-chunkified`

* While we may have missing metadata, there is even another category of things that are missing: **missing data**.
* These are topics and issues that we may not realize exist because:
* there a few (if any) known datasets about them; or
* they are rarely mapped

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Artist Mimi Onuoha has compiled her thoughts on missing data which you can read [here](https://github.com/MimiOnuoha/missing-datasets). She outlines a few reasons why data are missing, including
> 1. Those who have the resources to collect data lack the incentive to (corollary: often those who have access to a dataset are the same ones who have the ability to remove, hide, or obscure it)
> 2. The data to be collected resist simple quantification (corollary: we prioritize collecting things that fit our modes of collection).
> 3. The act of collection involves more work than the benefit the presence of the data is perceived to give.
> 4. There are advantages to nonexistence.

Does this list make you think of any recurring themes we've discussed in this class? Can you think of an example of a missing dataset?

</aside>

* **Just because the data doesn't exist to map it, doesn't mean it isn't real.** Centuries of societal norms and thought practice have built up into what is mapped and what isn't.
* Sometimes there are strategic reasons for missing data such as privacy and safety of those being counted.
* But we hope this course empowers you to identify what isn't being mapped, identify *why*, and then figure out what you can do about it!

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While we may have missing metadata and lacking data transparency, there is even another category of things that are missing - missing data. These are topics and issues that there are very little to zero known datasets about and people thus far have rarely mapped them. Artist Mimi Onuoha has compiled her thoughts on missing data which you can read [here](https://github.com/MimiOnuoha/missing-datasets). She writes the following:
> "Missing data sets" are my term for the blank spots that exist in spaces that are otherwise data-saturated. My interest in them stems from the observation that within many spaces where large amounts of data are collected, there are often empty spaces where no data live. Unsurprisingly, this lack of data typically correlates with issues affecting those who are most vulnerable in that context.

Essentially: Data do not show us a complete picture of the world. Increasingly the concept of "missing data" has been embraced by academics and practitioners to acknowledge that there will always be missing information in even the best datasets.

This suggests that while data gives us the power to see things and bring to light new issues, just because the data doesn't exist doesn't mean it isn't real. Centuries of societal norms and thought practice have built up into what is mapped and what isn't. We hope this course empowers you to identify what isn't being mapped and what you can do about it! However, sometimes there are strategic reasons for missing data such as privacy and safety of those being counted.

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