Assessing data you found
<img src="https://i.imgur.com/KKsIx5Y.gif" width="500" height="300" alt="Data">
Follow through these considerations:
[[The format is usable as is]]
[[The format is not usable]]There are two primary types of spatial data models: vector and raster.
Vector represents discrete features like points, lines, and polygons. Raster represents a continuous phenomenon and stores the information in a matrix of cells (pixels).
Next, **Coordinate System**
[[The data have defined coordinate system]]
[[The data's coordinate system is unknown]][[The format can be converted->The format is usable as is]]
[[The format can't be converted]]<img src="https://media0.giphy.com/media/3orifeRIO7aSrLP3Py/source.gif" width="500" height="300">A geographic coordinate system (GCS) defines *where* something is located on the Earth's round surface. A projected coordinate system (PCS) calculates *how* something is placed on a 2D plane.
Did you obtain the data from an **authoritative/reliable source**?
[[Yes, the data are from an authoritative source]]
[[No, the origins are sketchy]]Check the metadata or any supplementary materials that might help you determine the coordinate system. Can you define it then?
[[Yes, I can now define the coordinate system ->The data have defined coordinate system]]
[[No, the coordinate system remains elusive]]The term "authoritative spatial data"" traces back to land surveyors, who professionally certify the accuracy of the data. Today, we refer to authoritative data as datasets provided by organizations (government, academia, NGOs...etc.) that adhere to set standards on acquisition, quality, transformation, and provide the data for the purposes of extensive use.
When you look closely at the data, does it have all the **attribute information you need**?
[[Yes, all the relevant attributes are included]]
[[Some attributes I need are missing]]<img src="https://i.imgur.com/YLsUyL4.gif" width="500" height="300"><img src="https://i.gifer.com/AL3k.gif" width="500" height="300">Attribute information are nonspatial information about a geographic feature. For example, a restaurant (represented as a point) can have attributes such as name, type of cuisine, whether it is dog-friendly.
Now we need more information about our information - **metadata**
[[The dataset has sufficient metadata]]
[[The metadata is sparse->No, the origins are sketchy]][[Each feature has an unique identifier that I can match the necessary information from another dataset->The dataset has sufficient metadata]]
[[I can't join the data with another dataset->The format can't be converted]] Metadata is data about data. Important metadata components to consider for spatial data are: citation, quality, lineage/maintenance, spatial reference, extent (temporal and geographic), content (such as describing each attribute field or provide details on coded values), and use/distribution.
This segways to the last few considerations: **appropriate scale**, **up-to-date**, and **permission to use**
[[Yes to all]]
[[If no to one or more]]<img src="https://media3.giphy.com/media/3o6nVcaclb9jZueZck/giphy.gif" width="500" height="300"><img src="https://media0.giphy.com/media/l2YWxte7sJB2XuE8M/giphy.gif" width="500" height="300">