Concepts
Discovery Space¶
ado is a tool for systematically exploring, measuring, and analysing a space of entities - for example, configurations, systems and substances. The core concept enabling this is a Discovery Space. It answers three questions:
- How are measurements performed? A Discovery Space defines a set of Experiments. Each Experiment takes defined inputs and produces measured outputs. The collection of Experiments is called a Measurement Space.
- What do you want to measure? A Discovery Space defines an Entity Space — the specific set of things, called Entities, you want to measure.
- What have you measured so far? A Discovery Space uses a Sample Store, a shared database, to read and store measurement results.
For users familiar with pandas, a Discovery Space is like a DataFrame that knows its own schema, knows how to fill in missing values, and shares data transparently with other DataFrames. See Discovery Spaces for more.
Sample Store¶
In ado, Entities and the results of Experiments on them are kept in a Sample Store — a shared database that multiple Discovery Spaces can use.
If an Experiment has already been run on an Entity, ado can reuse the result rather than running it again. This transparent data sharing is a core feature of ado. See Shared Sample Stores for more details.