Each time data is queried from the Data Tunnel, a schema of the data (also in JSON format) is returned together with the data. This schema explains the data structure for the data consumer (e.g. application developers). With the schema, all data output can be predicted, enabling developers to create dynamic layers that support all datasets published through the AllianceBlock data tunnel. Furthermore, combined with ABQL, developers are able to create dynamic queries that are generated on the fly so that all data can be analyzed without human interference.
Furthermore, queries that alter the output of the data (aggregations, different column names, etc.) will come with an automatically generated schema that fits the output of that query, so that that output can be automatically queried once more using ABQL.
Ultimately, ABQL combined with the generated JSON data schemes, will help drive adoption of decentralized access to datasets.
The output data is separated into two parts: the schema that describes the data, and the data itself. Here we can see the aggregated amount of LP tokens staked in a pool (done through ABQL). ABQL is great for blockchain analysis too!
Click here to read more about the Data Tunnel on Medium.