This project contains the implementation for the DBC Smart Indexing Engine (DBC-SIE).
DataBlockChain.io utilizes an open source Smart Indexing Engine (SIE) to index all data sources and assign confidence scores on the sources. The SIE constantly checks and reevaluates the sources updating the scores.
The SIE uses predictive analytics to create an appropriate score. The AI in the SIE quantifies each of the discrete values to build an evolving quantitative analysis. Through sample population validation a qualitative component is built to accompany the quantitative analysis. The SIE periodically runs performance evaluations and uses past performance modifiers to learn and adjust the score.
The scoring algorithm takes into account the speed of the data source, the age of the data, the amount of data available, the quality of the data based on source metrics, the attributes available, coherence with other data sources, and validation of a sample population.
The data sources with higher scores receive preferential treatments as long as query parameters are observed.
The SIE connects to data sources using smart blockchain oracles called DBCOracles (based on Oraclize).
Smart Contracts generated by DataBlockChain.io contain the signatures of the DBCOracle for full traceability.