Source Configuration

Owned by Craig Vitter (Unlicensed)
Last updated: Apr 10, 2015 by andrew johnston (Unlicensed)
2 min read

Overview of the Data Harvesting Process

The Community Edition (CE) platform features a robust set of data harvesters that give it powerful data extraction and transformation (enrichment) capabilities. CE's harvesters are designed to consume data from a variety of sources and media types including:

  • Web based content accessible via URL including:
    • Static HTML content;
    • RSS and ATOM based news feeds;
    • Restful web services interfaces.
  • Traditional relational database management systems (RDBMS) via Java Database Connectivity (JDBC) drivers;
  • Files located on local and network attached storage devices.

Source Pipeline

Harvesting and enrichment is a logical process based around the concept of applying a pipeline of processing elements to documents emanating from a source.

The following high level steps are applied to the source data, although there is considerable flexibility in the order of pipeline elements.

The pipeline elements can be approximately grouped into the following categories:

  • Extractors: Generate mostly empty CE documents from external data sources.
  • Globals: Generate javascript artifacts that can be used by subsequent pipeline elements.
  • Secondary extractors: Enables new documents to be spawned from the existing metadata.
  • Text extraction: Manipulation of the raw document content.
  • Metadata: Generate document metadata such as title, description, date; and arbitrary content metadata using xpath, regex, and javascript
  • Entities and associations: Create entities and associations out of the text.
  • Storage and indexing: Decide which documents to keep, what fields to keep, and what to "full text index" (for searching using the GUI/API).

Creating a Source

The following WIKI pages describe the source creation steps:

  1. Extractors
    How to specify the mechanics required to extract data from a source system:
    1. File extractor
    2. Feed extractor
    3. Web extractor
    4. Database extractor
  2. Entities and associations
    An introduction to the Structured Analysis Harvester and how to specify the methods for enriching structured data sources with geographic information, entities, and events.
    1. Specifying Document Level Geographical Location
    2. Manual entities
    3. Manual association of entities
    4. Javascript globals
    5. Transforming data with JavaScript
  3. Metadata
    1. Document metadata
    2. Content metadata

A simple web-based GUI is available in conjunction with the structures described in these pages.

Source Reference Documents

Source Document Specification

The following links provide detailed information regarding the objects that make up a Source document and the individual fields within each object.

Source Pipeline Documentation

Sample Source Documents

The following sample source documents are provided as an aid to learning how to create your own sources:

Source APIs:

In this section: