The usual workflow of a PoolParty GraphSearch project starts with the gathering of structured and unstructured data. You can use data from various sources by using UnifiedViews and/or by transforming documents into RDF by means of the PoolParty Extractor. The processed RDF data is stored in a search index like Apache Solr or Elastic Search or an Enterprise graph database. The PoolParty GraphSearch Server offers a web service API that follows the RESTful principle and produces results in JSON for ‘traditional’ document search applications with additional beneficial features like synonym search and hierarchical drill down based on the knowledge graph that is managed with PoolParty Thesaurus Server.
Using an Enterprise graph database allows in addition to uses special data structures in the data that has to be searched in combination with optimized SPARQL queries in combination with default the document search features. The date can be organized in named graphs to provide a separation of data. By this, you can aggregate and manage large volumes of information like DBpedia, WordNet, Geonames etc. to integrate those into your search and analytics applications.
Since all relevant data can be acquired from the graph database, interactive visualizations or other forms of analytics, like reports can be built using SPARQL queries. Customizing integrated linked knowledge graphs and adapting SPARQL queries allows you to adapt and modify your analysis applications in a very dynamic and agile way. Like you do mashups, you can combine different data sets and formulate queries to retrieve data accordingly to your needs.