Semantic Search and Visualization of Time-Series Data

In the economic and financial analysis domain, quick access to the right information plays a major role. Using current systems, the search for and presentation of data is very cumbersome. The data, mostly in form of time-series, is stored in various databases. In order to retrieve the searched data, the analysts need to know where to search and sometimes even the structure of the database and its coding. Then it is required to export the data, process the data and create a chart to view the data. This might take time from tens of minutes to hours. In our work we present a first prototype of an integrated search engine that takes as input a natural language query and offers graphic and text output depending on the user task. The system automatically identifies the resulting time-series and types of graphical data presentation, and shows the results in a web browser or in Excel. The knowledge based expert system uses domain ontologies for extraction of economic terms in the search queries and specially built data type taxonomies with user task and chart type ontologies for the identification of graphical output.