This research is focused on developing effective visualization tools for query construction and advanced exploration of temporal relational databases. Temporal databases enable the retrieval of each of the states observed in the past and even planned future states. Several query languages for relational databases have been introduced, but only a few of them deal with temporal databases. Moreover, most users are not highly skilled in query formulation and hence are not able to define complex queries. The visual approach introduced here aims at simplifying the query construction process, It gives the user the option to define complex temporal constructs and provides visual tools with which to explore the returned networks intuitively. The exploration process should provide better insight into networks of entities, reveal patterns between the entities, and enable the user to forecast the behavior of entities in the future. A visual query language as an isolated subsystem is not sufficient in itself for a complete data analysis process. A query's output should be further explored to find patterns that are hidden in the output.