Storing historical data is not new. Data warehouses are filled with it. However, querying temporal data has only, in the past few years, become a realistic possibility.Yet the SQL standard has not had significant updates in temporal data support since 1992. The demands of the modern world are no longer satisfied by decades-old solutions. MySQL, an open-source database extremely popular in the sciences, has still not yet fully implemented SQL-92. Its approach to temporal needs is lacking. Too many queries are not answerable, and those that are answerable are often answered inconsistently.
As the volume of scientific data increases, the need for automated data provenance has expanded. Currently, several provenance systems exist to aid users in recording and querying provenance data. They range from very specific programs designed to accomplish a small number of clearly defined tasks to broad-range applications intended to appeal to a wider audience. This paper discusses several provenance systems and describes some areas for future study.
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