Periodic events seem to be an intrinsic part of our life, and a way of perceiving reality. There are many application domains where periodic data play a major role. In many of such domains, the huge number of repetitions make the goal of explicitly storing and accessing such data very challenging to the extent of even not being possible, in cases of open ended intervals. In this work, we present a concept to represent periodic data in an implicit way. The representation model we propose captures the notion of periodic granularity provided by the temporal database glossary. We define the algebraic operators, and introduce access algorithms to cope with them and also with temporal range queries, proving that they are correct and complete with respect to the traditional explicit approach. In an experimental evaluation we show the advantages of our approach with respect to traditional explicit approach, in terms of space usage, physical disk I/O's and query response time.