the data. Each generated attribute value preferably depends upon the existing value for a particular attribute (which may be null or zero if no “relevant” data has previously been received—where “relevant” here means both that it pertains to the attribute in question and pertains to the time period covered at least partially by the summary bin in question) as well as the received data.
Preferably, the content of each bin is updated from time-to-time (e.g. on a periodic basis or, more preferably on an event driven basis such as whenever a new event which will have an effect on the content of at least one bin is detected—refinements on this may include buffering a predetermined number of events (or the events occurring—or commencing or ending—within a predetermined period of time) and then performing an update based on the contents of the buffer when the buffer is read at a predetermined time (e.g. because the buffer period of time has expired or the buffer is full or has reached a trigger capacity, etc.). When an update is performed it is preferable if all of the bins are also updated at that time. Updating the bins preferably includes ascertaining a portion of one or more bins to be transferred to one or more other bins as well as ascertaining the additional new contents to be added to new bins based on newly detected events/acquired data. In some embodiments, updating bins may additionally involve ascertaining the proportion of the contents of one or more old bins to now be discarded as a result of the contents being associated with data/events which are now so old as to not be relevant to any of the stored bins.
Preferably, transferring some portion of the contents of one bin into another is just a matter of transferring the complete contents from a bin of one scale to a bin of another larger scale/coarser granularity (or possibly sharing the contents of one bin between two adjacent and overlapping coarser grain bins). Alternatively, each time a new event is recorded, the time period with which 