It sounds a bit like multiple concrete expressions of a meta model though. Where the potential set of values is your hX and tX is expressed in your concrete data.
So you have multiple dimensions (one of which is time) which are then expressed in concrete data. On Sun, Aug 10, 2014 at 11:20 PM, Alireza Rezaei Mahdiraji < [email protected]> wrote: > > Hi All, > > I saw documentation about how to model time series in graph but my problem > seems > does not fall into that meta models. > > Here is a description: I have a graph with a fixed connectivity, however > based on variable > let say h with values <h1,h2,..hn> some of internal properties of the > graph nodes changes, i.e. > for h=h1 a node have value x1 for property x but for h=h2 the value of x > for the node is x2. > > Moreover, there are other data (properties in graph terminology) for > nodes which are > based on time, i.e., I have a set of timestamps t=<t1,t2,t3, ...,tn> and > for each > timestamp and for each value of h, each node have one or a vector of data. > > This nested data structure seems very hard to model with graph. Does > anybody has > ideas on how to model this? > > Thanks, > Best, > Alireza > > > -- > You received this message because you are subscribed to the Google Groups > "Neo4j" group. > To unsubscribe from this group and stop receiving emails from it, send an > email to [email protected]. > For more options, visit https://groups.google.com/d/optout. > -- You received this message because you are subscribed to the Google Groups "Neo4j" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
