How are data for a Production Record Data Model stored

storing data based on id relations to be able to store production event records, users have to create a data model first as described by the chapter core concept behind recording production record data via data model docid\ ffsctesqgb9gj7wy5kymo , the model represents a hierarchy structure with a lot of variability every data model, which in eav terms equals an entity, is defined by a unique name called a nodename inside litmus production record database, which will get its own distinct id assigned in the example below, the nodename is line x all further definitions for this hierarchy such as the sub levels ( station a and station b ) as well as all items (purple boxes) are in eav terms attributes the relation between an entity and an attribute is created by forming a relation between the respective id of the entity and the id's of an attribute data are later recorded just with the reference to their respective attribute production record unique relation and identifiers in most use cases for an eav data model like patient records recording observations data are stored directly against an entity itself as events recorded by litmus production record database are not observed only one time but on a reoccurring basis, it is necessary to create basically an index of each event litmus production record database does solve this through the concept of a production record id or prorecid for short a prorecid is a unique index for a specific event recorded for a specific data model this does allow users to retrieve the data recorded for a specific data model for a specific event as this does require to know the prorecid and users typically do not know a specific prorecid, litmus production record database makes use of identifiers identifiers are up to five attributes, which in their unique combination describe a specific prorecid these identifiers should be chosen based on how an organization refers to these events on a day to day basis, as it then allows their natural understanding to retrieve the data below are some possible examples for what identifiers could be bulk batch tracking identifiers saplotnumber productnumber ordernumber step monitoring identifiers asset programnumber starttime individual parts tracking identifiers serialnumber productnumber line for more examples, please go to the chapter litmus production record database use cases docid\ ew5koajvqbxx bzau7p6 users are therefore able to retrieve event data by searching for the event id which correlates with the value recorded for the identifiers for the desired data model example is shown by the chapters reading production record event data with local timestamp docid\ pfw2g0s705ff3qcouhpys reading production record event data with utc timestamp docid\ zmrhs1q1rgiydzat6wf2z