Question

I have an application that receives a number of datums that characterize 3 dimensional spatial and temporal processes. It then filters these datums and creates actions which are then sent to processes that perform the actions. Rinse and repeat.

At present, I have a collection of custom filters that perform a lot of complicated spatial/temporal calculations.

Many times as I discuss my system to individuals in my company, they ask if I’m using a rules engine.

I have yet to find a rules engine that is able to reason well temporally and spatially. (Things like: When are two 3D entities ever close? Is 3D entity A ever contained in 3D region B? If entity C is near entity D but oriented backwards relative to C then perform action D.)

I have looked at Drools, Cyc, Jess in the past (say 3-4 years ago). It’s time to re-examine the state of the art. Any suggestions? Any standards that you know of that support this kind of reasoning? Any defacto standards? Any applications?

Thanks!

Answer 1

Premise – remember that a SQL-based¹ DBMS is a (quite capable) inference engine, as can be seen from these comparisons between SQL and Prolog:

• prolog to SQL converter
• difference between SQL and Prolog

To address specifically your spatio-temporal applications, this book will help:

• TEMPORAL DATA AND THE RELATIONAL MODEL – A Detailed Investigation into
  the Application of Interval and Relation Theory to the Problem of Temporal Database Management.

That is, combining Interval and Relation Theory is possible to reasoning about spatio-temporal problems effectively (see 5.2 Applications of Intervals).

Of course, if your SQL-based DBMS is not (yet) equipped with interval (and other) operators you will need to extend it appropriately (via store-procedures and/or User-Defined Functions – UDFs).

Update: skimming the paper pointed out in comments by timemirror (Towards a 3D Spatial Query Language for Building Information Models) they do essentially what I touched on above:

(last page)

IMPLEMENTATION CONCEPTS

The implementation of the abstract
type system into a query language will
be performed on the basis of the query
language SQL, which is a widely
established standard in the field of
object-relational databases. The
international standard SQL:1999
extends the relational model to
include object-oriented aspects, such
as the possibility to define complex
abstract data types with integrated
methods.

I do not concur with the “object-relational database” terminology (for reason off-topic here) but I think the rest is pertinent.

Update: a quote regardind 3D and interval theory from the book cited above:

NOTE: All of the intervals discussed
so far can be thought of as
one-dimensional. However, we might
want to combine two one-dimensional
intervals to form a twodimensional
interval. For example, a rectangular
plot of ground might be thought of as
a two-dimensional interval, because it
is, by definition, an object with
length and width, each of which is
basically a one-dimensional interval
measured along some axis. And, of
course, we can extend this idea to any
number of dimensions. For example, a
(rather simple!) building might be
regarded as a three-dimensional
interval: It is an object with length,
width, and height, or in other words a
cuboid. (More realistically, a
building might be regarded as a set of
several such cuboids that overlap in
various ways.) And so on. In what
follows, however, we will restrict our
attention to one-dimensional intervals
specifically, barring explicit
statements to the contrary, and we
will omit the “one-dimensional”
qualifier for simplicity.

Note

1. I wrote SQL-based and not relational because there are ways to use such DBMSes that completely deviate from relational theory.