Dear Michael G Michael U and Nicola,
I was reading this section on integration during
the call last night, and it did not ring true to me, but I
was struggling to put my finger on what I thought the
problem was:
In
this class of applications, the primary functionality is the
matching and mapping of concepts, while the primary
architecture is within a set of multiple systems. Ontologies
are typically used at runtime by application developers (who
are in the best position to write translators among the
systems). (2PQO)
- information
integration Multiple
information resources are combined using ontologies at
runtime to match concepts with similar meaning. (2OM2)
Examples:
web service composition, mashups, information aggregation,
data fusion, linked data (2PQP)
- database
integration Queries that
require multiple databases are specified using common
ontologies and data schema are matched using these
ontologies at runtime.
After a troubled night’s sleep, I think I have a
better idea.
In industry, when people talk about integration,
they mean what it takes to turn a bunch of separate
information systems into a single coherent system of
systems. There are typically 4 types of integration with
different characteristics:
1. Core Process Integration: An enterprise will have at least one and maybe
several core processes. These are the processes the
execution of which are the purpose of the enterprise. In
business they are often around the provision of goods or
services to customers. These core processes are supported by
information systems, and information needs to pass between
them in order to efficiently perform the overall process,
integrating the disparate systems involved. A key part of
this will include Master Data Management so that all the
systems use the same identification for key things like
products and customers.
2. Lifecycle Integration: There will be a number of things needed
to support the core processes, such as factories and
vehicles, each of which has a lifecycle that needs to be
integrated. Particularly with large and long lived assets
like factories and ships, information needs to be passed
between lifecycle stages (e.g. design to construction,
design and construction to operations, etc) and between the
information systems that support the different processes in
those different stages.
3. Supply Chain Integration: When enterprises procure goods in particular,
but also services, they do not just capture price
information, part of the product will be information about
it, and its use. This information needs to be integrated
within the systems that are involved with the operation and
use of those products.
4. Business Intelligence (Performance Management): To understand how well an enterprise is
performing its processes you need to be able to analyse the
data that arises from the performance of its processes. This
usually involves collecting and integrating the data from
multiple systems, and populating star or snowflake schemas
so that for example sales can be analysed by customer type,
by product type, by geographic region, by volume, by value,
by profitability etc.
I’m afraid I did not get a any sense of this from
the description above.
The other thing that was implicit was that data
resides in one system and is queried from there (single
source of truth). This is actually extremely unusual. Much
more common is managed replication, for reasons of both
performance and resilience. Take the business intelligence
type of integration above. The source data is typically in
one or more Transaction Processing systems, where there are
no indices because when you create records, building the
indices are what hits performance. So to perform the
queries, not only do you need to do joins across the
transaction data and the master data, but most queries will
require a table scan. This of course will not only affect
the performance of the query, but the TP system as well. So
a copy of the TP data is made at regular intervals and it is
combined with the Master Data into massively denormalized
tables that have indices on most columns. Performance is
transformed.
There are in fact a variety of architectures
possible for achieving data integration, which is suitable
will depend on the circumstances. This paper of mine from
1998 outlines some of the possible approaches.
http://www.matthew-west.org.uk/documents/TheRoleOfEnterpriseModelsInIntegration.PDF
Regards
Matthew
West
Information
Junction
Tel: +44
1489 880185
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