Data Bearings: A semantic approach to Enterprise Information Integration

1. DataBearings: A Semantic Approach to
Enterprise Information Integration
Artem Katasonov
VTT Technical Research Centre of Finland
Business Needs
• Companies have increasing number of own databases as
well as external data sources (business partners, Open
data).
• Companies want to exploit ever-growing and diverse data
efficiently and dynamically for new and better services.
• In the market, there is a great need for novel applications
and better capability to provide novel services to customers
in order to differentiate and compete.
• Companies are looking for low cost and easy to install data
management solutions.
Solution
DataBearings enables on-the-fly, i.e. at a user request time,
integration of data from distributed heterogeneous sources:
databases, Web services, sensor feeds.
DataBearings manages data virtualization, federation, and
abstraction, as well as allows organizing data processing
pipelines. It also supports federated data updates (writes).
DataBearings reduces integration costs by allowing leveraging
existing data sources in new ways, while also allowing access
to “live” data.
DataBearings is based on unique capabilities of Semantic
Agent Programming Language (S-APL).
DataBearings has the competitive edge of being more
lightweight and cheaper than commercial Enterprise
Information Integration solutions, allowing faster
implementation of data integration systems, enabling better
extensibility – to support later N+1th data source or M+1th data
processing case, as well as providing a richer features set than
any comparable solution.
DataBearings is a relatively mature platform, yet in continuous
evolution.
DataBearings has been applied in a several operational data
integration systems of Finnpark Ltd (on the right).
HTTP GET
Figure 1. Semantic data virtualization and federation in DataBearings
A DataBearing supplies data to CarP:
• Integrates static (manually-managed)
data and dynamic data (from sensing
systems).
• Integrates data from different Finnish
cities (different systems in use for
static and dynamic data).
Contacts
Artem Katasonov
Tel. +358 40 1976669
artem.katasonov@vtt.fi
Engine
Jani Mäntyjärvi
Tel. +358 40 5191361
jani.mantyjarvi@vtt.fi
SQL plugin
SOAP plugin
XML plugin
JSON plugin
…
Universal adapter
Business case logic
Semantic
Query
Semantic
Data
Data source
annotations
SQL
SOAP
HTTP GET
Data
Scripts
Annota-tions
Reusable Atomic Behaviors
Currently, SPoT is a single data
source service (video-based plate
recognition in car parks).
A DataBearing will extend SPoT:
• Integrate the currently used data
with street parking data from
various sources.
A DataBearing supplies data to
“Street Parking Enforcement” mobile
application:
• Integrates data from various
payment providers – currently
mobile payment services
(Easypark, Parkman), later also
‘pay and display’ machines.
Figure 2.
DataBearings
general
architecture
Marjaana Komi
Tel. +358 40 5321637
marjaana.komi@vtt.fi