Data bearings, Artem Katasonov
1
DataBearings: A Semantic Approach to Enterprise Information Integration Artem Katasonov VTT Technical Research Centre of Finland 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). Figure 1. Semantic data virtualization and federation in DataBearings Contacts Artem Katasonov Tel. +358 40 1976669 [email protected] Jani Mäntyjärvi Tel. +358 40 5191361 [email protected] SQL plugin SOAP plugin XML plugin JSON plugin … Universal adapter Business case logic Semantic Query Semantic Data Data source annotations SQL SOAP HTTP GET HTTP GET 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. Data Scripts Annota- tions Reusable Atomic Behaviors Engine 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). 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 [email protected]
-
Upload
vtt-technical-research-centre-of-finland -
Category
Data & Analytics
-
view
102 -
download
2
description
Data Bearings: A semantic approach to Enterprise Information Integration
Transcript of Data bearings, Artem Katasonov
DataBearings: A Semantic Approach toEnterprise Information Integration
Artem KatasonovVTT Technical Research Centre of Finland
SolutionDataBearings 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, andabstraction, as well as allows organizing data processingpipelines. It also supports federated data updates (writes).
DataBearings reduces integration costs by allowing leveragingexisting data sources in new ways, while also allowing accessto “live” data.
DataBearings is based on unique capabilities of SemanticAgent Programming Language (S-APL).
DataBearings has the competitive edge of being morelightweight and cheaper than commercial EnterpriseInformation Integration solutions, allowing fasterimplementation of data integration systems, enabling betterextensibility – to support later N+1th data source or M+1th dataprocessing case, as well as providing a richer features set thanany comparable solution.
DataBearings is a relatively mature platform, yet in continuousevolution.
DataBearings has been applied in a several operational dataintegration systems of Finnpark Ltd (on the right).
Figure 1. Semantic data virtualization and federation in DataBearings
ContactsArtem KatasonovTel. +358 40 [email protected]
Jani MäntyjärviTel. +358 40 [email protected]
SQL plugin
SOAP plugin
XML plugin
JSON plugin
…Uni
vers
alad
apte
r
Busin
ess
case
logi
c
SemanticQuery
SemanticData
Data sourceannotations
SQL
SOAP
HTTP GET
HTTP GET
Business Needs• Companies have increasing number of own databases as
well as external data sources (business partners, Opendata).
• Companies want to exploit ever-growing and diverse dataefficiently and dynamically for new and better services.
• In the market, there is a great need for novel applicationsand better capability to provide novel services to customersin order to differentiate and compete.
• Companies are looking for low cost and easy to install datamanagement solutions.
DataScripts
Annota-tions
Reusable Atomic Behaviors
Engine
A DataBearing supplies data to CarP:• Integrates static (manually-managed)
data and dynamic data (from sensingsystems).
• Integrates data from different Finnishcities (different systems in use forstatic and dynamic data).
Currently, SPoT is a single datasource service (video-based platerecognition in car parks).
A DataBearing will extend SPoT:• Integrate the currently used data
with street parking data fromvarious sources.
A DataBearing supplies data to“Street Parking Enforcement” mobileapplication:• Integrates data from various
payment providers – currentlymobile payment services(Easypark, Parkman), later also‘pay and display’ machines.
Figure 2.DataBearingsgeneralarchitecture
Marjaana KomiTel. +358 40 [email protected]
