KEES™ ( Knowledge Exchange Engine Services ) is a service architecture for Master Data Management (MDA), Data Federation e Data Cleansing.
KEES™ is the result of over three years of research carried out in our laboratories on semantic technologies and is entirely based on the standards promoted by the W3C.
Please download the KEES presentation.
For an implementation of KEES architecture have a look to our LinkedData.Center service.
Data technologies are evolving rapidly, but organizations have adopted most of these in piecemeal fashion. As a result, enterprise data—whether related to customer interactions, business performance, computer notifications, or external events in the business environment —is vastly underutilized.
Moreover, companies’ data ecosystems have become complex and littered with data silos. This makes the data more difficult to access, which in turn limits the value that organizations can get out of it. Beside this a vast amount of open data is now already available in the web.
To unlock the value hidden in all accessible data, companies must start treating data as a supply chain, enabling it to flow easily and usefully through the entire organization—and eventually throughout each company’s ecosystem of partners, including suppliers, customers, government, open data and specialized data providers.
In such scenario, companies must manage technological threads (i.e. big data) and data quality issues. Information captured from a plurality of sources could easily contains duplication, inconsistencies and errors. The data meaning need to be harmonized in order to make data fully integrable.
We need a service architecture for data integration, data federation and data cleansing
We need a new system that is able to recognize the "concepts" that are behind a data model and that is able to map these concepts to different data models. This means to operate choices among data when some inconsistency arises.
These issues are already covereded by Semantic Web Standards, so we just need to rationalize and to specialize an already existing and proved architecture.
KEES is a service architecture for data ecosystems based on Semantic Web and Linked Data principles.
KEES can be used to realize services in following applicative domains:
- data ingestion
- data semantic
- knowledge consolidation
- data integration
- data federation
- data cleansing
KEES is fully agnostic about business domains