Semantic data integration allows enterprises to connect heterogeneous data sources through a common language. This creates a unified 360-degree view of enterprise data and facilitates knowledge management and use. Semantic integration aims to enrich existing data with external knowledge and provide a single access point for enterprise assets. It addresses challenges of accessing and storing data from various internal resources by building a well-structured integrated whole to enhance business processes.
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Semantic data integration is about building and using the right tools
to make your data speak a universal language.
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Thankfully,
just like there is a common language for
the documents on the Web –
the Hypertext Markup Language (HTML),
there is a common language for data.
4. If you are looking for solutions that
allow you not only to manage all
of your data (structured,
semi-structured
and unstructured),
but to also
make the most out
of them, using a common
language is critical.
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5. To bring
heterogeneous data
sources into one
synchronized
360-degree view
of your enterprise data,
you need a type of
integration that uses
Semantic Technology.
4
360º
6. What makes your data speak a universal
language and allows them to connect
with other data through a seamless
exchange across systems are
W3C standards such as IRI, RDF,
OWL and SPARQL.
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IRI
RDF
OWl
SPARQL
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Adding Semantic Technology
to data integration is the glue
that holds together all your enterprise data
and their relationships in a meaningful way.
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The process of such semantic data integration creates an interrelated
information space, which facilitates the management and use of both
the information and the knowledge derived from the data.
9. From a business strategy perspective, the aim of semantic data integration
is two-fold:
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It aims to
bring external
knowledge
to existing
data as to
provide an
enriched view
(from a single
entry point)
to your
enterprise
data assets.
It addresses the
challenge of
accessing and
storing data from
heterogeneous
internal resources by
building a unified
well-structured
whole to enhance
your business
processes.
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We know from experience that semantic data integration
dramatically extends the enterprise capabilities to turn heterogenous data
of all formats and sources into an integrated whole that serves better
decision making and processes management.
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At Ontotext, we have created a set of data integration tools that
can perform complex operations and are easy to use.
TSV, CSV, *SV, Excel, (.xls and .xlsx), JSON, XML, RDF as XML and Google Data documents
are all supported. Support for other formats can be added with OpenRefine extensions.
from clipboard
from webaddresses (URLs)
TSV, CSV, *SV, Excel, (.xls and .xlsx), JSON, XML, RDF as XML and Google Data documents
are all supported. Support for other formats can be added with OpenRefine extensions.
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In more technical detail, the semantic data integration lifecycle we
have designed includes:
recreating an Application Profile (RDF Shape) that describes the
required form of the final dataset;
reusing existing ontologies and engineering new ontologies as
needed;
leveraging fully the available Linked Open Datasets in your
domain;
designing a simple, logical and sustainable URL strategy;
using the variety of available conversion and ETL tools to perform
the integration;
designing and implementing a data update strategy.
14. www.ontotext.com
You can also reach us via email at
info@ontotext.com
and directly by calling
1-866-972-6686 (North America),
or +359 2 974 61 60 (Europe)
Learn how you can quickly design data processing jobs
and integrate massive amounts of data and see what
semantic integration can do for your data
and your business.