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Corporate  |  Product  |  Technology

Corporate

When was Unicornâ founded?
Unicorn Solutions, Inc. was co-founded in 2001 by entrepreneur Dr. Zvi Schreiber and software executive Rannen Meir.

How many rounds of financing has Unicorn raised to date?
Unicorn raised a Series A round totaling $8.8 million and a Series B round totaling $6 million.

Who are Unicorn's investors?
Unicorn is privately-held. Unicorn's corporate investors include Intel Capital, Bank of America Equity Partners, Jerusalem Global Ventures (JGV), Israel Seed Partners, Apropos IT Ventures, Tecc-IS, and a leading group of individual investors, and others.

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Product
What is the Unicorn System?
The Unicorn System is a comprehensive platform for managing and integrating enterprise information resources. It combines metadata repository, information modeling, hub-and-spoke mapping, and automated data transformation script generation capabilities into a single fully-integrated suite. The Unicorn System provides customers with a seamless business view by relating disparate data formats and interfaces to an agreed-upon Information Model that describes the business, its component parts, and all relationships.

What is an Information Model?
An Information Model - or ontology - is a highly expressive formal model representing some or all of the enterprise. Information Models are used within The Unicorn System in one of three ways: (1) building from scratch, (2) reverse-engineering existing models, or (3) adopting industry standard models.

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Technology

What are Data Semantics & the Semantic Web?
Semantics inspires a vision in which data carries unambiguous business meaning that can be found, aggregated and used accurately and flexibly without prior knowledge of the data’s specific format. Data Semantics are tightly linked in many ways with the vision of a Semantic Web in which the W3C is taking a leading role.

The Semantic Web is a web of data that will enable machines to comprehend documents and data. The Semantic Web is not a separate Web but an extension of the current World Wide Web. The advantage of the Semantic Web is that information is given well-defined meaning, better enabling computers to work in cooperation.

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What is Semantic Information Management?
Semantics inspires a vision in which data carries unambiguous business meaning that can be found, aggregated and used accurately and flexibly without prior knowledge of the data’s specific format. Semantic Information Management (SIM) delivers the benefits of semantics to enterprise IT. Semantic Information Management addresses the problem of incompatible data formats by capturing the precise meaning of data in agreed-upon terms. Key elements of the architecture are:
  • Metadata – Data assets must be cataloged if they are to be used for any sort of IT project.
  • Information Model - A rich central model of some or all of the business.
  • Data Semantics - Semantically mapping data sources to the Information Model to capture meaning.

Semantic Information Management creates value by delivering higher quality business information, providing the flexibility to support business change and making IT costs lower and more predictable. SIM can be introduced gradually to specific projects or applied to an entire enterprise in a comprehensive initiative. With Semantic Information Management, the enterprise can strive for an environment in which everyone speaks the same business language, data carries unambiguous business meaning and the data environment is managed and integrated at will. To request a copy of our SIM White Paper, visit the Unicorn Literature section.

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What is an ontology?
In philosophy, ontology is a theory about the nature of existence. The word ontology stems from the Greek language, meaning the study of being. It is the fundamental interpretation of the ultimate constituents of the world of experience. Computer science researchers have co-opted the term for computer science, whereby an ontology is a machine-readable dictionary that formally defines relations among terms. An ontology is a model of the products, materials, documents and other entities about which the data is making statements. An ontological model can therefore serve as a rich dictionary or thesaurus which is able to link data structures - whatever their source or format, by means of a common model. It is thus a powerful tool which allows a formal description of semantics - the meaning of the data.

Ontologies are becoming increasingly popular in the enterprise by virtue of what they promise to deliver: a shared and common description of data that is not dependent on the particular context of a data source, and can be freely communicated between application systems, information systems, and people. Ontologies will enable the second generation of e-commerce and knowledge management tools, and will shape the future of the Semantic Web. In adopting an ontological model, enterprises can seamlessly map between the hundreds of different data formats they have.

According to Gartner Research, “The objective of an ontology is to provide a formal specification of part of the real world… Ontology-based techniques are beginning to provide the structure to realize effective application discovery, maturing to yield tool and methodology frameworks that can support end users … the ontology can provide design and integration time coherence.” ("Semantic Web Technologies Take Middleware to Next Level," by Jim Jacobs and Alexander Linden, August 2002, used with permission).

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