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Re: [ontolog-forum] master data vs. ontologies

To: ontolog-forum@xxxxxxxxxxxxxxxx
From: Kingsley Idehen <kidehen@xxxxxxxxxxxxxx>
Date: Thu, 12 Feb 2015 08:13:05 -0500
Message-id: <54DCA6E1.3000506@xxxxxxxxxxxxxx>
On 2/12/15 6:30 AM, Erick Antezana wrote:
> Hi,
> I need some help to better define the line (sometimes apparently grey) 
> between master data and ontologies.
> We all, at least in this forum, know that there are several 
> definitions for both terms.
> I guess most of us are familiar with Gruber's one: a formal 
> specification of a shared conceptualization.
> In the case of master data:
> - 'entities, relationships, and attributes that are critical for an 
> enterprise and foundational to a key business process and application 
> systems'
> or among others:
> - 'is the consistent and uniform set of identifiers and extended 
> attributes that describes the core entities of an enterprise'.
> What are the key components to differenciate master data and ontologies?
> What is common to both artefacts?
> From what I have seen, sometimes the border between them seems indeed 
> relatively grey... which seems to be the product of having ontologies 
> as glue components of disparate master data. Also, there seems to be a 
> continuum between them (as in the databases and knowledge base thread 
> in this forum). Anyway, I would appraciate reading your thoughts about it.
> Cheers,
> Erick    (01)

Erick,    (02)

The problem is that MDM is a marketing moniker, just like "Big Data", 
SOA, and the like. All of these monikers are deliberately generic and 
borderline meaningless (by design). An ontology (in my eyes) is the 
antithesis of fluffy marketing buzzwords since they force you to look at 
the actual characteristics of an entity and define said characteristics 
meaningfully.    (03)

MDM is fundamentally about holistic views of heterogeneous data sources. 
Basically, heterogeneous data source virtualization.    (04)

Most MDM narratives pay lip service to "semantics" and rarely address 
the practical realities of implementing enterprise-wide heterogeneous 
data virtualization, which cannot really manifest without an ontology of 
terms that defines the nature of entities and relations, in a given 
enterprise.    (05)

Anyway, ontologies are a powerful tool for addressing the fundamental 
challenges associated with practical virtualization of heterogeneous 
data sources, be it at the private enterprise level or even across the 
many data-silos that now constitute the world wide web (e.g., Facebook, 
Google+, Twitter, LinkedIn etc..).    (06)

BTW -- I've recently published a number of blog posts about data 
de-silo-fication and heterogeneous data virtualization.    (07)

Links;    (08)

-- Deceptively Simple Conceptual Data Virtualization
-- From Open Database Connectivity to Open Data Connectivity
-- Oracle Data De-Silo-Fication .    (09)

Regards,    (010)

Kingsley Idehen 
Founder & CEO
OpenLink Software
Company Web: http://www.openlinksw.com
Personal Weblog 1: http://kidehen.blogspot.com
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Twitter Profile: https://twitter.com/kidehen
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LinkedIn Profile: http://www.linkedin.com/in/kidehen
Personal WebID: http://kingsley.idehen.net/dataspace/person/kidehen#this    (011)

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