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All Wonderful and illuminating and John I appreciate and mostly agree. - We need formalization, namely on how to interact, map or integrate the two.
- Specifically relate Enterprise Data Dictionaries (associated entities and schemas as well) and logically developed Ontologies i.e. with associated things and predicates.
- Do any mapping tools exist? I have only seen associative or parallel semantic method (manual) of looking at Terms and mapping to Entities in OWL- RDF use case and with DB E-R.
- Are organizations such as OMG and W3C doing it already ( as part of or beyond ODM)?
Regards, Ravi
On Thu, Feb 12, 2015 at 10:52 AM, David Price <dprice@xxxxxxxxxxxxxxx> wrote: In my experience, the distinction is :
MDM is a discipline concerned with managing data models and key data values and codes. For example, some people consider the list of customer contact information as master data, the names and columns of RDBMS tables as master data, country code lists as master data, etc. So, MDM apps are built using data models whose data values are about other data models/values/codes used in their enterprise. MDM has a fuzzy definition, as noted by others, but most people I’ve worked with mean what I’ve suggested when using the term.
Ontologies are data models written using logic-based languages and can cover whatever scope is of interest. So, you can have an ontology whose scope is supporting MDM, and your MDM app may contain names of classes and properties in operational ontologies. Some people require that data models be about the real world to be considered an ontology, but others are less worried about that criteria when using that term and really only care about the data model being written using logic-based languages.
So, simply put MDM apps are about managing other apps in my enterprise, and ontologies are a kind of data model that can be the basis for any enterprise app.
Cheers, David
Dear Erick, This is largely a question of the different language used by different communities. People who work with RDBMS and are struggling to integrate data across different databases will talk about Master and Reference Data, and use tools like SQL and ETL. People who use OWL or RDF and Prolog are likely to talk about ontologies, and be looking at performing reasoning across their ontologies. What the ontologies and master data represent is essentially the same thing. Regards Matthew West Information Junction Skype: dr.matthew.west This email originates from Information Junction Ltd. Registered in England and Wales No. 6632177. Registered office: 8 Ennismore Close, Letchworth Garden City, Hertfordshire, SG6 2SU. 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' - '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.
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Thanks.
Ravi
(Dr. Ravi Sharma)
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