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

To: "[ontolog-forum]" <ontolog-forum@xxxxxxxxxxxxxxxx>
From: David Price <dprice@xxxxxxxxxxxxxxx>
Date: Thu, 19 Feb 2015 16:39:37 +0000
Message-id: <218503DF-80C3-41B4-8DE4-3BF9CE9D83E0@xxxxxxxxxxxxxxx>
Hi Tom,

The Wikipedia quote about MDM for SAP is a very limited perspective of this topic. If you think what Wikepedia said is correct and complete, then there’s no point in discussing this topic because “ontology” in not in your vocabulary. If not, then we continue.

MD may be concepts in a SKOS concept scheme (e.g. country code). MD may be table and column names in RDBs (e.g. Customer table has Country column). MD may be managed data values for specific columns in RDBs (e.g. country code). MD may be managed rows in RDBs (row in Customer table). MD may be part of an ontology (e.g.an enumerated class Country with property hasCode). MD may be instances based on an ontology (e.g. Customer class instance). 

MDM is not about philosophy or type/token debates (since that distinction depends on the technology in play), but about a practice. Other that that practice, there is nothing really special about master data at all.  The only important difference wrt Master Data in any of the forms I mentioned is that it is *governed* in a specific manner for the purpose of providing a common/shared, stable framework for use across enterprise apps. It’s the governance and related practices that are important when talking about MD, not the technology.

For example, in the Semantic Web world look at the UN FAO Geopolitical ontology [1] where the ontology is only interesting because it is used to define instances of Country and related characteristics of those instances. 

Also, as the technology is not *the* key factor, you can quite often download public MD as OWL, Oracle or MySQL database dumps, SKOS, and often one or two standard XML or text encoding. A good example of that is ChEMBL [2] which is a "manually curated chemical database of bioactive molecules with drug-like properties”.  It’s all the same MD just represented in different forms for different user communities. Enterprises often manage MD in a similar variety to allow different architectural approaches to app development, including things you might not expect like two-way integration via spreadsheets or with Sharepoint.

So in some sense Matthew is wrong in that if the ontology is not governed following MDM practice then it is indeed not about MD and does not contain MD. However, if the ontology is something like the ChEMBL or FAO Geo OWL ontology & instances and your enterprise uses that directly in an app then Matthew is right, that ontology and the instances based on the ontology are governed using MDM practice.


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On 18 Feb 2015, at 02:29, Thomas Johnston <tmj44p@xxxxxxx> wrote:


Ontologies and Master Data: Types and Tokens, or Something Else?

After having laid out my argument that ontologies and master data are not about “the same thing”, Matthew West has repeated his belief that they are. But he has done so without addressing my argument that they are not. I think the point I tried to make is important enough and indeed that the case I made for it (correct or incorrect) is solid enough that if Matthew doesn't agree with me, he should say why he does not, and also provide a cogent argument for saying that they are indeed about “the same thing”.

Of course, “same thing” is a vague enough predicate that for most comparisons of any but a trivial nature, it will be possible to say that, in some sense, the compared things are “the same”; but equally possible to say that, in some sense, the compared things are different, i.e. not “the same thing”.

I do not deny that many true things have been said, in this thread, about ontologies and about master data. If two things are not “the same thing” unless all statements true of the one are also true of the other, then “same thing” means “identity”, and by that standard, clearly, ontology and master data are not “the same thing”.

But that is not the relevant standard. I do not require Matthew, or anyone else claiming that ontologies and master data are, in some sense, “the same thing”, to show that they are the “identical, one-and-the-same thing”. Nor do I think they mean that. However, I do ask that they do more than make some statements that are true of one, but not of the other. The distinction, or the absence of one, must be based on a more substantive issue than that.

For me, I use a theoretically well-grounded distinction to support my contention, and I explain in unambiguous terms how that distinction applies to master data and to ontologies. If Matthew or anyone else disagrees with me, I would appreciate hearing what is wrong with my argument.

To adumbrate that argument from some messages of a few days ago, I said that ontologies are about types and master data is about instances/tokens or types. Now since the type/token distinction is as clear as the distinction between sets and their members, or sentences and their utterances/inscriptions, and is a staple of formal logic, I claim that the distinction is theoretically well-grounded. It is also well-established in introductions to logic. Indeed, it is the basis of the distinction between first-order and higher-order logics, first-order logic being about instances and higher-order (second-order) logic required to formalize types of those instances, including types of kinds of things, types of properties of things, and types of relationships among things.

Given all this, the next question is: does the distinction apply in this case? Are ontologies about types, and not about tokens? From a theoretical point of view, going back to Aristotle, they clearly are. From the point of view of current usage of the term “ontology”, I have never found anything called an ontology that was not about types, and was about tokens.

And is master data about tokens, not about types? I think it is clear that it is. For example, from the Wikipedia entry for “master data”, we have:

“Material Master Data is a specific data set holding structured information about spare parts, raw materials and products within Enterprise Resource Planning (ERP) software. The data is held centrally and used across organizations. ….. Vendor Master refers to the centralized location of information pertinent to the Vendor. Often this will include the Legal entity name, Tax identification and contact information.

Clearly, this quotation is talking about spare parts, not Spare Part as a type, nor to types of Spare Parts, to specific instances of raw material, not to a type labeled “Raw Material”, to date about specific vendors, not about Vendor as a type, and so on.

And I have another argument showing that the type/token (or type/instance as it is sometimes called) distinction does apply to ontologies and master data. As I explained in the earlier messages, relational tables represent types of things, and their columns represent types of properties of those things or relationships among those things. (The fuller account can be found in Chapters 4-6 of “Bitemporal Data: Theory and Practice” (BDTP). Yet SQL does not manages and retrieves data about types of things. It manages and retrieves data about instances of those types, and rows in relational tables are each descriptive of one instance of the type represented by the table it is in.

I think that what I have said is true, and also that it is important (although I haven't said anything about that second point so far). If Matthew or anyone else thinks that what I have said is not true, I would appreciate hearing why they think that, and specifically what about my argument is wrong.

I do not claim that any reading about ontologies and master data, no matter how extensive, would make what I have said obvious. The situation is at best, I think, a matter of the trees hiding the forest. It seems to me, with all due respect, that Matthew and others contributing to this thread have pointed out various trees, and in some cases tried to describe the clump those trees comes from (i.e. what they have in common, that commonality being the proffered distinction/similarity between ontologies and master data).

But perhaps the problem is that I am wandering in the wrong forest.

I'd like to know what others here think.

With my thanks in advance,

Tom Johnston

On Thursday, February 12, 2015 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.


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On 12 Feb 2015, at 18:09, Matthew West <dr.matthew.west@xxxxxxxxx> wrote:

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.
Matthew West                            
Information  Junction
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Skype: dr.matthew.west
This email originates from Information Junction Ltd. Registered in England and Wales No. 6632177. 
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From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Erick Antezana
Sent: 12 February 2015 11:30
To: [ontolog-forum]
Subject: [ontolog-forum] master data vs. ontologies
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.

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