>From Matthew West's study on the high quality data models,
http://www.matthew-west.org.uk/documents/princ03.pdf, there is a listing of
key properties, as pictured below. One could also add relativity, utility,
worth, correctness, originality, credibility, certainty, truth, etc. As i
know, there is a new book coming. (01)
----- Original Message -----
From: "MacPherson, Deborah" <dmacpherson@xxxxxxxxxxxxxxxx>
To: "Ontology Summit 2011 discussion" <ontology-summit@xxxxxxxxxxxxxxxx>
Sent: Monday, January 24, 2011 4:22 PM
Subject: [ontology-summit] Data Quality - Was: Invitation to a brainstorming
call for the 2011 Ontology Summit (02)
> From the US Dept of Transportation, Federal Highway Administration Policy
> Information
>
> "...Accuracy is only one characteristic of quality, just as validity or
> conformance to business rules is one characteristic of quality. These
> characteristics are some of the information quality characteristics
> categorized as inherent characteristics.
>
> Fitness for purpose is the characteristic of usefulness of data for a
> specific requirement..."
>
> http://www.fhwa.dot.gov/policy/ohpi/dataquality.cfm
>
>
>
> DEBORAH MACPHERSON, CSI CCS, AIA
> Specifications and Research
>
> Cannon Design
> 1100 Wilson Boulevard, Suite 2900
> Arlington, Virginia 22209
>
> Direct Line 703 907 2353
> 4 Digit Dial 6353
>
> dmacpherson@xxxxxxxxxxxxxxxx
> cannondesign.com
>
> Please consider the environment before printing this email.
>
> -----Original Message-----
> From: ontology-summit-bounces@xxxxxxxxxxxxxxxx
> [mailto:ontology-summit-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Peter R.
> Benson
> Sent: Sunday, January 23, 2011 7:42 AM
> To: Ontology Summit 2011 discussion
> Cc: Ontology Summit 2011 discussion
> Subject: Re: [ontology-summit] Invitation to a brainstorming call for the
> 2011 Ontology Summit
>
> The definition of "quality" is pretty simple "meets requirements" the
> issue is how to define requirements. ISO 22745-30 does a pretty good job.
>
> Data and Information are two different concepts, their characteristics are
> different. Timeliness and relevance are characteristics of information,
> the data is what it is. Finally there is no such thing as accuracy only
> assertions of accuracy. A lot of this ground is covered in ISO 8000
>
> Peter
> Cell: +1 610 462 5923
>
> On Jan 22, 2011, at 9:18 AM, "Brian K Lucas" <lucasb@xxxxxxxx> wrote:
>
>> Greetings all,
>>
>> I like this discussion, and have a few thoughts of my own (as you come
>> to know me more, you'll discover that to be the norm ;=)
>>
>> A) @Jack : I agree that "adequate, accurate and timely" is a worthy goal.
>> I'd like to hear more about your definition of "adequate" and "accurate".
>>
>> B) @Jack : Regarding quality: In my experience, "fitness for purpose"
>> is trinary, when taken from a single consumer's point of view: not
>> fit, fit, overly fit. In the real world, however, very few offerings
>> are consumed by a single entity. Therefore, I believe that, when
>> taken in the context of the offering, and including all consumers,
>> fitness for purpose/quality is indeed scalar, if the measurement is
>> being taken from the perspective of the producer. If you complete a
>> histogram/pie chart of these three values for all consumers, you get
>> three counts of valuable metrics, which should not be
>> combined: % fit for purpose, % not fit for purpose, and %overly fit
>> for purpose. The requirements not met for the "not fit" group
>> represent offering "defects"; the requirements met for the "overly
>> fit" group represent waste of effort for that consumer group. If
>> requirements have been implemented that NOBODY in the "fit" group
>> needs, then that is wasted producer effort - unless, of course, they
>> serve a future consumer. My conclusion? There is value in measuring
>> "quality" across the existing and intended user base, and improving
>> the offering to move more consumers into the "fit for purpose" count,
>> without removing anyone who is already there.
>> And, because consumer requirements usually change over time,
>> continuous improvement of "quality" is desirable. Then, add in that
>> even for a single consumer, they may present KANO-like ranking of
>> requirements (must have, should have, could have, etc.), and binary
>> gets even a little more fuzzy for me.
>>
>> C) Producer cost is also key here. If the value exchange received by
>> the consumer does not support the cost to meet their requirements,
>> then a "not fit" offering may still be of value to the consumer, as
>> they may augment it with other offerings. An example of this is
>> Microsoft Word. It does NOT meet all of my requirements - and yet I
>> find it "fit for purpose" because I can work around the "defects".
>>
>> D) @Nicola : I agree with the case for varying levels of "quality";
>> however, I also think that case studies are notoriously hard to
>> quantify. In my experience, it is usually an opinion that one work
>> method over another produced "better" results, because most people
>> don't try it both ways and actually measure fitness for purpose
>> afterwards.
>>
>> E) I have been working on an ontology of organizations and human value
>> exchange. I have tried traditional ERD-style modeling,
>> object-oriented class modeling, and now OWL ontology modeling. Each
>> has strengths as a modeling method; each has "defects", or "fitness of
>> purpose" for my work.
>> It may be an understanding defect on my part, but one of the primary
>> issues that I have been facing is polymorphism of modeled objects. As
>> soon as you "declare" something to be of a "type" of some modeling
>> class/entity/etc, you constrain it from taking on characteristics of
>> other classes that it may also play a role in. An example is a human
>> - most people would model "human" as a class; but in my domain, a
>> "human" is also the offering of an educational process (with an
>> improved knowledge metric). My solution so far has been to only use
>> inferred classes to discover a thing's class by its relationships.
>> So, from my perspective, I am finding ontologies "not fit for purpose"
>> in their current description language and implementation. I am
>> interested in thoughts that the other summit participants may have to
>> help me remove this obstacle - even if it is more training for me on
>> building ontologies. :=)
>>
>> Brian K. Lucas
>> Sponsor, Worldwide Institute for Organization Ontologics
>> Lucasb-at-wio2-dot-org
>>
>> -----Original Message-----
>> From: ontology-summit-bounces@xxxxxxxxxxxxxxxx
>> [mailto:ontology-summit-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Tim
>> Wilson
>> Sent: Saturday, January 22, 2011 8:11 AM
>> To: ontology-summit@xxxxxxxxxxxxxxxx
>> Subject: Re: [ontology-summit] Invitation to a brainstorming call for
>> the
>> 2011 Ontology Summit
>>
>> Gentlemen,
>>
>> If I may jump in here. This discussion makes me think of the 85/15
>> rule where finding and fixing 85% of all software bugs is relatively
>> easy, the last 15% is much more difficult in terms of time and effort.
>> There comes a point where developers have to say that the ontology is
>> 'good enough'. Jack is arguing that this does not constitute 'high
>> quality'
>> and therefore the comment on quality being binary. Some person or
>> persons must make a decision that the product is good enough (until
>> the next serious bug is uncovered). You may think that there are no
>> more blue balls in the bin, but yet one is found. Quality instantly
>> goes from "1" to "0" until the issue is analyzed and a choice is made to
>> either ignore it or fix it.
>>
>> Tim Wilson
>>
>> On 12/15/2010 3:22 AM, Matthew West wrote:
>>> Dear Jack,
>>>
>>>> MW,
>>>> Standing on the shoulders of Deming, Crosby, Juran, etc. I would
>>>> first ask
>>> the
>>>> owner a) Is the fifth one guaranteed irrelevant
>>> MW: I am assuming it is relevant.
>>>
>>>> and b) what is your level of
>>>> confidence there are not 6 errors?
>>>> Jack
>>> MW: Indeed, but then by the same token how can you be certain
>>> anything is defect free, even if no defects are apparent?
>>>
>>> MW: I think it is more useful to think of quality as the degree to
>>> which requirements are met. Then when you fix some bugs you have
>>> improved the quality, though you may not have met all the requirements.
>>>
>>> Regards
>>>
>>> Matthew West
>>> Information Junction
>>> Tel: +44 560 302 3685
>>> Mobile: +44 750 3385279
>>> matthew.west@xxxxxxxxxxxxxxxxxxxxxxxxx
>>> http://www.informationjunction.co.uk/
>>> http://www.matthew-west.org.uk/
>>>
>>> This email originates from Information Junction Ltd. Registered in
>>> England and Wales No. 6632177.
>>> Registered office: 2 Brookside, Meadow Way, Letchworth Garden City,
>>> Hertfordshire, SG6 3JE.
>>>
>>>
>>>
>>>
>>>> On Dec 14, 2010, at 3:45 PM, Matthew West wrote:
>>>>
>>>>> Dear Jack,
>>>>>
>>>>>> Regarding Nicola's quite relevant concern (below) it may be useful
>>>>>> to
>>> note
>>>>>> that
>>>>>> a) quality is binary, not a scalar (Crosby, Deming, Juran, etc.)
>>> Quality
>>>>>> signifies conformance to requirements, Yes or No, therefore 'high
>>>>> quality' is
>>>>>> meaningless.
>>>>> MW: So presumably you would argue that if an ontology has 5
>>>>> defects, and
>>> 4
>>>>> of them are fixed, there is not improvement in quality as a result....
>>>>>
>>>>> Regards
>>>>>
>>>>> Matthew West
>>>>> Information Junction
>>>>> Tel: +44 560 302 3685
>>>>> Mobile: +44 750 3385279
>>>>> matthew.west@xxxxxxxxxxxxxxxxxxxxxxxxx
>>>>> http://www.informationjunction.co.uk/
>>>>> http://www.matthew-west.org.uk/
>>>>>
>>>>> This email originates from Information Junction Ltd. Registered in
>>> England
>>>>> and Wales No. 6632177.
>>>>> Registered office: 2 Brookside, Meadow Way, Letchworth Garden City,
>>>>> Hertfordshire, SG6 3JE.
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>> b) note carefully that from the usage viewpoint the requirements
>>>>>> amount
>>> to
>>>>>> 'fit for purpose' (Checkland) or 'satisficing' (Simon).
>>>>>> c) both proof of correctness and exhaustive test are futile,
>>>>>> therefore
>>> not
>>>>>> included.
>>>>>> d) the goal becomes warranty that the ontology of interest is
>>>>>> devoid of internal faults and external incompatibilities wherein
>>>>>> warranty means
>>> zero
>>>>>> false positives and false negatives.
>>>>>> e) an appropriate theme may be "Making the case for adequate,
>>>>>> accurate
>>> and
>>>>>> timely ontologies" which embraces both the result and the
>>>>>> development activity.
>>>>>> f) whether any ontology is viable or not depends on both the
>>>>>> ontology
>>> and
>>>>> the
>>>>>> intended usage.
>>>>>> g) this means that any cadre of ontology developers must include
>>> members
>>>>> who
>>>>>> are dedicated to independent and objective assessment of the
>>>>>> viability
>>> of
>>>>> any
>>>>>> ontology or patch thereof or ordered set of patches.
>>>>>> h) fortunately, technologies, tools and methods exist (or are
>>>>>> imminent)
>>>>> for
>>>>>> viability assessment of algorithms of all classes and types with
>>> respect
>>>>> to
>>>>>> intended usage. This includes ontologies. Even the spaghetti code
>>>>>> in
>>> most
>>>>> OWL-
>>>>>> based examples can be assessed, even simplified, and potentially
>>>>>> made
>>> more
>>>>>> "lean" without inducing 'brittle.'
>>>>>> i) this is one reason why I suggested to Steve Ray that one corner
>>>>>> of
>>> the
>>>>>> Summit allow open-mind dialogue regarding new technologies.
>>>>>>
>>>>>> Onward,
>>>>>> Jack Ring
>>>>>>
>>>>>>
>>>>>> On Dec 14, 2010, at 5:00 AM, Nicola Guarino wrote:
>>>>>>
>>>>>>> Dear colleagues,
>>>>>>>
>>>>>>> I also agree very much with John and Matthew concerning the
>>>>> importance
>>>>>> of high quality ontologies, and on their observation that the
>>>>>> quest for
>>>>> high
>>>>>> quality data models in software engineering definitely reflects a
>>>>> sensitivity
>>>>>> to important ontological aspects much higher than what we find in
>>> people
>>>>> just
>>>>>> focusing on ontology languages.
>>>>>>> In the light of this, I suggest to specify a bit more the
>>>>>>> overall
>>>>> theme
>>>>>> of our Summit, which in my opinion could be "Making the case for
>>>>> ontological
>>>>>> analysis" instead of "Making the case for ontology". An
>>>>>> alternative
>>> could
>>>>> be
>>>>>> "Making the case for high-quality ontologies".
>>>>>>> The reason for this proposal should be self-evident, I believe.
>>>>> Deciding
>>>>>> how much effort to put in developing a particular ontology is a
>>>>>> crucial choice, and it is very important to distinguish the cases
>>>>>> where a
>>> proper
>>>>>> ontological analysis pays off, and is indeed a crucial aspect of
>>> success,
>>>>> from
>>>>>> those where a "lightweight" approach is sufficient.
>>>>>>> Just brainstorming...
>>>>>>>
>>>>>>> Talk to you soon,
>>>>>>>
>>>>>>> Nicola
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>> On 9 Dec 2010, at 16:03, John F. Sowa wrote:
>>>>>>>
>>>>>>>> Dear Matthew and Peter,
>>>>>>>>
>>>>>>>> MW:
>>>>>>>>> ... my forthcoming book "Developing High Quality Data Models".
>>>>> Substitute
>>>>>>>>> ontology for data model and the same argument applies. The
>>>>>>>>> benefits
>>>>> come
>>>>>>>>> from improving and automating decision making through
>>> fit-for-purpose
>>>>>>>>> information to support those decisions.
>>>>>>>> I very strongly agree. Software engineers have been doing
>>>>>>>> ontology (avant la lettre, as they say) for a very long time.
>>>>>>>> And much of
>>> that
>>>>>>>> work has been very good -- sometimes much better than what
>>>>>>>> people are doing with so-called ontology languages.
>>>>>>>>
>>>>>>>
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>>
>> --
>> Timothy C. Wilson
>> Graduate Student in Knowledge Management Kent State University
>> Expected
>> Completion: August 2011
>>
>>
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