Re: playing with pil ontology

Hi Graham,
I like Provenance Container. What if your provenance statements were created
by different persons,
processes or at different times, but they are within the same Provenance
Document
(since they are provenance assertions about the same entity)? I may want to
describe the different
provenance containers, or even the provenance container descriptions with
another one.

Thanks,
Daniel

2011/8/15 Graham Klyne <GK@ninebynine.org>

> Jim,
>
> FWIW, in PAQ we talk about "provenance information" as just another
> resource that includes provenance assertions.  To my mind, it's primary
> representation would be as an RDF document.
>
> The terminology here is subject to review and harmonization with the model,
> but I'm not convinced that we need a new concept in the model for this, and
> I'm not keen on a name involving "container", as in my mind that sets up
> expectations of a distinct layer of encapsulation.  We don't talk about
> "containers" for HTML or XML elements, we just talk about HTML and XML
> documents.  Same for provenance, IMO.
>
> I suppose that suggests "Provenance Document", or similar.
>
> #g
> --
>
> Myers, Jim wrote:
>
>>
>>
>> A couple quick comments: I don’t think we’ve distinguished provenance
>> container and account at this point – they are an entity which contains
>> provenance statements and are used to enable you to talk about how the
>> provenance was created (what processes and inputs caused those statements to
>> be), but collection has been discussed as a general aggregate
>> entity/container – a bag of marbles is an entity and saying a process
>> execution used it is shorthand for talking about the individual marbles. A
>> file is a collection of bytes and a process execution may only use some of
>> the bytes, etc.
>>
>>
>> Re: roles – I would argue that you should use something quite specific for
>> the role of your temperature parameter, e.g. “processingtempraturesetpoint’
>> rather than a generic “input” or “inputParameter” role (parameter might
>> still be a supertype of processingtemperaturesetpoint)**. This would be
>> necessary if, for example, your process execution had a reaction temperature
>> and a storage temperature as inputs – now you have two numbers/two
>> temperatures and you have to use each in the correct role for the provenance
>> to be correct. In many cases, you could potentially describe the type of the
>> entity itself well enough to make the provenance clear, but putting the
>> information into the entity typing rather than into the role it has relative
>> to the process execution causes trouble if you use the entity in multiple
>> processes (if I make an entity that is of type “**processingtemperaturesetpoint”
>> and I have a second process that displays a “printablenumber” that uses it
>> as input, the same entity can’t also be of type “printable number” – better
>> to make the entity have type number and play a ‘**processingtemperaturesetpoint”
>> role in one process and the “printablenumber” role in the other.)
>>
>>
>> Jim
>>
>>
>> *From:* public-prov-wg-request@w3.org [mailto:public-prov-wg-**
>> request@w3.org <public-prov-wg-request@w3.org>] *On Behalf Of *Satya
>> Sahoo
>> *Sent:* Monday, August 15, 2011 11:02 AM
>> *To:* Deus, Helena
>> *Cc:* Khalid Belhajjame; public-prov-wg@w3.org
>> *Subject:* Re: playing with pil ontology
>>
>>
>> Hi Lena,
>>
>> Thanks again for trying to use the ontology for the microarray use case!
>>
>> My comments are inline:
>>
>>
>>  >I am not questioning whether agent should be mapped to agents defined
>> elsewhere, which seems to >be obvious– only wondering whether agent “label”
>> and “description” are things we want to standardize >in our model or not. We
>> can “suggest” rdfs:label and rdfs:comment without enforcing it as such –
>> >having those included in the model will likely result in much less
>> heterogeneity when it comes to >reporting provenance (particularly since we
>> are defining it necessarily “open” and highly granular to fit >any
>> particular domain.
>>
>>
>> I am not sure I understand your point. The rdfs:label and rdfs:comment are
>> two of the nine annotation properties that are part of the OWL2 syntax. So,
>> the provenance ontology encoded in OWL includes them by default.
>>
>>
>>
>>
>>  > What was its intended purpose/role in the description of provenance?
>>
>>
>> Provenance container, account, and collection are related concepts for
>> modeling a collection of provenance assertions. E.g. provenance of a
>> Affymetrix gene chip will be a collection of provenance assertions (date of
>> manufacture, location of manufacturer, production series etc.) that can be
>> stored in a single file and the file will be a provenance container.
>>
>>
>>
>>
>>> Example: a list of height measurement is an “untransformed” entity (a
>>>
>> dataset); the average of that list >is the “transformed” entity (another
>> dataset, although a very simple one).
>>
>>  I am dealing with much more complex workflows, (e.g. files containing
>>>
>> the outcome of a microarray >experiment as the untransformed dataset and a
>> list of differentially expressed genes as the >transformed dataset), so
>> please take the example above is just illustrative.
>>
>>
>> I am not sure I see the granularity/expressivity issue in the above
>> example (from your first mail). Both the "untransformed" and "transformed"
>> entities map to input and output data of a process execution - we can create
>> subclass of Entity for this purpose.
>>
>>
>>
>>
>>
>>> An investigator (agent) performs an experiment That experiment has
>>>
>> several input parameters, some >of which are entities (e.g. samples),
>> other are not (e.g. temperature) Resulting from the experiment are  >several
>> output parameters (entities)
>>
>>
>> I am confused by the above scenario. Why is temperature not an entity?
>> Both the input (sample) and (temperature) are special types (sub class) of
>> entities - (a) InputData and (b) InputParameter etc.
>>
>>
>>
>>
>>> So if I understand what you are saying correctly, “temperature” would
>>>
>> be an entity of type “input”, >which in turn would be subclass of “role”.
>> An instance of “input” could then have a certain value (e.g.  >15C) in one
>> of its properties?
>>
>>  In that case, does it make sense to include “input” and “output” classes
>>>
>> in the model as subclasses of >“role”? Or is this something that me and
>> Stephan exemplify in the primer document under “usage of >agent” (or
>> something of the sort)?
>>
>>
>> I agree with Khalid's example where Role allows us to model more complex
>> scenarios. For example, X is an instance of class HumanBeing (perhaps as
>> subclass of entity) and X has multiple roles - researcher, parent, soccer
>> player etc. To model these "functions" we will use the Role class. I believe
>> in the microarray scenario (in your first mail) Roles are not needed.
>>
>>
>>
>>
>>> In that case, does it make sense to include “input” and “output”
>>>
>> classes in the model as >subclasses of “role”? Or is this something that
>> me and Stephan exemplify in the primer >document under “usage of agent” (or
>> something of the sort)?
>>
>>
>> Sorry I did not understand this. Role can be used by any entity, why only
>> "usage of agent"?
>>
>>
>> Thanks.
>>
>>
>> Best,
>>
>> Satya
>>
>>
>> On Mon, Aug 15, 2011 at 7:01 AM, Deus, Helena <helena.deus@deri.org<mailto:
>> helena.deus@deri.org>> wrote:
>>
>> Hi Khalid,
>>
>> Please see comments inline
>>
>>
>> *From:* Khalid Belhajjame [mailto:Khalid.Belhajjame@cs.**man.ac.uk<Khalid.Belhajjame@cs.man.ac.uk><mailto:
>> Khalid.Belhajjame@cs.**man.ac.uk <Khalid.Belhajjame@cs.man.ac.uk>>]
>>
>> *Sent:* 12 August 2011 10:22
>> *To:* Deus, Helena
>> *Cc:* public-prov-wg@w3.org <mailto:public-prov-wg@w3.org>
>>
>> *Subject:* Re: playing with pil ontology
>>
>>
>>
>> Hi Helena,
>>
>> Thanks for this, I think that this is a good exercise and some of the
>> point you mentioned relate to the conceptual model, not only the formal
>> model.
>>
>> On 11/08/2011 18:52, Deus, Helena wrote:
>>
>> Hi all,
>>
>> Reiterating a bit on what was addressed today  in the telco, I downloaded
>> the ontology from mercurial and tried to use it with my use case.
>>
>> I am using the use cases published in [1] and demoed with SPARQL at
>> http://biordfmicroarray.**googlecode.com/hg/sparql_**endpoint.html<http://biordfmicroarray.googlecode.com/hg/sparql_endpoint.html>
>>
>>
>> Here is my input so far:
>>
>>
>> Agent could have dataProperty “label” and “description”; it would help the
>> implementer describe what type of agent does he/she intend to describe. Is
>> the ontology here being confused with the query model?
>>
>> I think that there was previously a long thread discussion on agent and
>> agent types, and whether the model should be prescriptive in this respect.
>> One of the solutions that I think many people were happy with is to leave
>> users choose their favorite model(ontology) for agent, which means that the
>> agent class defined in the ontology acts as a place holder that can be
>> specialized to include description, types, and whatever the application
>> needs.
>>
>>
>> I am not questioning whether agent should be mapped to agents defined
>> elsewhere, which seems to be obvious– only wondering whether agent “label”
>> and “description” are things we want to standardize in our model or not. We
>> can “suggest” rdfs:label and rdfs:comment without enforcing it as such –
>> having those included in the model will likely result in much less
>> heterogeneity when it comes to reporting provenance (particularly since we
>> are defining it necessarily “open” and highly granular to fit any particular
>> domain.
>>
>>
>> ProvenanceContainer is not useful, or its description is not clear; what
>> should be an instance of provenanceContainer?
>>
>>
>> At this stage, the description of this concept is not yet stable in the
>> conceptual model as far as I know.
>>
>>
>> What was its intended purpose/role in the description of provenance?
>>
>>
>> I want to create an instance of a “untransformed” entity (in my case, a
>> dataset) and a “transformed” entity. Is the model going to give me that
>> granularity/expressivity or do we expect each implementer to come up with
>> their own way of defining these?
>>
>> Could you please clarify what you mean by transformed and untransformed
>> entity?
>>
>> Example: a list of height measurement is an “untransformed” entity (a
>> dataset); the average of that list is the “transformed” entity (another
>> dataset, although a very simple one).
>>
>>
>> I am dealing with much more complex workflows, (e.g. files containing the
>> outcome of a microarray experiment as the untransformed dataset and a list
>> of differentially expressed genes as the transformed dataset), so please
>> take the example above is just illustrative.
>>
>>
>> ProcessExecution needs more expressivity, I think. Not sure how to solve
>> this in a domain independent way, but here’s my problem:
>>
>> An investigator (agent) performs an experiment
>>
>> That experiment has several input parameters, some of which are entities
>> (e.g. samples), other are not (e.g. temperature).
>>
>> Resulting from the experiment are several output parameters (entities)
>>
>>
>> I think that the current model caters for the above need. If you are
>> specifically trying to differentiate between different kinds of inputs
>> (samples as opposed to temperature), then the notion of role can be helpful
>> in this resepect.
>>
>>
>> So if I understand what you are saying correctly, “temperature” would be
>> an entity of type “input”, which in turn would be subclass of “role”. An
>> instance of “input” could then have a certain value (e.g. 15C) in one of its
>> properties?
>>
>> In that case, does it make sense to include “input” and “output” classes
>> in the model as subclasses of “role”? Or is this something that me and
>> Stephan exemplify in the primer document under “usage of agent” (or
>> something of the sort)?
>>
>>
>>
>>
>> Thanks, khalid
>>
>>
>> Have not completed my “experiment” yet, but will provide more feedback
>> soon J
>>
>>
>> Best Regards,
>>
>> Helena F. Deus
>>
>> Post-doctoral Researcher
>> Digital Enterprise Research Institute
>>
>> National University of Ireland, Galway
>>
>> http://lenadeus.info
>>
>>
>>
>>
>
>
>