From OntologPSMW
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(Last updated at: 2012-01-05 16:23:11 By user: PeterYim) |
(Last updated at: 2012-01-05 16:29:08 By user: PeterYim) |
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** [[ToddSchneider]]: Jack, Brilliant! | ** [[ToddSchneider]]: Jack, Brilliant! | ||
− | === From [[HensonGraves]] / 2012.01.02~ === | + | === From [[HensonGraves]] / 2012.01.02~05 === |
− | [[HensonGraves]]: Tracks should be designed to produce usable | + | [[HensonGraves]]: Tracks should be designed to '''produce usable work products for the engineering and well as the ontology community''' |
− | work products for the engineering and well as the ontology community | + | |
My suggestion is that the summit develop a collection of challenge problems | My suggestion is that the summit develop a collection of challenge problems | ||
Line 170: | Line 169: | ||
If this approach with the challenge problems were to be attractive then I | If this approach with the challenge problems were to be attractive then I | ||
− | would be willing to participate with the proviso that I could get some folks | + | would be willing to participate with the proviso that I could '''get some folks |
from the ontology community to join the [[INCOSE]] Model-Based System | from the ontology community to join the [[INCOSE]] Model-Based System | ||
− | Engineering Ontology Action Team (OAT) | + | Engineering Ontology Action Team (OAT)'''. |
− | + | ||
− | + | ||
− | + | ||
− | === From [[EricChan]] | + | === From [[EricChan]] / 2012.01.05 === |
− | [[EricChan]]: I have in mind about a track for "ontological information model for cloud infrastructure" with focus on "complex event processing of high-volume, high-velocity, monitoring data (Big Data)" in different layers of the infrastructure. This ontology can enable effective use of Business Activity Monitoring (BAM) tool in cloud infrastructure. ... I will be happy to support others who would like to chair this track. | + | [[EricChan]]: I have in mind about a track for "'''ontological information model for cloud infrastructure'''" with focus on "complex event processing of high-volume, high-velocity, monitoring data (Big Data)" in different layers of the infrastructure. This ontology can enable effective use of Business Activity Monitoring (BAM) tool in cloud infrastructure. ... I will be happy to support others who would like to chair this track. |
+ | |||
+ | === Recap: [[AmandaVizedom]] and [[JoanneLuciano]] / 2011.12.06 === | ||
+ | |||
+ | '''An Objective Metrics for Understanding Ontology Quality in Context''' - |
Revision as of 16:27, 18 December 2012
Contents |
This is a workspace collecting suggestions on how to better organize, coordinate and facilitate OntologySummit2012 activities. While mainly intended for the use by the organizing committee, this is an open page, and contributions from other summit participants who are not on the organizing committee are welcome.
    (1A)
7th in the series of a 3-month open annual event by and for the Ontology Community. This Summit is co-organized by Ontolog, NIST, NCOR, NCBO, IAOA & NCO_NITRD
    (1B1)
ref. OntologySummit
    (1B2)
- [ ontology-summit-org ] message archives - http://interop.cim3.net/forum//ontology-summit-org/
(organizing committee members only)
    (1B3)
- [ ontology-summit ] message archives - http://ontolog.cim3.net/forum/ontology-summit/
(open - for all summit participants)
    (1B4)
ref. http://ontolog.cim3.net/cgi-bin/wiki.pl?ConferenceCall_2011_12_08#nid30GJ
    (1C1A)
- Systems engineering focuses on the interactions of people with their systems, so includes information technology, data and metadata, socio-technical and cultural aspects including institutional, legal, economic, and human-centered design requirements.     (1C1B)
- o Software engineering     (1C1B1)
- o Business rules and enterprise issues     (1C1B2)
- o Socio-technical environment     (1C1B3)
- o Big Data     (1C1B4)
- o Ontology Quality in Context     (1C1B5)
- "Big Data" to include several dimensions:     (1C1C)
- o Complexity of collections     (1C1C1)
- o Large quantities of data     (1C1C2)
- o Heterogeneity of data (e.g. 600 different representations of patient records)     (1C1C3)
- o Federation of distributed data sources     (1C1C4)
- o Extracting (useful) knowledge out of big data (using ontology to UNDERSTAND data)     (1C1C5)
- formulate recommendations for the application of ontological techniques to specific key problems we are facing in the subject area.     (1C1D)
- Potential supporting tracks:     (1C1E)
- Health applications     (1C1E1)
- Reference Data / Authoritative Data     (1C1E2)
- Business Process Data     (1C1E3)
- Net-centric Society     (1C1E4)
- Grand Challenge Problems     (1C1E5)
From the 2011_12_08 community brainstorm input - items to note for action:     (1C2)
ref. under: http://ontolog.cim3.net/cgi-bin/wiki.pl?ConferenceCall_2011_12_08#nid3085
    (1C2A)
- TimWilson: I have to leave the call soon, but I am very interested in     (1C2B)
the System Engineering aspects of Ontology as well as Ontology
Acquisition, including text analytics.
    (1C2C)
Systems Engineering and International Society for Systems Sciences is
pursuing the development of a Unified Ontology for Systems
Engineering. This effort is mostly practitioners getting ready for
interaction with ontologists.
    (1C2E)
(fitness for purpose, evaluation, metrics and metrics) under whichever
theme.
    (1C2G)
I'm suggesting is the theme-focused variant of the topic Joanne and I
suggested here:http://ontolog.cim3.net/cgi-bin/wiki.pl?OntologySummit/Suggestions#nid30E4.
A better title might be "Ontology Quality in Big System applications"
or something like that. Or, "Evaluating Ontologies for Use in Big [X]
Systems Applications"
    (1C2I)
- KenAllgood: I will volunteer for Ontology in electronic health     (1C2J)
record/bioinformatics
    (1C2K)
Big Data and Cloud systems
    (1C2M)
engineering systems, I'm happy to contribute.
    (1C2O)
- MatthewWest: @Todd That sounds close to what I was suggesting. Happy to merge.     (1C2P2)
- PatCassidy: I would be willing to champion a track on exploring the     (1C2Q)
use of a common foundation ontology as a translation mechanism
(interlingua) among multiple databases or multiple systems - large or
small. But if there are no others to make a "track" out of this, I
can just present a paper with my views.
    (1C2R)
the bandwidth to head this up.
    (1C2T)
- JackRing: I was volunteering to organize a track on the hardware implications.     (1C2U)
- JackRing: Track: Implications of forthcoming massively parallel hardware.     (1C2U1)
- Eric Chan: + for aligning dots to tracks, I have Data, Process,     (1C2V)
Engineered, Multi-displinary,
    (1C2W)
- KenAllgood: I'd recommend "information interoperability across federated data"     (1C2Y)
- AliHashemi: @Steve -- at the end of the last summit, there was a     (1C2Z)
consideration to alongside a Communique, explicitly commit to creating
a website for the summit?
    (1C2AA)
- AliHashemi: I can volunteer, but I definitely won't be able to do it alone.     (1C2AB1)
- KenAllgood: I could assist Ali in the website     (1C2AB2)
focusing down or presenting some branches/subtopics.
    (1C2AD)
Ontologies in Big Systems"
    (1C2AF)
track under which we bring in some folks in various domains and/or
projects to describe particular cases where ontologies are being
brought in to support big systems.
    (1C2AH)
possibility.
    (1C2AJ)
and decisions.
    (1C2AL)
HensonGraves: Tracks should be designed to produce usable work products for the engineering and well as the ontology community
    (1C3A)
My suggestion is that the summit develop a collection of challenge problems
which different tracks work on. A track representing an interest group could
take a problem and have its members propose approaches and solutions which
would be critiqued by the group. A track would not have to come to a
consensus solution only produce as a work product proposed solutions and
critiques. Here are some examples of the kind of thing that I have in mind,
based on by experience and interests. Other examples would work as well.
    (1C3B)
- 1. Develop an ontology for metadata for engineering applications. This would     (1C3C)
include artifacts such as specifications, test plans, and test results.
Something like DOLCE would be a good place to start the discussion. As
participants one needs people with real experience in engineering practice
and ontology theory. It is not too hard to argue that an ontology is the
best way to manage the volume of data encountered on large scale engineering
programs. [I spent about 7 years attempting to design a metadata based
information storage and retrieval system for a very large scale product
development program.] I would be happy to contribute or identify others who
could contribute to understanding of the data management issues of such an
endeavor.
    (1C3D)
- 2. Develop engineering models (or axiom sets) for the human heart. Two     (1C3E)
approaches naturally present themselves as starting points. One is models
produced in SysML and the other is Description Logic with possibly
Description Graph extensions. Analysis of the difference would be of great
benefit for both communities and have immediate practical applications.
Along the way one needs to look at how the literature on mereology
contributes or not to developing axioms.
    (1C3F)
- 3. Develop use cases for reasoning based on engineering models (axiom sets     (1C3G)
in description logic). The use cases of course have to be grounded in
everyday engineering problems and have to have to be embedded in logics for
which tractable reasoning is possible. [I am very much engaged with this as
I have a lot of industry experience with relatively simple cases where
checking consistency of axiom sets would have saved the taxpayer a few
billion dollars and 4 or 5 years of product development time. The problem is
that engineering models do not represent the assumptions under which they
are valid. As design progresses a model gets included in a design without
knowledge of the assumptions under which it is valid. The result is
inconsistent designs and the inconsistency is often not detected until test
and evaluation, which of course may require years of rework to fix.]
    (1C3H)
If this approach with the challenge problems were to be attractive then I
would be willing to participate with the proviso that I could get some folks
from the ontology community to join the INCOSE Model-Based System
Engineering Ontology Action Team (OAT).
    (1C3I)
EricChan: I have in mind about a track for "ontological information model for cloud infrastructure" with focus on "complex event processing of high-volume, high-velocity, monitoring data (Big Data)" in different layers of the infrastructure. This ontology can enable effective use of Business Activity Monitoring (BAM) tool in cloud infrastructure. ... I will be happy to support others who would like to chair this track.
    (1C4A)
An Objective Metrics for Understanding Ontology Quality in Context -
    (1C5A)