[seek-kr-sms] Notes from SWDB @ VLDB
Shawn Bowers
bowers at sdsc.edu
Wed Sep 1 07:41:07 PDT 2004
The proceedings will be available through Springer LNCS (free through most
universities). They aren't available yet because the keynote speakers will
also have papers in the proceedings.
If there is a paper of interest, we can look at the author's website, or
contact them directly.
shawn
On Tue, 31 Aug 2004, Serguei Krivov wrote:
> Shawn,
> These things are interesting. Is there any way to obtain (freely) the
> complete text of the proceedings?
> Serguei
>
> ------------------------------------------------------------------------
> --------------
> Serguei Krivov, Assist. Research Professor,
> Computer Science Dept. & Gund Inst. for Ecological Economics,
> University of Vermont; 590 Main St. Burlington VT 05405
> phone: (802)-656-2978
>
>
> -----Original Message-----
> From: seek-kr-sms-admin at ecoinformatics.org
> [mailto:seek-kr-sms-admin at ecoinformatics.org] On Behalf Of Shawn Bowers
> Sent: Tuesday, August 31, 2004 11:17 AM
> To: seek-kr-sms at ecoinformatics.org
> Subject: [seek-kr-sms] Notes from SWDB @ VLDB
>
>
>
> Hi all,
>
> Here are some notes I took from the SWDB workshop. VLDB has started
> today, so I will take send notes from that as well...
>
> I presented our paper on Sunday. It went well, and I talked with a few
> people who were generally interested. I having also been pushing Kepler
> for you Kepler folks.
>
> (Note that the notes are only for talks, papers that seem somewhat
> interesting/related.)
>
> Shawn
>
>
> ----------
>
>
> SWDB'04 NOTES:
> --------------
>
> * HCOME: A tool-supported methodology for engineering living ontologies
> ---------------------------------------------------------------------
> Konstantinos Kotis
> Pg. 147
>
> A "personal space" tool; maybe something for UI for ontology building
>
>
> * Data Semantics Revisited
> ------------------------
> Keynote: John Mylopoulos and Alex Borgida
>
> J. Mylopoulos starts:
> =====================
>
> "World semantics": Trying to capture the relation between the model
> (information source) and the real-world things that are being
> modeled by that source.
>
> Semantic data models: Jean-Robert Abrial (workshop in Corsica);
> Bracchi, Paolini, Pelagatti; Haniaut and Pirotte; Schmid and
> Swenson; in 1975 Chen, Navathe, Roussopoulos and Mylopoulos
>
> Role of semantic data models: Part of the DBMS technology (semantic
> DBMSs); Used during/for design (part of design process); part of the
> user interface to a database.
>
> How does one use a db where semantics has been factored out? Rely on
> a stable env. of users and app programs to know the
> semantics. Downside: Legacy data! Hard to mainain, share, etc.
>
> Factoring out semantics is bad in open, changing
> environments (like the web)
>
> Semantic Web: Sycara, ODBASE'03. Hypertex data are desinged for
> human consumption. Machine processable web data. Layered cake.
>
> Data semantics take 2: Formal ontology. Web-page
> annotations. Annotations used by browsers/search engines/e-service
> composition.
>
> Lots of work on the expressive languages. Not much on the annotation
> and use (applications).
>
> Some concerns: Hard to use technologies for computationally
> demanding tasks, e.g., theorem provers, model checkers, deductive
> databases, .... Scalability?? Practioners find it hard to use
> logical formal languages, e.g., Z, Datalog, ....
>
> We have to carefully blend technologies with methodologies.
>
> A. Borgida ends:
> ================
>
> Towards other visions of data semantics (alter sem web vision)
>
> What does data semantics mean? New angles on the problem.
>
> The mapping continuum and semantic encapsulation. Intentional
> aspects of data semantics.
>
> mapping continuum and semantic encapsulation. Peter Ladkin 1997
> (what is modeling in general?). A model is a subject and built for
> some purpose (implicit, but important to keep track of). The purpose
> is often for answering questions of the model, so you don't have to
> of the subject. M is a model of subject S for a purpose P.
>
> *** This paper sounds very interesting! Must get.
>
> We need: methods for building and changing the model. asking and
> answering questions in the model. a mapping to help translate
> applicable qustions about the subject matter into questiosn about
> the model .A way to translate results of the query to the model to
> answers about the subject. University database to model enrollment.
> An interesing phenomena: the model becomes the reality (you aren't
> an employee if you aren't in the db).
>
> Typology of models: E-models (extensional), set-theoretic,
> relational e.g.; I-models (intensional), based on an entailment rel,
> e.g., ontos, schemas, but also equations; C-models (computational),
> query answering by running software, a simulation program (the
> queries mean the result of running the tool; like OWL-DL parsers
> ... the language is defined by the parsers)
>
> Terminology/intension (schema), Assertion/extension (specific
> individuals)
>
> Typology of subjects: Physical reality (tricky to define, see
> philosophy); human's perception of reality (better); Another
> Model!!! A database as a model of the conceptual model or ontology
> (of some domain). This makes it possible to make precise the
> mapping between model and subject.
>
> Study of mappings. Query languages are usually infinit. So mappings
> specified compositionally, at schema level. Form of mapping
> specifications (corespondences, GAV/LAV/GLAV) involving queries over
> the subject and the model. Correspondences between
> individuals. Translating the queries to answer them, via the
> mapping.
>
> A correspondence continuum (B.C. Smith 87). Consider: a photo of a
> landscape is a model of the landscape (its subject matter);
> photocopy of the photo is a model of a model of the landscape; a
> digitization of the photocopy, etc., etc. Mappings of mappings of
> mappings, ...
>
> Mapping graphs. the graph associated with each mapping continuum is
> acyclic and has one or more "roots".
>
> The complete meaning of data in a model includes "composition" of
> the mappings to the subject.
>
> Related work: data integration; ontology integration; model
> management; peer data management; data provenance. The novlety here
> is the emphasis of the semantic side, as opposed to the subject
> side (?)
>
> Whence mappings: Lineal mappings should be saved during
> design. Other mappings derived.
>
> View: Mappings between models. Mappings are easier to
> formalize/discover than the concepts. Instead of annotating things
> individual, define mappings and infer the semantics ... ?
>
> An intensional dimension of data semantics. Traditionally data
> semantics deals with "what (when)". You really need to understand
> "how" and "why". (How is the object used? Why was the data
> gathered?)
>
> Answers and intensions. Tropos +i*. Highly speculative. Actors,
> goals, and softgoals. Actors like Admin, Planning. Goal like
> determin incoming. Goals have clear success criteria. Softgoals
> aren't so, e.g., Maximize, Accurate (Determine Size). The design of
> goals is determined/explained by the softgoals. You can state how
> certain goals either positively/negatively contribute to softgoals.
> FormalTropos is a temporal logic language for defining this stuff, a
> formalized version of the diagrams shown in the
> presentation. Related work: Hippocratic databases [Agrawal02], why
> data provenance [Buneman], data semantics in systems involving
> workflows and processes.
>
> Conclusions (J. Mylopoulos): Data semantics will remain a core
> problem for databases with/without web technologies. Current semweb
> research address this with emph. on formal reasoning and
> expressiveness. Models and mappings critical research. Ultimately,
> the meaning of data needs to be tied down to the intentions of its
> designers and users.
>
> questions
> =========
>
> Val Tannen: Semantics is a religion. There is a continuum: what is
> semantic enough to be called semantic and what is not. It is in the
> eye of the beholder (i.e., the user). Claims that too much work on
> focusing on the complexity (the religion). The mathematics should be
> the real religion: precisesness, derive algorithms, etc. Claims Clio
> is a good example of getting from the religion.
>
>
> * DOGMA Framework
>
> LinkBase, a huge medical ontology for drugs
> An associated database, National Drig Code Directory
> RIDL (1979): constraint and conceptual update/query part ...
>
>
> * Context Mediation in the Semantic Web (COIN paper)
> --------------------------------------------------
> Stuart Madnick
>
> COIN: Focus on resolving semantic conflicts among heter. data
> sources
>
> SEMWEB: Focus on making web semantically clear
>
> COIN: system for semantic interop. among heter. sources, COINL based
> on FOL/Prolog, to model application ontology and context modifiers.
>
> Context Interchange Architecture (very cool)
>
> - Every source has a "Source Context"
>
> - Shared Ontologies (e.g., Meters and Feet are Lengths)
>
> - Receiver Context (assuming length is in Feet)
>
> - Conversion Libraries (meters to feet)
>
> - Context Mediator (mediates conversion libs, shared ontos, source
> context, receiver context) to do context transformation from
> Source to Receiver.
>
> Two sides of COIN:
>
> - OWL as COIN's application ontology representation
> - COIN as 'meta-ontology' for OWL ontology interoperability
> - RuleML for specifying transforms
>
> Design Approach
>
> - Preserve constraint programming engine in the eCOIN prototype
> - 3-tier approach: ECOIN unchanged, ontologies in OWL, converted
> to internal form
>
> Not available in OWL: COIN modifiers (special type of attribute,
> like it has currency, but any currency is okay)
>
> There is an internal working report on this stuff too.
>
> This is written in Prolog!!!
>
> Really need to look at this stuff.
>
> * Interesting Discussion with Alex Borgida and Stuart Madnick about
> data conversion
>
> It was mentioned that one can use concrete domains, n-ary predicates
> that are defined essentially outside the reasoner, so that the
> reasoner (such as fact) can "hand out" the reasoning task to handle
> the case. This is useful if, e.g., you want to use the reasoner to
> determine whether you need to do a transformation. Sounds like this
> stuff has been worked out in the literature; but is an interesting
> idea.
>
>
> * Kenneth Ross paper on Faceted Databases
> ---------------------------------------
>
> Faceted Hierarchies: entities in multiple classes. Invented by a
> Librarian in 20's. Entities can have attributes:
>
> Entity [ID]
> hasType [type]
> Context (type=context)
> Object (type=object) [category,location]
> Pot (category=pot) [capacity]
> ...
>
> Searching faceted databases
> Specify criteria from a variety of dimensions
> E-commerce: search desired values for one of color, price, size,
> etc.
> Answer set shrinks and can then be further searched
> Flamenco: database of images, classified in many dimensions
>
> Querying faceted databases
> Design query lang. to allow more complex queries
> Preserve "set of entities" abstraction
> Compositionality
> E.g., no joins
> Low data complexity
> Conceptually simple
> Implementation
> Trying to have a complete algebra: given a set of entities; return
> a set of entities
>
> Entity algebra
> Operators: Selection, Union, Diff, Intersection, Semijoin
> Entity sets may be heterogeneous: which attributes are avail?
>
> Attributes in Entity Algebra
> Compose queries one op at a time, using class and/or past query
> results
> At each step, teh system determines which atts are available
> Users do not have to figure this out themselves
>
> Queries with select, union, intersecct, are sound and complete.
> push selects to classes
> ... need to look at the paper ...
> decidable constraint language (e.g., constraint=constant, but can
> expand and does in paper)
>
> Used in an NSF-sponseored Archeological Project and a Human Anatomy
> Same infrastructure for both projects
> Presenation language separate from the query language
> You describe what you want to display of an attribute set
>
>
>
>
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