ACM-L: Active Conceptual Modeling of Learning

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Event When Where Deadline
ACM-L 2010 Third International Workshop on Active Conceptual Modeling of Learning
Nov 1, 2010 - Nov 4, 2010 Vancouver, BC, Canada Apr 28, 2010 (Apr 20, 2010)
ACM-L 2009 Second International Workshop on Active Conceptual Modeling of Learning
Nov 9, 2009 - Nov 12, 2009 Gramado, RS, Brazil May 15, 2009
 
 

Present CFP : 2010

Third International Workshop on
Active Conceptual Modeling of Learning
ACM-L 2010

Vancouver, BC, Canada, 1-4 November 2010
[to be held in conjunction with the 29th International Conference on
Conceptual Modeling, ER 2010]

http://www.er2010.sauder.ubc.ca/

http://www.cs.uta.fi/conferences/acm-l-2010/


Workshop Description and Call for Papers

We will study a framework for the active conceptual modeling of learning based on the
Entity-Relationship (ER) approach and human cognition paradigm for developing a learning-
base to support and develop complex applications, act on inevitable "surprises" and cognitive
capability development. The goal is to develop new technology for building computer
systems that help us learn from the past, cope with the present and plan for the future.

A need for active conceptual modeling for information systems rises from several sources:
active modeling, emergency management, learning from surprises, data provenance,
modification of the events/conditions/actions as the system evolves, actively evolving
conceptual models, schema changes in conceptual models, historical information in
conceptual models, ontological modeling in domain-aware systems, spatio-temporal and
multi-representation modeling, etc. The most important needs are perhaps emergency
management and learning from surprises, because they often appear in big disasters and
catastrophes. In these kinds of situations, information systems must collect large amounts raw
data, analyze it, conceptualize it, map it to the domain, distribute it, make conclusions, make
plans for new activities, and manage cooperation of active officials.

This effort aims to enhance our fundamental understanding of how to capture knowledge
from transitions between system states, model continual learning from past experiences, and
construct new interpretations on the basis of evolution of recognized system states.

Problem: The advent of information technology allows us to model the world by mapping
real-world scenarios onto information systems and applications in a more sophisticated way.
However, today's databases and knowledge bases only reflect the static characteristics of the
intended Universe of Discourse, captured by the conceptual model as distinct snapshots. The
information system, which provides us with "almost recent" information, neither supports
applications that require historical information nor provides information for projecting the
future based on past experience and lessons learned. Without the relationships between
snapshots, it is difficult to simulate the "what if" scenarios. Temporal and spatial
relationships between entity behaviors and uncertainty cannot be fully modeled. Temporal
concepts are not taken into account properly. Therefore, historical information and their
changes cannot be managed, and the certainty of information cannot be assessed. Inadequate
dynamic modeling constructs result in incomplete representation of the changing real-world
domain.

Approach: To achieve active information processing, learning from our past experience is
essential. Learning is a continuous process by which relatively permanent behavioral changes
occur, potentially as a result of an experience. Lessons learned are knowledge gained by
reflecting on experiences that can avoid the repetitions of past mishaps to share observations
and to improve future actions. While learning is an ongoing process that transfers knowledge
from one state to another, a lesson learned summarizes knowledge at a point in time. To
describe an experience is to model past events and associated knowledge from a different
perspective. The domain can be described in terms of topic, time/space, people,
scenarios/events, cause/effect and general knowledge about the situation or domain. Active
conceptual modeling is a continual process of describing all concepts and aspects of a domain,
its activities, and changes under different perspectives. The model is viewed as a multilevel
(e.g. strategic, tactical, operational) and multi-perspective high-level abstraction of reality.
Our effort focuses on relationships between past knowledge/data and current knowledge/data
from different perspectives. We propose a framework for active conceptual modeling of
learning.

Topics:

Technical Areas: Accomplishing our goal will require investigation of the following basic and
exploratory research areas. Some other relevant areas may also be found.
? Integrating time, space, and perspective dimensions in a theoretical framework of conceptual
models
- Theory of human concepts, human cognition
- ER theory
- Mathematical active conceptual models
- Multi-level conceptual modeling
- Multi-perspective conceptual modeling
- Multi-media information modeling
- Mapping of constructs among conceptual models

? Management of continuous changes and learning
- Conceptual change
- Continuous knowledge acquisition
- Experience modeling and management
- Learning from experience
- Representation and management of changes
- Transfer learning in time dimension
- Lessons learned capturing
- Information extraction, discovery, and summarization

? Behaviors of evolving systems ? including model evolution, patterns, interpretation,
uncertainty, integration
- Time and events in evolving systems
- Situation monitoring (system- and user-level)
- Schema evolution and version management
- Content awareness and context awareness
- Modeling of context changes
- Information integration and interpretation
- Pattern recognition over a time period
- Uncertainty management WRT integrity
- Reactive, proactive, adaptive, deductive capability in support of active behavior
- Combined episodic and semantic memory paradigm for structuring of historical
information

? Executable conceptual models for implementation of active systems
- Dynamic reserve modeling
- Storage management
- Security
- User interface
- Bench marking for Test & Evaluation
- Languages for information manipulation
- Architectures for information system based on the active conceptual model

Capability: The active model can only be realized by integrating technology (e.g. AI, software
engineering, information/knowledge management, cognitive science, philosophy, etc.) and
combining
modeling techniques. We will provide an enhanced situational awareness and monitoring
capability
through the following services ( See more: http://www.cs.uta.fi/conferences/acm-l-2010/):

Applications: The ACM-L capability can be applied to a large class of applications including
the
following ( See more: http://www.cs.uta.fi/conferences/acm-l-2010/):

Status: To begin framing the problem, SPAWARSYSCEN Pacific hosted two workshops on
ACM-L in 2006. The first event was held at SPAWARSYSCEN Pacific to introduce the
Science & Technology (S&T) Initiative and identify a Research and Development agenda for
the technology development investigation. The first open workshop was held at the 25th
International Conference on Conceptual Modeling, ER 2006, 6-9 November 2006, in Tucson,
Arizona. The second open workshop was held at the 28th International Conference on
Conceptual Modeling, ER 2009, 9-12 November 2009, in Gramado, Brazil.

Workshop deadlines.

Abstract Submission: April 20, 2010
Full Paper Submission: April 28, 2010
Author Notification: June 7, 2010
Camera-ready Paper Submission: June 30, 2010
Workshop: November 1-4, 2010

Formatting Guidelines

ACM-L 2010 proceedings will be part of the ER 2010 Workshop volume published by
Springer-Verlag in the LNCS series. Thus, authors must submit manuscripts using the
Springer-Verlag LNCS style for Lecture Notes in Computer Science. Refer to
http://www.springer.de/comp/lncs/authors.html for style files and details. Papers in the final
proceedings are strictly limited to 10 pages. Therefore, submitted papers should also not
exceed 10 pages, but technical appendices, e.g. containing proofs, can be added to a
submission.

Papers must be in English, formatted in LNCS style and submitted as PDF-files. Submitted
papers must be original and not submitted or accepted for publication in any other workshop,
conference, or journal.

Submission Guidelines

Submission to ACM-L 2010 will be by electronic mail, only, to all three workshop chairs to
addresses below, in PDF format, by the due date. All correspondence with authors will be via
e-mail, so please ensure that your submission includes an e-mail address for the
corresponding author.

Workshop chairs and their e-mail addresses:

Hannu Kangassalo; University of Tampere, Finland; hk at cs.uta.fi
Salvatore T. March; Vanderbilt University, U.S.A; Sal.March at owen.vanderbilt.edu
Leah Y Wong; SPAWARSYSCEN Pacific, U.S.A; leah.wong at navy.mil

PROGRAM COMMITTEE MEMBERS (to be extended)

Stefano Borgo, Laboratory for Applied Ontology, ISTC-CNR, Italy
Alfredo Cuzzocrea, University of Calabria, Italy
Giancarlo Guizzardi, Universidade Federal do Espirito Santo, Brazil
Raymond A Liuzzi, Raymond Technologies, USA
Jari Palom?ki, Tampere University of Technology/Pori, Finland
Oscar Pastor, Valencia University of Technology, Spain
Sudha Ram, University of Arizona, USA
Laura Spinsanti, LBD lab ? EPFL, Swizerland
Il-Yeol Song, Drexel University, USA
Bernhard Thalheim, Christian Albrechts University Kiel, Germany

 

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