KNUMS

First Workshop on Knowledge Management for Numerical Modeling, Measurement & Simulation

November 26-28, 2024, Amsterdam, Netherlands
(in conjunction with EKAW 2024)

Research on data and knowledge management has made much progress in recent years, culminating in best practices, widely-adopted standards and (commercial) systems for a wide range of applications. However, despite these advancements, many fields still face challenges in managing the knowledge about complex measurements and numerical models. These challenges span across a broad spectrum of disciplines, from engineering and natural sciences to sociology and economics, and extend to a variety of applications, including manufacturing, agriculture, medicine and public policy. In a wide range of domains, it remains difficult to keep track of the connection between measurement datasets and the physical processes that generate them, or the simulations that use them.

Recently, advancements in (Cognitive) Digital Twins (DTs) and Pre-trained Large Language Models (LLMs) have opened up new opportunities for managing model metadata and integrating diverse data sources, but progress and results are often shared only within their application domain.

Objectives and Topics

This workshop aims to bring together a diverse set of perspectives from different traditions and will attempt to establish common ground for how these various kinds of representation and processes might be integrated.

Potential topics include, but are not limited to:

  • Representing Measurement
    • Knowledge representation and management techniques for measurement datasets
    • Ontologies and semantic technologies for handling measurement data
    • Ontological representation of time series observations and their associated temporal concepts, e.g., events, situations, processes and temporal relations
    • Measurement data quality assurance and validation techniques in knowledge management systems (e.g. units, uncertainty, provenance)
    • Utilizing Large Language Models (LLMs) for knowledge extraction, management and metadata synthesis in measurement datasets
  • Numerical Modeling, Simulation and Knowledge Management
    • Integration of numerical modeling in knowledge management systems
    • Integration of ontologies in numerical modeling systems
    • Modularization and compositionality of numerical models
    • Equations and formulas management in knowledge repositories
    • Simulation data organization and retrieval strategies
    • Collaborative knowledge sharing platforms for numerical modeling and simulation communities
    • Knowledge management for uncertainty quantification in simulation data
    • FAIR numerical / simulation model sharing
  • Interdisciplinary and Application Perspectives
    • Interdisciplinary perspectives on knowledge management in numerical model / simulation studies
    • Case studies and applications demonstrating effective knowledge management practices in measurement datasets and numerical / simulation models

Important Dates

  • Paper submission deadline: September 17 September 24, 2024
  • Authors notification:October 15, 2024
  • Author registration: October 17, 2024
  • Workshop Day: November 26
  • Workshop camera-ready paper (for joint workshop proceedings volume): November 20, 2024

Submissions

The workshop will accept regular papers and short (position) papers. Pieces of ongoing research work are also welcome.

Papers must be submitted in PDF format according to the CEUR-WS template published in the CEUR-WS guidelines. Long papers should be between 10 and 15 pages, while short papers between 5 and 9 pages, including references. Workshop papers must be self-contained and in English.

Further, at least one author of each accepted workshop paper has to register for the conference. Please note that workshop attendance is only granted to registered conference participants.

Submissions should be made via EasyChair: https://easychair.org/conferences/?conf=knums2024

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