connecting and synchronizing scientific knowledge
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Prashant Gupta, Mark Gahegan and Gill Dobbie
The University of Auckland New Zealand
ConnecBng and synchronizing scienBfic knowledge
The current state of scienBfic pracBces
The current state of scienBfic pracBces
How well are we carrying forward the core principles of science (communicaBon, repeatability and refutability) with the new scienBfic pracBces?
Learning from the past
Learning from the past
Map
Categories
Learning from the past
Map
Categories
How do we connect them back to synthesize an integrated view ?
Knowledge producer and consumer perspecBve
Data Methods
Analysis Map
Workflow
Data model Knowledge producer
Knowledge producer and consumer perspecBve
Data Methods
Analysis Map
Workflow
Data model Knowledge producer
It’s very confusing. They are all disconnected. Hard to say how they were used. I wish they had some
explicit connecBons.
Knowledge consumer
FragmentaBon of scienBfic arBfacts and processes among communiBes
Community 2
Image processing tools
CSV/XML/database
Image processing
DigiBzed data
Community 1 Remote sensing
system
Data observaBon
Satellite Imagery
Concepts
Database
Community 4
ClassificaBon
Machine learning tool Land-‐cover dataset
Web-‐mapping tool
Taxonomy tool
Community 5
Land-‐cover map
Taxonomy
ApplicaBons
Community 3
Field work Aerial photography
Training data
CSV/XML/database
FragmentaBon of scienBfic arBfacts and processes among communiBes
Richer/beXer data
Community 2
Image processing tools
CSV/XML/database
Image processing
DigiBzed data
New validaBon techniques
Conceptual change
New ideas
Algorithmic improvement
Community 1 Remote sensing
system
Data observaBon
Satellite Imagery
Concepts
Database
Community 4
ClassificaBon
Machine learning tool Land-‐cover dataset
Web-‐mapping tool
Taxonomy tool
Community 5
Land-‐cover map
Taxonomy
ApplicaBons
Community 3
Field work Aerial photography
Training data
CSV/XML/database
New/beXer technology
State of knowledge integraBon
Data
Models
Articles
External Databases
http://www.seek4science.org
Metadata
http://www.isatools.org
Interlinking methods, models, data, samples..
Other knowledge integraBon models..
• Research Objects S. Bechhofer, D. De Roure, M. Gamble, C. Goble, and I. Buchan, “Research objects: Towards exchange and reuse of digital knowledge,” presented at The Future of the Web for CollaboraBve Science, NC, USA, 2010.
• Reproducible Research System J. P. Mesirov, “Accessible reproducible research,” Science, Jan. 2010.
• Linked Science T. Kauppinen and G. M. Espindola, “Linked open science communicaBng, sharing and evaluaBng data, methods and results for executable papers,” presented at the Int. Conf. ComputaBonal Science (ICCS), 2011.
• Workflows
Other knowledge integraBon models..
• Research Objects S. Bechhofer, D. De Roure, M. Gamble, C. Goble, and I. Buchan, “Research objects: Towards exchange and reuse of digital knowledge,” presented at The Future of the Web for CollaboraBve Science, NC, USA, 2010.
• Reproducible Research System J. P. Mesirov, “Accessible reproducible research,” Science, Jan. 2010.
• Linked Science T. Kauppinen and G. M. Espindola, “Linked open science communicaBng, sharing and evaluaBng data, methods and results for executable papers,” presented at the Int. Conf. ComputaBonal Science (ICCS), 2011.
• Workflows
What are the shortcomings?
• Focus on a single experiment of science, rather than science as an ongoing and evolving process
• Provide a linear view of science, but science is instead exploratory, dynamic and cyclic
• Focus typically on data and not on conceptual structures
A model that supports living and linked scienBfic knowledge
AssociaBonist view
A model that supports living and linked scienBfic knowledge
AssociaBonist view
Organic view – born, evolve and
die
ConnecBng scienBfic arBfacts
Data Database schema
Sogware tools
Categories Map Ontology
Live connecBons among scienBfic
arBfacts
Includes e-‐Science tools and process models
Example
Data Database schema
Sogware tools
Categories Map Ontology
1. If a new classifier method is used for land cover classificaBon, it may lead changes to categories
2. The extension of the category ‘Forest’ changes, leading to change in the data stored under that category.
3. Finally, the change in data is reflected in the land cover map
1
2
3
Adventures of Categories (AdvoCate)
• An e-‐Science tool that incorporates the process model of category evoluBon
• The system allows researchers to model changes in categories, captures the process of evoluBon and maintains a category-‐versioning system
• Connect changes in categories with the tools supporBng database and ontology evoluBon
Process model of category evoluBon
External change drivers
Revising categorical model
EvaluaBon of categorical model
Change approval
Change report (using elementary and complex
change operaBons)
ImplemenBng the changes & updaBng category versioning
system
Change PropagaBon
Process model of category evoluBon
External change drivers
Revising categorical model
EvaluaBon of categorical model
Change approval
Change report (using elementary and complex
change operaBons)
ImplemenBng the changes & updaBng category versioning
system
Change PropagaBon
• New observaBon (training data)
• Societal drivers • New understanding
• New category • Splikng or merging of
categories • Drig in categories
• Elementary changes: • Add/Delete category • Add/Delete relaBonship • Change label • Change intension
• Composite changes: • Born • Die • Merge • Split • Drig
Process model of category evoluBon
External change drivers
Revising categorical model
EvaluaBon of categorical model
Change approval
Change report (using elementary and complex
change operaBons)
ImplemenBng the changes & updaBng category versioning
system
Change PropagaBon
Ontology/database evoluBon tools
Process of science
Data model
An example of category evoluBon from land cover mapping
An example of category evoluBon from land cover mapping
An example of category evoluBon from land cover mapping
Future work
• Formalize data model using semanBc technologies
• Change recogniBon rules for various categories models (probability distribuBon models, rule-‐based models, etc.)
• VisualizaBon of categories evoluBon • Change broadcasBng service to ontology and database evoluBon tools
QuesBons ??