Instructors: Professor Deborah McGuinness and Professor Peter Fox
Meeting times: Monday afternoons 1:00 pm - 3:50; Winslow 1140
Office Hours: Tuesdays 11-12 in Winslow 2104
Class Listing: SEMANTIC E-SCIENCE CLASS WILL MEET IN WINSLOW BUILDING - 44775 - CSCI 6962 - 01 1:00 3:50PM McGuinness/ Fox
Science has fully entered a new mode of operation. E-science, defined as a
combination of science, informatics, computer science, cyberinfrastructure and
information technology is changing the way all of these disciplines
do both their individual and collaborative work.
Scientists are facing global problems of a magnitude, complexity and
interdisciplinary nature that progress is limited by a trained
and agile workforce.
At present, there is a lack formal training in the key cognitive and
skill areas that would enable graduates to become key participants
in e-science collaborations. The purpose is to teach methodologies,
and provide application experience and skill-sets in an
inter-disciplinary forum to students and interested participants.
As semantic technologies have been gaining momentum in various e-Science
areas (for example, W3C's new interest group for semantic web health care
and life science), it is important to offer semantic-based methodologies,
tools, middleware to facilitate scientific knowledge modeling, logical-based
hypothesis checking, semantic data integration and application composition,
integrated knowledge discovery and data analyzing for different e-Science
Partially influenced by the Artificial Intelligence community, the Semantic Web
researchers have largely focused on formal aspects of semantic representation
languages or general-purpose semantic application development, with inadequate
consideration of requirements from specific science areas. On the other hand,
general science researchers are growing ever more dependent on the web,
but they have no coherent agenda for exploring the emerging trends on the
semantic web technologies. It urgently requires the development of a multi-disciplinary field
to foster the growth and development of e-Science applications based on the
semantic technologies and related knowledge-based approaches.
Goals: to fill the gaps that are currently present in the integrative
nature of informatics for the translation of science into requirements
for the underlying and largely syntactic e-infrastructure.
Topics for Semantic e-Science/ Foundations:
- Semantic Methodologies
- Knowledge Representation for e-Science
- Ontology Engineering and Re-Use for e-Science
- Knowledge Integration for e-Science
- Semantic Data Integration
- Semantic Web Languages, Tools and Services
- Semantic Infrastructure and Architecture for e-Science
- Semantic Grid Middleware
- Ontology Evolution for e-Science
- Knowledge Management for e-Science
- e-Science Workflow Management
- Data life-cycle for e-Science
- Data Mining and Knowledge Discovery
Semantic Web Applications and Ontologies for:
- Semantic Web for Health Care and Life Science
- Semantic Web for Bio-Med-informatics
- Semantic Web for System and Integrated Biology
- Semantic Web for Sun, Earth, Environment and Climate
- Semantic Web for Chemistry, Physics and Astronomy
- Semantic Web for Engineering
- Semantic Web and Digital Libraries and Scientific Publications
Semantic e-Science Project options
- Configuration and Deployment of Semantic Virtual Observatories
- Oceanography, astronomy, geology
- Ontology Merging and Validation Test-bed
- Semantic Language and Tool Use and Evaluation
- Semantic eScience Implementation Evaluation
- Semantic Collaboration Case Studies
- Semantic Application Development and Demonstration
- Class 1: Monday, August 31
- NO CLASS on Labor Day September 7
- Class 2: Monday, September 14
- Class 3: Monday, September 21
- Class 4: Monday, September 28
- Class 5: Monday, October 5
- Class 6: TUESDAY, October 13
- Class 7: Monday, October 19
- No class: Monday, October 26
- Class 8: Monday, November 2
- Class 9: Monday November 9
- Class 10: Monday, November 16
- Class 11: Monday November 23
- Class 12: Monday November 30
- Class 13: Thursday December 10
For complete reading citation with link(s) to papers, see reference list below.
- Class 1: Introduction to e-Science and Semantic Web August 31, 2009
- reading: Ontologies 101, Semantic Web, e-Science, RDFS, OWL Guide, NYT article, Optional, Common Logic
- assignment 0: Introduction to e-Science and Semantic Web
- Class 2: Foundations I: September 14, 2009 Methodologies, Knowledge Representation
- reading: Semantic Web for the Working Ontologist (first few chapters). Alternate reading - OWL Pizzas.
- assignment 1: Representing Knowledge and Understanding Representations
- Class 3: Foundations II: Ontology Engineering September 21, 2009
- reading: Use Cases
- Class 4: Class exercise I: Use Case development September 28, 2009
- reading: Ontology Tool Summary, Pellet, OWL-S, SAWSDL, Wine Agent
- assignment 2: Use-case Driven Knowledge Encoding Part I
- reading: Ontology Evolution
- OWL-S editor tutorial http://owlseditor.semwebcentral.org/documents/tutorial.pdf
- OWL-S and WSDL references http://www.daml.org/services/owl-s/1.1/owl-s-wsdl.html
- CMAP download http://18.104.22.168/cmapdownload/coe/Web_Installersv411.b117/install.htm
- Class 6: Class Presentation I: Tuesday October 13, 2009 Use Cases - Part II of Assignment 2
- Class 7: Foundations IV: Ontology Evolution and Knowledge Management October 19, 2009
- reading: no new reading - use case preparation
- Class 8: Class exercise II: Use Case Implementation November 2, 2009
- reading: IAAI VSTO, Semantic eScience Web Services, Computers and Geoscience
- assignment 3: Team Use Case Implementation
- Class 9: Foundations V: Infrastructure and Architecture, Middleware November 9, 2009
- Class 10: Class exercise III: Application Project Evaluation November 16, 2009
- additional material: Summative versus Formative evaluation
- additional material: Example of evaluation
- additional material: Template example for Evaluation
- reading: semantic integration
- Class 11: Class Presentation II: Team Use Case Implementation, November 23, 2009
- reading: no new reading
- Term assignment: Use Case: Iterating and Evolving, Lessons Learned;
- Class 12: Foundations VI: Discovery, Access and Semantic Integration and Foundations VII: Data Mining and Knowledge Discovery .
Extra Slides November 30, 2009
- reading: Provenance/ PML
- Class 13: Class Presentation III: Term assignment - Project Outcome, December 10, 1PM, 2009
Student-teacher relationships are built on trust. For example, students must trust that teachers have made appropriate decisions about the structure and content of the courses they teach, and teachers must trust that the assignments that students turn in are their own. Acts, which violate this trust, undermine the educational process. The Rensselaer Handbook of Student Rights and Responsibilities defines various forms of Academic Dishonesty and you should make yourself familiar with these. In this class, all assignments that are turned in for a grade must represent the student’s own work. In cases where help was received, or teamwork was allowed, a notation on the assignment should indicate your collaboration. Submission of any assignment that is in violation of this policy will result in a penalty.
If found in violation of the academic dishonesty policy, students may be subject to two types of penalties. The instructor administers an academic (grade) penalty, and the student may also enter the Institute judicial process and be subject to such additional sanctions as: warning, probation, suspension, expulsion, and alternative actions as defined in the current Handbook of Student Rights and Responsibilities.
of an academic grade penalty or . If you have any question concerning this policy before submitting an assignment, please ask for clarification.
Course Learning Objective
- Ontology Development, Merging and Validation
- Semantic Language and Tool Use and Evaluation
- Use Case Development and Elaboration
- Semantic eScience Implementation and Evaluation via Use Cases
- Semantic Application Development and Demonstration
- Group Project and Team Development, Use Case Implementation and Evaluation
- Via written assignments with specific percentage of grade allocation provided with each assignment
- Via oral presentations with specific percentage of grade allocation provided
- Via group presentations
- Via participation in class (not to exceed 10% of total)
- Late submission policy: first time with valid reason – no penalty, otherwise 20% of score deducted each late day
- Knowledge such as that gained in a Semantic Web class (e.g., CSCI-6961)
- Knowledge such as that gained in a Web Science class (e.g., CSCI-xx)
- or permission of the instructors
Class 1 Reading Assignment:
- [Ontologies 101] Natalya F. Noy and Deborah L. McGuinness. Ontology Development 101: A Guide to Creating Your First Ontology. Stanford Knowledge Systems Laboratory Technical Report KSL-01-05 and Stanford Medical Informatics Technical Report SMI-2001-0880, March 2001.
- Semantic Web:
- T Berners-Lee, J Hendler, O Lassila. The Semantic Web. Scientific American, 2001. alternative link - http://www.si.umich.edu/~rfrost/courses/si110/readings/in_out_and_beyond/semantic_web.pdf
- Grigoris Antoniou and Frank van Harmelen. Semantic Web Primer
- e-Science: Hey, T., and Trefethen, A. Cyberinfrastructure for e-Science. Science 308, 5723 (2005), 817–821.
- RDFS: RDF Vocabulary Description Language 1.0: RDF Schema. World Wide Web Consortium (W3C) Recommendation. February 10, 2004.
- [OWL Guide] Michael K. Smith, Chris Welty, and Deborah L. McGuinness. OWL Web Ontology Language Guide. World Wide Web Consortium (W3C) Recommendation. February 10, 2004.
- (Optional) Common Logic: John Sowa, Common Logic Controlled English, March, 2007. (The previous link is an updated Section 7 of (the full) Common Logic Controlled English draft.)
Class 2: Reading Assignment:
- Semantic Web for the Working Ontologist (Allemang and Henderl), first few chapters.
We are not aware of any online availability of the book but one can buy it from Amazon or elsewhere.
Alternate reading -
- Alan Rector, Nick Drummond, Matthew Horridge, Jeremy Rogers, Holger Knublauch, Robert Stevens, Hai Wang, Chris Wroe. OWL Pizzas: Practical Experience of Teaching OWL-DL: Common Errors & Common Patterns. EKAW 2004. http://www.co-ode.org/resources/papers/ekaw2004.pdf
- Optional McGuinness, D.L. Ontologies come of age, http://www.ksl.stanford.edu/people/dlm/papers/ontologies-come-of-age-abstract.html
Class 3: Reading Assignment:
- Use Cases:
- http://en.wikipedia.org/wiki/Use_case ,
- RDFS: http://www.w3.org/TR/rdf-schema/
Class 4: Reading Assignment:
- Ontology Tool Summary: Michael Denny. Ontology Tools Survey, Revisited. XML.com
- Pellet: web page: http://www.mindswap.org/2003/pellet/
- Pellet: Evren Sirin and Bijan Parsia and Bernardo Cuenca Grau and Aditya Kalyanpur and Yarden Katz, Pellet: a practical owl-dl reasoner. Journal of Web Semantics. http://www.mindswap.org/papers/PelletJWS.pdf
- OWL-S: David Martin, Mark Burstein, Drew McDermott, Deborah L. McGuinness, Sheila McIlraith, Massimo Paolucci, Evren Sirin, Naveen Srinivasan, and Katia Sycara. Bringing Semantics to Web Services with OWL-S. World Wide Web Journal, Volume 10, Number 3, pp 243-277. Also, Stanford KSL Technical Report KSL-06-21.
- SAWSDL: Semantic Annotation of the Web Services Description Language
- Wine Agent:
- * Eric Hsu, and Deborah L. McGuinness. KSL Wine Agent: Semantic Web Testbed Application, Proceedings of the 2003 International Workshop on Description Logics (DL2003). Rome, Italy, September 5-7, 2003.
- * James Michaelis, Li Ding, Deborah McGuinness. The TW Wine Agent A Social Semantic Web Demo. ISWC 2008 Poster and Demo Track, 2008.
Class 5: Reading Assignment:
- [Ontology Evolution] Deborah L. McGuinness, Richard Fikes, James Rice, and Steve Wilder.
An Environment for Merging and Testing Large Ontologies. In Proceedings of the 7th International Conference on Principles of Knowledge Representation and Reasoning (KR2000), Breckenridge, Colorado, USA 12-15 April 2000
- Aseem Das, Wei Wu, and Deborah L. McGuinness. ``Industrial Strength Ontology Management. Stanford Knowledge Systems Laboratory Technical Report KSL-01-09 2001. In the Proceedings of the International Semantic Web Working Symposium. Stanford, CA, July 2001. Also published in In Isabel Cruz, Stefan Decker, Jerome Euzenat, and Deborah L. McGuinness, eds. The Emerging Semantic Web. (Book available from http://www.iospress.nl/site/html/boek-1381825766.html). IOS Press, 2002.
- Prompt - http://protege.cim3.net/cgi-bin/wiki.pl?Prompt
Class 6: Reading Assignment:
Class 7: Reading Assignment:
Class 8: Reading Assignment:
- [IAAI VSTO] Deborah McGuinness, Peter Fox, Luca Cinquini, Patrick West, Jose Garcia, James L. Benedict, and Don Middleton. The Virtual Solar-Terrestrial Observatory: A Deployed Semantic Web Application Case Study for Scientific Research. In the Proceedings of the Nineteenth Conference on Innovative Applications of Artificial Intelligence (IAAI-07). Vancouver, British Columbia, Canada, July 22-26, 2007.
- [Semantic eScience Web Services] Peter Fox, Luca Cinquini, Deborah L. McGuinness, Patrick West, Jose Garcia, James L. Benedict and Steph an Zednik. Semantic web services for interdisciplinary scientific data query and retrieval. In the Proceedings of the Semantic eScience Workshop co-located with the Association for the Advancement of Artificial Intelligence Conference, Vancouver, CA., July 23, 2007.
- P. Fox, D. McGuinness, L. Cinquini, P. West, J. Garcia, and J. Benedict 2008, Ontology-supported Scientific Data Frameworks: The Virtual Solar-Terrestrial Observatory Experience, Computers and Geosciences, special issue on Geoscience Knowledge Representation for Cyberinfrastructure, in press.
Class 9: Reading Assignment:
- Evaluation: Twidale, M., Randall, D. and Bentley, R. 1994,Situated evaluation for cooperative systems, Proceedings, Comp. Supp. Coop. Work 1994, Chapel Hill, NC, pp. 441-452.
Class 10: Reading Assignment:
- Fox, P.; McGuinness, D.L.; Raskin, R.; Sinha, K. A Volcano Erupts: Semantically Mediated Integration of Heterogeneous Volcanic and Atmospheric Data. Proceedings of the First Workshop on Cyberinfrastructure: Information Management in eScience, co-located with the ACM Conference on Information and Knowledge Management, Lisbon, Portugal, November 9, 2007. ftp://ftp.ksl.stanford.edu/pub/KSL_Reports/KSL-07-09.pdf
- Sunil Movva, Rahul Ramachandran, Xiang Li, Phani Cherukuri, Sara Graves. Noesis: A Semantic Search Engine and Resource Aggregator for Atmospheric Science. NSTC2007. http://esto.nasa.gov/conferences/nstc2007/papers/Ramachandran_Rahul_A3P4_NSTC-07-0084.pdf
- Boyan Brodaric and Florian Probst. Enabling Cross-Disciplinary e-Science by Integrating Geoscience Ontologies with DOLCE. Under Review. 2008.
- Yolanda Gil, Ewa Deelman, Mark Ellisman, Thomas Fahringer, Geoffrey Fox, Dennis Gannon, Carole Goble, Miron Livny, Luc Moreau, Jim Myers, "Examining the Challenges of Scientific Workflows," Computer , vol. 40, no. 12, pp. 24-32, December, 2007. http://www.isi.edu/~gil/papers/computer-NSFworkflows07.pdf
Class 11: Reading Assignment: none
Class 12: Reading Assignment:
- PML -McGuinness, Ding, Pinheiro da Silva, Chang. PML 2: A Modular Explanation Interlingua. AAAI 2007 Workshop on Explanation-aware Computing, Vancouver, Can., 7/07. Stanford Tech report KSL-07-07. http://www.ksl.stanford.edu/KSL_Abstracts/KSL-07-07.html
- Inference Web - McGuinness and Pinheiro da Silva. Explaining Answers from the Semantic Web: The Inference Web Approach. Web Semantics: Science, Services and Agents on the World Wide Web Special issue: International Semantic Web Conference 2003 - Edited by K.Sycara and J.Mylopoulis. Volume 1, Issue 4. Journal published Fall, 2004 http://www.ksl.stanford.edu/KSL_Abstracts/KSL-04-03.html
- McGuinness, D.L.; Zeng, H.; Pinheiro da Silva, P.; Ding, L.; Narayanan, D.; Bhaowal, M. Investigations into Trust for Collaborative Information Repositories: A Wikipedia Case Study. The Workshop on the Models of Trust for the Web (MTW'06), Edinburgh, Scotland, May 22, 2006. 2006. http://www.ksl.stanford.edu/KSL_Abstracts/KSL-06-05.html
Class 13: Reading Assignment: None.
Enrolled students may miss at most one class without permission of the instructor.
Course: Semantic eScience