Abstract

Semantic Provenance: Modeling, Querying, and Application in Scientific Discovery Provenance metadata, describing the history or lineage of an entity, is essential for ensuring data quality, correctness of process execution, and computing trust values. Traditionally, provenance management issues have been dealt with in the context of workflow or relational database systems. However, existing provenance systems are inadequate to address the requirements of an emerging set of applications in the new eScience or Cyberinfrastructure paradigm and the Semantic Web. Provenance in these applications incorporates complex domain semantics on a large scale with a variety of uses, including accurate interpretation by software agents, trustworthy data integration, reproducibility, attribution for commercial or legal applications, and trust computation. In this dissertation, we introduce the notion of 'semantic provenance' to address these requirements for eScience and Semantic Web applications. In addition, we describe a framework for management of semantic provenance by addressing the three issues of, (a) provenance representation, (b) query & analysis, and (c) scalable implementation. First, we introduce a foundational model of provenance called Provenir to serve as an upper-level reference ontology to facilitate provenance interoperability. Second, we define a classification scheme for provenance queries based on the query characteristics and use this scheme to define a set of specialized provenance query operators. Third, we describe the implementation of a highly scalable query engine to support the provenance query operators, which uses a new class of materialized views based on the Provenir ontology, called Materialized Provenance Views (MPV), for query optimization. We also define a novel provenance tracking approach called Provenance Context Entity (PaCE) for the Resource Description Framework (RDF) model used in Semantic Web applications. PaCE, defined in terms of the Provenir ontology, is an effective and scalable approach for RDF provenance tracking in comparison to the currently used RDF reification vocabulary. Finally, we describe the application of the semantic provenance framework in biomedical and oceanography research projects.

Slideshow

Committee Members

Amit P. Sheth, Ph.D. (Advisor)	Krishnaprasad Thirunarayan, Ph.D.	Michael Raymer Ph.D.
Nicholas V. Reo, Ph.D.	Olivier Bodenreider, Ph.D.	William S. York, Ph.D.

Publications

Presentation

Satya S. Sahoo, “Glycomics Project Overview,”presentation, Kno.e.sis Center, February 2007.

Satya Sahoo, “Semantics and Services enabled Problem Solving Environment for Trypanosoma cruzi, ”NIH RO1 grant (collaborations with NCBO), Knoesis Center presentation, January 25, 2008

Cory Henson and Satya Sahoo, 'Sensor Networks Survey,' presention, daytaOhio, May 2007.

TechnicalReport

Satya S. Sahoo, Roger S. Barga, Jonathan Goldstein,Amit Sheth, 'Provenance Algebra and Materialized View-based Provenance Management, Microsoft Research Technical Report, (MSR-TR-2008-170) November 2008

Satya S. Sahoo, Krishnaprasad Thirunarayan, 'Tableau Algorithm for Concept Satisfiability in Description Logic ALCH', Kno.e.sis Center Technical Report knoesis-TR-2009-07, July, 2009

Satya S. Sahoo, Roger S. Barga, Amit P. Sheth, K. Thirunarayan, Pascal Hitzler, 'PrOM: A Semantic Web Framework for Provenance Management in Science,' Kno.e.sis Center Technical Report KNOESIS-TR-2009, 2009.

Amir H. Asiaee, Prashant Doshi, Todd Minning, Satya Sahoo, Priti Parikh, Amit Sheth, and Rick L. Tarleton. From Questions to Effective Answers: On the Utility of Knowledge-Driven Querying Systems for Life Sciences Data, Kno.e.sis Center Technical Report 2010.

Book Series

Boanerges Aleman-Meza, Christian Halaschek-Wiener, Satya Sanket Sahoo, Amit P. Sheth, and Ismailcem Budak Arpinar (Eds.), Template Based Semantic Similarity for Security Applications, Lecture Notes in Computer Science, Vol. 3495, Springer, April 2005, pp. 621–622.

Book Chapter

Satya Sahoo, Amit P Sheth, B. Hunter, and W. York, 'Semantic Biological Web Services Registry,'in Semantic Web: Revolutionizing Knowledge Discovery in the Life Sciences, Christopher Baker and Kei-Hoi Cheung (Eds.), Springer, 2007.

Satya Sanket Sahoo, Amit P. Sheth, Blake Hunter, and William S. York, 'SemBOWSER-Semantic Biological Web Services Registry,'in Semantic Web: Revolutionizing Knowledge Discovery in the Life Sciences, Christopher J.O. Baker and Kei-Hoi Cheung (Eds.), New York: Springer, 2007, pp. 317-340.

PhDThesis

Satya S. Sahoo, Semantic Provenance: Modeling, Querying, and Application in Scientific Discovery, Ph.D. Thesis, Wright State University, 2010

Poster

Amit Sheth (PI),Rick Tarleton,Prashant Doshi,Mark Musen,Natasha Noy,Satya Sahoo,D. Brent Weatherly and Pablo Mendes. 'Collaborative R01 with NCBO Semantics and Services Enabled Problem Solving Environment For Trypanosoma Cruzi'. Poster, 2008

Conference Poster

Ashwin Manjunatha, Paul Anderson, Satya S. Sahoo, Ajith Ranabahu, Michael Raymer and Amit Sheth, 'Semantically Annotated RESTful Services for Large-scale Metabolomics Data Analysis', Conference Poster, Ohio Collaborative Conference on Bioinformatics 2010, Columbus, Ohio, June 15-17, 2010

Ashwin Manjunatha, Ajith Ranabahu, Paul Anderson, Satya S. Sahoo, Michael Raymer and Amit Sheth, Cloud Based Scientific Workflow for NMR Data Analysis, Conference Poster, 18th Annual International Conference on Intelligent Systems for Molecular Biology, Boston MA, July 11-13, 2010

Vinh Nguyen, Satya Sahoo, Priti Parikh, Todd Minning, Brent Weatherly, Flora Logan, Amit Sheth, Rick Tarleton, 'Biomedical Ontologies for Parasite Research', ISMB, Boston, 11-13 July 2010.

Pramod Anantharam, Satya S. Sahoo, D. Brent Weatherly, Flora Logan, Raghava Mutharaju, Amit P. Sheth, Rick Tarleton. Trykipedia: Collaborative Bio- Ontology Development using Wiki Environment. Ohio Collaborative Conference on BioInformatics (OCCBIO 2009), June 14-17, 2009.

ConferencePaper

Satya S. Sahoo, Christopher Thomas, Amit P. Sheth, William York, and Samir Tartir, 'Knowledge Modeling and Its Application in Life Sciences: A Tale of Two Ontologies,'15th International World Wide Web Conference (WWW2006), Edinburgh, Scotland, May 23-26, 2006.

Satya S. Sahoo, Kelly Zeng, Olivier Bodenreider, and Amit P. Sheth, 'From 'Glycosyltransferase'to 'Congenital Muscular Dystrophy': Integrating Knowledge from NCBI Entrez Gene and the Gene Ontology,' in MEDINFO 2007: Proceedings of the 12th World Congress on Health (Medical) Informatics, K.A. Kuhn, J.R. Warren, T.-Y. Leong (Eds.), Studies in Health Technology and Informatics, Vol. 129, Amsterdam: IOS, August 2007, pp. 1260-04. PMID: 17911917

Satya S. Sahoo, D. Brent Weatherly, Raghava Mutharaju, Pramod Anantharam,Amit Sheth, Rick L. Tarleton 'Ontology-driven Provenance Management in eScience: An Application in Parasite Research,' OnTheMove Federated Conferences & Workshops (OTM 2009) - ODBASE'09, Vilamoura, Algarve-Portugal, Nov 03 - 04 - 05, 2009, pp. 992-1009.

Satya S. Sahoo, Amit P. Sheth, William S. York, and John A. Miller, 'Semantic Web Services for N-glycosylation Process,' International Symposium on Web Services for Computational Biology and Bioinformatics, Blacksburg, VA, May 25-27, 2005.

Satya S. Sahoo, Olivier Bodenreider, Pascal Hitzler, Amit Sheth, and Krishnaprasad Thirunarayan, 'Provenance Context Entity (PaCE): Scalable Provenance Tracking for Scientific RDF Data,' In Proceedings of the 22nd International Conference on Scientific and Statistical Database Management (SSDBM'10), Michael Gertz and Bertram Ludascher (Eds.). Springer-Verlag, Berlin, Heidelberg, 461-470.

WorkshopPaper

Satya S. Sahoo, Olivier Bodenreider, Kelly Zeng, and Amit P. Sheth, “An experiment in integrating large biomedical knowledge resources with RDF: Application to associating genotype and phenotype information,”workshop paper, Workshop on Health Care and Life Sciences Data Integration for the Semantic Web at WWW2007, 2007.

Matthew D. Valerio, Satya S. Sahoo, Roger S. Barga, Jared J. Jackson, 'Capturing Workflow Event Data for Monitoring, Performance Analysis, and Management of Scientific Workflows', SWBES08 Workshop in conjunction with IEEE International Conference on e-Science 2008, Indianapolis, Indiana, Dec 10, 2008.

S. Sahoo, M. Raymer, C. Henson, A. Sheth and W. York (2008) Ontology driven Semantic Provenance for Heterogeneous Bionomics Experimental Data. Oral presentation at the Ohio Collaborative Conference on Bioinformatics (OCCBIO), University of Toledo, OH, July 2008.

Amit Sheth, William York, Christopher Thomas, Meenakshi Nagarajan, John A. Miller, Krys Kochut, Satya Sahoo, and Xiaochuan Yi, “Semantic Web technology in support of Bioinformatics for Glycan Expression,” W3C Workshop on Semantic Web for Life Sciences, Cambridge, MA, October 27–28, 2004.

Satya S. Sahoo, Amit Sheth, 'Provenir ontology: Towards a Framework for eScience Provenance Management', Microsoft eScience Workshop, Pittsburgh, PA Oct 15-17, 2009

Harshal Patni, Satya S. Sahoo, Cory Henson and Amit Sheth, 'Provenance Aware Linked Sensor Data', 2nd Workshop on Trust and Privacy on the Social and Semantic Web, Co-located with ESWC, Heraklion Greece, 30th May - 03 June 2010

Paolo Missier, Satya S Sahoo, Jun Zhao, Carole Goble, Amit Sheth (2010) Janus: from Workflows to Semantic Provenance and Linked Open Data. In Procs. The 3rd International Provenance and Annotation Workshop,Troy NY, USA, June 15-16, 2010

Journal Article

Satya S. Sahoo, Christopher Thomas, Amit P. Sheth, Cory Henson, and William S. York, 'GLYDE—An expressive XML standard for the representation of glycan structure,'Carbohydr Res, 340 (no. 18), December 30, 2005. pp. 2802–2807. Epub 2005 Oct 20. PMID: 16242678.

Satya S. Sahoo, Olivier Bodenreider, Joni L. Rutter, Karen J. Skinner, and Amit P. Sheth, 'An Ontology-Driven Semantic Mash-up of Gene and Biological Pathway Information: Application to the Domain of Nicotine Dependencem,'special issue: Semantic Biomedical Mashups Journal of Biomedical Informatics, 41 (5), October 2008, pp.752-765.PMID: 18395495

Amit Sheth, Cory Henson, and Satya Sahoo, 'Semantic Sensor Web,' IEEE Internet Computing, July/August 2008, p. 78-83.

Satya S. Sahoo,Amit Sheth, and Cory Henson, 'Semantic Provenance for eScience: Managing the Deluge of Scientific Data', IEEE Internet Computing, vol. 12, no. 4, 2008, pp. 46-54.

J.A. Atwood III, S.S. Sahoo, G. Alvarez-Manilla, D.B. Weatherly, K. Kolli, R. Orlando, and S. York, “Simple modification of a protein database for mass spectral identification of N-linked glycopeptides,” Rapid Commun Mass Spectrom, 19 (no. 21), 2005, pp. 3002–06. PMID: 16196021.

Jun Zhao, Satya S. Sahoo, Paolo Missier, Amit Sheth, Carole Goble, 'Extending Semantic Provenance into the Web of Data,' IEEE Internet Computing, vol. 15, no. 1, pp. 40-48, Jan./Feb. 2011, doi:10.1109/MIC.2011.7

Satya S. Sahoo, Vinh Nguyen, Olivier Bodenreider, Priti Parikh, Todd Minning, Amit P. Sheth. 'A Unified Framework for Managing Provenance Information in Translational Research.' BMC Bioinformatics 2011, 12:461 doi:10.1186/1471-2105-12-461. PMID: 22126369 [Highly Accessed]

Priti P. Parikh, Todd A. Minning, Vinh Nguyen, Sarasi Lalithsena, Amir H. Asiaee, Satya S. Sahoo, Prashant Doshi, Rick Tarleton, and Amit P. Sheth. '“A Semantic Problem Solving Environment for Integrative Parasite Research: Identification of Intervention Targets for Trypanosoma cruzi.” PLoS Negl Trop Dis 6(1): e1458. doi:10.1371/journal.pntd.0001458, 2012. PMID: 22272365

Panel Presentation

Satya S. Sahoo, “RDB2RDF: Incorporating Domain Semantics in Structured Data,”W3C RDB2RDF Incubator Group, April 11, 2008

Abstract

Over the last few years, there has been a growing public and enterprise fascination with <91>social media<92> and its role in modern society. At the heart of this fascination is the ability for users to participate, collaborate, consume, create and share content via a variety of platforms such as blogs, micro-blogs, email, instant messaging services, social network services, collaborative wikis, social bookmarking sites, and multimedia sharing sites. Today, in addition to any factual information, we are also able to access conversations, opinions and emotions that these facts evoke among other users. We are able to ask questions such as, what are people saying about any news-worthy event or entity? Can we use this information to assess a population<92>s preference? Can we study how these preferences propagate in a network of friends? Are such crowd-sourced preferences a good substitute for traditional polling methods?This dissertation is devoted to understanding informal user-generated textual content on social media platforms and using the results of the analysis to build Social Intelligence Applications.The body of research presented in this thesis focuses on understanding what a piece of user- generated content is <91>About<92> via two sub-goals of Named Entity Recognition and Key Phrase Ex- traction on informal text. In light of the poor context and informal nature of content on social media platforms, we investigate the role of contextual information from documents, domain mod- els and the social medium to supplement and improve the reliability and performance of existing text mining algorithms for Named Entity Recognition and Key Phrase Extraction.In all cases we find that using multiple contextual cues together lends to reliable inter-dependent decisions, better than using the cues in isolation and that such improvements are robust across domains and content of varying characteristics, from micro-blogs like Twitter, social networking forums such as those on MySpace and Facebook, and blogs on the Web.Finally, we showcase two deployed Social Intelligence applications that build over the results of Named Entity Recognition and Key Phrase Extraction algorithms to provide near real-time information about the pulse of an online populace. Specifically, we describe what it takes to build applications that wish to exploit the <91>wisdom of the crowds<92> <96> highlighting challenges in data collection, processing informal English text, metadata extraction and presentation of the resulting information.

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Video

Committee Members

Amit P. Sheth, Ph.D. (Advisor)	John M. Flach Ph.D.	Daniel Gruhl Ph.D.
Michael L. Raymer, Ph.D.	Shaojun Wang, Ph.D.	Kevin Haas, M.S.

Convocation

Publications

Presentation

Meenakshi Nagarajan, “Data Integration ,” presentation, Kno.e.sis Center, 2007.

TechnicalReport

Meenakshi Nagarajan, Kamal Baid,Amit Sheth, Shaojun Wang, Monetizing User Activity on Social Networks, Technical Report, 2008

Meenakshi Nagarajan, Kamal Baid,Amit Sheth, Shaojun Wang, Targeted Content Delivery for Social Media Content, Technical Report, 2008

Rama Akkiraju, Joel Farrell, John A Miller, Meenakshi Nagarajan, Amit P Sheth, and Kunal Verma, 'Web Service Semantics-WSDL-S,'Technical Note, IBM Research and LSDIS Lab, University of Georgia, April 2005.

Julia Grace, Daniel Gruhl, Kevin Haas, Meenakshi Nagarajan, Christine Robson, and Nachiketa Sahoo, 'Artist Ranking through Analysis of Online Community Comments,'technical report, IBM Almaden, 2008.

Lu Chen, Wenbo Wang, Meenakshi Nagarajan, Shaojun Wang and Amit P. Sheth. Beyond Positive/Negative Classification: Automatic Extraction of Sentiment Clues from Microblogs. Kno.e.sis Center Technical Report 2011.

KeynoteTalk

Meenakshi Nagarajan, User-Generated Content on Social Media Challenges, Opportunities, Keynote Talk, Social Data on the Web Workshop, collocated with the International Semantic Web Conference, 2009

Book Chapter

Meenakshi Nagarajan, “Semantic Annotations in Web Services,”in Semantic Web Services, Processes and Applications, Jose Cardoso and Amit P. Sheth (Eds.), Springer, August 2006.

PhDThesis

Meenakshi Nagarajan, Understanding User-Generated Content on Social Media, Ph.D. Dissertation, Wright State University, 2010

Conference Poster

Meenakshi Nagarajan, Marti A. Hearst. An Examination of Language Use in Online Dating Personals, 3rd Int'l AAAI Conference on Weblogs and Social Media, ICWSM 2009: 266-269

Meenakshi Nagarajan,Amit Sheth, Marcos Aguilera, Kimberly Keeton, Arif Merchant, and Mustafa Uysal, 'Altering Document Term Vectors for Classification-Ontologies as Expectations of Co-occurrence,'16th World Wide Web Conference (WWW2007), 1225-1226, Banff, Canada, May 8-12, 2007.

Meenakshi Nagarajan, Hemant Purohit, Amit Sheth. A Qualitative Examination of Topical Tweet and Retweet Practices. 4th Int'l AAAI Conference on Weblogs and Social Media, ICWSM 2010, pp. 295-298.

ConferencePaper

Boanerges Aleman-Meza, Meenakshi Nagarajan, Cartic Ramakrishnan, Li Ding, Pranam Kolari, Amit P. Sheth, Ismailcem Budak Arpinar, Anupam Joshi, Tim Finin: Semantic analytics on social networks: experiences in addressing the problem of conflict of interest detection. WWW 2006, New York: ACM Press, 2006, pp. 407-416.

Meenakshi Nagarajan, Kunal Verma, Amit P. Sheth, John A. Miller, andJonathan Lathem, 'Semantic Interoperability of Web Services-Challenges and Experiences,'IEEE International Conference on Web Services (ICWS'06), Chicago, IL, September 18-22, 2006, Proceedings, IEEE Computer Society, 2006, pp. 373-382. ISBN:0-7695-2669-1

A. Alba, V. Bhagwan, J. Grace, D. Gruhl, K. Haas, M. Nagarajan, J. Pieper, C. Robson, and N. Sahoo, 'Applications of Voting Theory to Information Mashups' in Proceedings of the 2nd IEEE International Conference on Semantic Computing, 10-17, Santa Clara, CA, August 4-7, 2008.

Meenakshi Nagarajan, Karthik Gomadam, Amit Sheth, Ajith Ranabahu, Raghava Mutharaju and Ashutosh Jadhav, 'Spatio-Temporal-Thematic Analysis of Citizen-Sensor Data - Challenges and Experiences,' Tenth International Conference on Web Information Systems Engineering, October 5-7, 2009, 539 - 553.

Meenakshi Nagarajan, Kamal Baid, Amit P. Sheth, and Shaojun Wang, 'Monetizing User Activity on Social Networks - Challenges and Experiences', 2009 IEEE/WIC/ACM International Conference on Web Intelligence, 92-99, Sep 15-18 2009, Milan, Italy.

Karthik Gomadam, Ajith Ranabahu, Meenakshi Nagarajan, Amit. P. Sheth and Kunal Verma, 'A Faceted Classification Based Approach to Search and Rank Web APIs', In Proceedings of 6th IEEE International Conference on Web Services (ICWS), 177-184, Beijing, China, Sep. 2008

Daniel Gruhl, Meenakshi Nagarajan, Jan Pieper,Christine Robson, Amit Sheth, 'Context and Domain Enhanced Entity Spotting in Informal Text,' The Semantic Web - ISWC 2009, Proceedings of 8th International Semantic Web Conference (ISWC 2009), Chantilly, VA, USA, October 25-29 , 2009, pp. 260-276.

WorkshopPaper

William S. York, Amit P. Sheth, Krzysztof J. Kochut, John A. Miller, Christopher Thomas, Karthik Gomadam, X. Yi, and Meenakshi Nagarajan, “Semantic Integration of Glycomics Data and Information,” Human Disease Glycomics/Proteome Initiative 1st Workshop 2004: Functional Glycomics in Disease, Osaka, Japan, 2004.

R. Akkiraju, J. Farrell, J.Miller, M. Nagarajan, M. Schmidt, A. Sheth, and K. Verma, 'Web Service Semantics - WSDL-S,'workshop paper, W3C Workshop on Frameworks for Semantics in Web Services, Innsbruck, Austria, June 9-10, 2005.

Amit Sheth, William York, Christopher Thomas, Meenakshi Nagarajan, John A. Miller, Krys Kochut, Satya Sahoo, and Xiaochuan Yi, “Semantic Web technology in support of Bioinformatics for Glycan Expression,” W3C Workshop on Semantic Web for Life Sciences, Cambridge, MA, October 27–28, 2004.

Journal Article

Meenakshi Nagarajan, Kunal Verma, Amit P. Sheth, and John A. Miller, 'Ontology Driven Data Mediation in Web Services,'International Journal of Web Services Research, 4 (no. 4) October-December 2007.

Amit Sheth and Meenakshi Nagarajan, Semantics-Empowered Social Computing. IEEE Internet Computing Jan/Feb 2009, pages 76-80

B. Aleman-Meza, M. Nagarajan, L. Ding, A. Sheth, I. B. Arpinar, A. Joshi, and T. Finin, 'Scalable Semantic Analytics on Social Networks for Addressing the Problem of Conflict of Interest Detection,'ACM Transactions on the Web, 2 (no.1), February 2008.

Daniel Gruhl, Meenakshi Nagarajan, Jan Pieper, Christine Robson, Amit Sheth, Multimodal Social Intelligence in a Real-Time Dashboard System to appear in a special issue of the VLDB Journal on 'Data Management and Mining for Social Networks and Social Media', 6 (2) 2010

Workshop Presentation

Meenakshi Nagarajan, Kamal Baid, Amit P. Sheth, and Shaojun Wang, Monetizing User Activity on Social Networks - Challenges and Experiences, The Beyond Search - Semantic Computing and Internet Economics 2009 Workshop, Redmond, Washington, June 10, 2009.

Rama Akkiraju, Joel Farrell, John A Miller, Meenakshi Nagarajan, and Amit P Sheth, Kunal Verma, “Web Service Semantics—WSDL-S,” Technical Note, W3C Workshop on Frameworks for Semantics in Web Services, DERI, Innsbruck, Austria, June 9–10, 2005.

Tutorial Presentation

Meenakshi Nagarajan,Cartic Ramakrishnan and Amit Sheth, 'Text Analytics for Semantic Computing - the good, the bad and the ugly', Second IEEE International Conference on Semantic ComputingSanta Clara, CA, USA - August 4-7, 2008

Meenakshi Nagarajan,Amit Sheth,Selvam Velmurugan Citizen Sensor Data Mining, Social Media Analytics and Development Centric Web Applications Proc of the WWW 2011, March 28 - April 1, 2011, Hyderabad, India, ACM.

Abstract

The information access paradigm offered by most contemporary text information systems is a search-and-sift paradigm where users have to manually glean and aggregate relevant information from the large number of documents that are typically returned in response to keyword queries. Expecting the users to glean and aggregate information has lead to several inadequacies in these information systems. Owing to the size of many text databases, search-and-sift is a very tedious often requiring repeated keyword searches refining or generalizing queries terms. A more serious limitation arises from the lack of automated mechanisms to aggregate content across different documents to discover new knowledge. This dissertation focuses on processing text to assign semantic interpretations to its content (extracting Semantic metadata) and the design of algorithms and heuristics to utilize the extracted semantic metadata to support knowledge discovery operations over text content. Contributions in extracting semantic metadata in this dissertation cover the extraction of compound entities and complex relationships connecting entities. Extraction results are represented using a standard Semantic Web representation language (RDF) and are manually evaluated for accuracy. Knowledge discovery algorithms presented herein operate on RDF data. To further improve access mechanisms to text content, applications supporting semantic browsing and semantic search of text are presented.

Slideshow

Committee Members

Amit P. Sheth, Ph.D. (Advisor)	Shaojun Wang, Ph.D.	Dr. Vassant Honavar Ph.D.
Michael L. Raymer, Ph.D.	Dr. Thaddeus Tarpey Ph.D.