Spring 2015 IS Distinguished Lecture 
Department of Information Systems

Opinion Mining, Machine Learning and Big Data

Dr. Philip Bourne
Associate Director for Data Science
The National Institutes of Health

10:00am Tuesday, 5 May 2015, ITE 456, UMBC

Philip E. Bourne is the Associate Director for Data Science at the National Institutes of Health. Formally he was Associate Vice Chancellor for Innovation and Industry Alliances, a Professor in the Department of Pharmacology and Skaggs School of Pharmacy and Pharmaceutical Sciences at the University of California San Diego, Associate Director of the RCSB Protein Data Bank and an Adjunct Professor at the Sanford Burnham Institute.

Bourne's professional interests focus on service and research. He serves the national biomedical community through contributing ways to maximize the value (and hence accessibility) of scientific data. His research focuses on relevant biological and educational outcomes derived from computation and scholarly communication. This implies algorithms, text mining, machine learning, metalanguages, biological databases, and visualization applied to problems in systems pharmacology, evolution, cell signaling, apoptosis, immunology and scientific dissemination. He has published over 300 papers and five books, one of which sold over 150,000 copies.

Bourne is a Past President of the International Society for Computational Biology, an elected fellow of the American Association for the Advancement of Science, the International Society for Computational Biology and the American Medical Informatics Association.  His awards include: the Jim Gray eScience Award (2010), the Benjamin Franklin Award (2009), the Flinders University Convocation Medal for Outstanding Achievement (2004), the Sun Microsystems Convergence Award (2002) and the CONNECT Award for new inventions (1996 and 1997).

Ph.D. Dissertation Defense

A Semantic Resolution Framework for Integrating
Manufacturing Service Capability Data

Yan Kang

10:00am Monday 27 April 2015, ITE 217b

Building flexible manufacturing supply chains requires availability of interoperable and accurate manufacturing service capability (MSC) information of all supply chain participants. Today, MSC information, which is typically published either on the supplier’s web site or registered at an e-marketplace portal, has been shown to fall short of interoperability and accuracy requirements. The issue of interoperability can be addressed by annotating the MSC information using shared ontologies. However, this ontology-based approach faces three main challenges: (1) lack of an effective way to automatically extract a large volume of MSC instance data hidden in the web sites of manufacturers that need to be annotated; (2) difficulties in accurately identifying semantics of these extracted data and resolving semantic heterogeneities among individual sources of these data while integrating them under shared formal ontologies; (3) difficulties in the adoption of ontology-based approaches by the supply chain managers and users because of their unfamiliarity with the syntax and semantics of formal ontology languages such as the web ontology language (OWL).

The objective of our research is to address the main challenges of ontology-based approaches by developing an innovative approach that is able to extract MSC instances from a broad range of manufacturing web sites that may present MSC instances in various ways, accurately annotate MSC instances with formal defined semantics on a large scale, and integrate these annotated MSC instances into formal manufacturing domain ontologies to facilitate the formation of supply chains of manufacturers. To achieve this objective, we propose a semantic resolution framework (SRF) that consists of three main components: a MSC instance extractor, a MSC Instance annotator and a semantic resolution knowledge base. The instance extractor builds a local semantic model that we call instance description model (IDM) for each target manufacturer web site. The innovative aspect of the IDM is that it captures the intended structure of the target web site and associates each extracted MSC instance with a context that describes possible semantics of that instance. The instance annotator starts the semantic resolution by identifying the most appropriate class from a (or a set of) manufacturing domain ontology (or ontologies) (MDO) to annotate each instance based on the mappings established between the context of that instance and the vocabularies (i.e., classes and properties) defined in the MDO. The primary goal of the semantic resolution knowledge base (SR-KB) is to resolve semantic heterogeneity that may occur in the instance annotation process and thus improve the accuracy of the annotated MSC instances. The experimental results demonstrate that the instance extractor and the instance annotator can effectively discover and annotate MSC instances while the SR-KB is able to improve both precision and recall of annotated instances and reducing human involvement along with the evolution of the knowledge base.

Committee: Drs. Yun Peng (Chair), Tim Finin, Yaacov Yesha, Matthew Schmill and Boonserm Kulvatunyou

Innovations in Cybersecurity Education Workshop

9:30 – 4:30 Friday, 12 June 2015, UMBC BWtech South Campus

Innovations in Cybersecurity Education is a free regional workshop on cybersecurity education from high school through post-graduate. It is intended primarily for educators who are teaching cybersecurity at high schools, colleges, and community colleges. Anyone is welcome to attend, including teachers, students, administrators, researchers, and government officials.

The workshop will highlight master teachers and ongoing educational projects, including an effort at the US Naval Academy to teach cybersecurity to all midshipmen. It will include discussions about cyber competitions, hands-on exercises, educational games, and integrating cybersecurity throughout the curriculum. There will be an opportunity to experience hands-on cyber defense exercises and to play new computer security education games, including SecurityEmpire developed at UMBC.

The workshop is free and open to the public — all are welcome to attend. This workshop will to be of interest to educators, school administrators, undergraduate and graduate students, and government officials. Lunch will be provided. Parking is free.

Please see the links above for the schedule and location and register to help us plan for the number of participants.

The workshop is organized by Dr. Alan T. Sherman with support provided in part by the National Science Foundation under SFS grant 1241576.

Name: Jennifer Montooth

Internship, Co-op or Research Site: Maryland Psychiatric Research Institute Peer Review Program | Title of Your Position: Research Intern

Major(s)/Minor(s): History, Political Science

Expected Graduation Year: December 2015

Briefly describe your internship, co-op, research, or service-learning opportunity, including your day-to-day tasks, responsibilities, and assignments.

The Peer Review Program helps low-income families in inner city Baltimore receive medication for their children with Schizophrenia. The researchers help make sure the children are efficiently getting the proper amount of medication. When I assist the researchers, I help them organize and file all of the patients' information in alphabetical order and send out their charts to the proper offices and hospitals to ensure that every patient gets the proper care.

Describe the process of obtaining your internship, research, or co-op opportunity.

I found my internship through UMBCWorks and was enthralled in the idea. Once I submitted my resume, I had a phone interview with the supervisor. She was curious as to why a history and political science major would want to help a psychiatric program. I explained to her, however, that I was very interested in pursuing a Public Policy degree once I graduate, and am very interested in learning about successful programs such as the Peer Review Program. I also told her about my research paper from a previous semester regarding the lack of mental health funding and assistance in Baltimore City prisons, and how it would help the city in several ways if inmates got proper treatments for their disorders. My excitement about the program and learning about mental health helped me get the internship almost on the spot.

Which of the following resources did you use to find your current experience?

UMBCworks

What have you enjoyed the most about your position or organization/company?

I love the people in the program, they're all very passionate about what they do, and it feels motivating to be around them. I learn more each day about all of the processes and steps it takes to keep the program running and proving their efficiency in order to continue receiving funding. Once a week I also get to meet with a doctor and a group of Schizophrenia patients at one of their education sessions, where the patients learn more about their disorder. I had never encountered anyone with Schizophrenia before, so it's been amazing to interact with the patients and learn more from the doctors.

What advice would you give to another student who is seeking an internship or similar experience?

I would advise them to think outside of the box, and think towards the future. This internship is a little far off from my major, but it keeps me constantly learning, which makes every day a new experience. I did a research paper that got me motivated to help mental health programs a year ago, and wanted to get more involved, but had no idea how. I feel like I have more understanding of what I want to do once I graduate thanks to this internship.

Please provide a short reflection or quote about what you liked most about your position / earning internship credit / the internship placement process.

Everyone involved in helping me receive credit for this internship, including Jeremiah Sawyer and my professor Michele Wolff, have been nothing but encouraging and helpful the whole time, which makes this experience all the better.

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