ISE 2002 Keynote Speech

 

 

Sensor Web and Sensor Data Management

Research Directions

 

Dr. Bhavani Thuraisingham

The National Science Foundation

Arlington, VA, USA

 

 

 

Abstract of Keynote Presentation

Sensor web is about millions of sensors connected together in an ad-hoc manner and collaborating with each other to gather sensor data, fuse the data, correlate the data and take actions.  Sensor data management provides techniques for effective management of sensor data.  For many applications in domains such as process control, intelligence, and command and control, it is critical that sensor data be processed in a timely manner.  For example, SIGINT data processing is an important part of managing Intelligence data.  For command and control systems such as AWACS (airborne warning and control system), sensors gather data about the tracks, correlate the data and process the data within a certain time.  The next generation of sensor computing deals with sensor web where the sensors are autonomous and yet they have to cooperate with one other. 

 

This presentation will discuss characteristics of sensor web and will describe architectures and data/information management issues for the sensor web.  The architectures include those based on components, frameworks and distributed objects.  Data management issues include data models for sensor data, techniques for managing data streams, techniques for query management, optimization, storage management and caching, as well as extracting and managing metadata from the sensor data.  

 

Since the sensors essentially form a web, we need common data representation schemes.  One approach is to examine XML-like languages for common sensor data representation.  We also need to examine the use of RDF-like languages for incorporating semantics.  Data mining and knowledge discovery techniques are needed for mining sensor data and extracting patterns often previously unknown.  For example, one may extract information about adversaries (their locations, plans and actions) by mining the sensor data.  We need to augment data mining with decision support techniques to support the analyst to make effective decisions. 

 

One may ask the question what is the difference between the sensor web and the semantic web?  According to Berners Lee et al, the semantic web is about machine understandable web pages.  Various data, information and agent technologies are being examined for understanding the web pages and making effective decisions.  Sensor web is somewhat similar except that we are dealing with sensor data.  That is, the sensor data has to be processed, managed and understood by the machines.  

 

Note that in addition to data and information management technologies, there are several other technologies such as networking, communication and signal processing needed in order to develop efficient sensor webs.  However, networking and communication issues are beyond the scope of this presentation.  They provide the communication infrastructure for the sensor data management systems.  

 

The presentation first describes the characteristics of the sensor web.  Then we will focus on possible architectures.  Data management issues will be addressed next.  Mining sensor data will be the next topic.  Next, we will focus on the use of XML and related languages.  Finally, the relationship to the semantic web will be explored.  

 

 

Biography of Dr. Thuraisingham:

Bhavani Thuraisingham is the program director for Information and Data Management (IDM) at the National Science Foundation.  In addition to her responsibilities in IDM, she is also part of a team setting directions for Bioinformatics and Geoinformatics as well as working on interagency efforts on Information technology for counter-terrorism.  She has also initiated a second program on Data and Applications Security.  She is on leave from the MITRE Corporation where she is chief scientist in data management in the Information Technology Directorate in Bedford Massachusetts.  Since joining MITRE in January 1989, she has held various positions including lead and principal scientist and was also a department head in data and information management.  Dr. Thuraisingham's research interests include secure databases, data mining, real-time databases and web data management.  She is the recipient of IEEE Computer Society's 1997 Technical Achievement Award for outstanding and innovative research contributions to secure data management.  She also holds three patents for MITRE on database inference control. 

 

Dr. Thuraisingham received the M.Sc. degree from the University of Bristol and the Ph.D. degree from the University of Wales both in the United Kingdom.  Prior to joining MITRE she worked in the computer industry for over 5 years in Minneapolis first at Control Data Corporation and later at Honeywell Inc.  She has also served as adjunct professor of computer science for over six years first at the University of Minnesota and later at Boston University.  Dr. Thuraisingham serves (or has served) on the editorial boards of IEEE Transactions on Knowledge and Data Engineering, the Journal of Computer Security and the Computer Standards and Interfaces Journal.  She has chaired over 15 conferences and workshops and has published over 400 technical papers and reports including over 50 journal articles.  She is the author of five books in data management and data mining for technical managers and has edited several more in information security and data management.  She is a senior member of IEEE and is also a member of ACM, the British Computer Society, and currently serves on the advisory committee in data management for IASTED.  She is a frequent keynote and featured speaker worldwide.