David Taniar is recognized for significant contributions in database query processing in (i) Parallel Database, and (ii) Mobile/Spatial Databases. His primary contribution is to make access pattern to these databases more efficient. He has authored two books on databases ("High Performance Parallel Database Processing and Grid Databases", Wiley 2008, and "Object-Oriented Oracle", 2006), and has received four best paper awards (from three IEEE conferences and one international journal). His list of publications can be found at the DBLP server (http://www.informatik.uni-trier.de/~ley/db/indices/a-tree/t/Taniar:David.html). He is the founding editor-in-chief of three Science Citation Index Expanded (SCI-E) journals (Mobile Information Systems, Intl. J. of Data Warehousing and Mining, and Intl. J. of Web and Grid Services), a PC chair and a General chair of a number of international conferences, and has been invited to deliver keynote speeches and tutorials at various international events. He is an Associate Professor at Monash University, Australia. Further details on his track records can be found at http://users.monash.edu/~dtaniar/.
Big Data is all about data that we don't have
Big Data is now becoming a buzz word in information technology industry and research. Is Big Data only about large volume of data?, and if it is yes, why is it suddenly becoming a trend. Hasn't the growth of data volume been gigantic in the last decade? From a research point of view, it is not surprising to see researchers from all walks of computer science are trying to align their research to Big Data for the sake of being trendy. The question remains whether it tackles the real Big Data problems. In this talk, I will describe the misconceptions of Big Data, present motivating cases, and discuss the unavoidable challenges faced by industry and research.
Torben Bach Pedersen
Torben Bach Pedersen is a Professor of Computer Science at Aalborg University, Denmark, where he has been a faculty member since 2000. Previously, he worked as a business intelligence specialist and researcher in industry for six years. His research concerns business intelligence and big data, more specifically technologies for "Big Multidimensional Data" - the integration and analysis of large amounts of complex and highly dynamic multidimensional data. He is an ACM Distinguished Scientist, an IEEE Senior Member, and a member of the Danish Academy of TechnicalSciences and the SSTD Endowment
Managing Big Multidimensional Data
Multidimensional database concepts such as cubes, dimensions with hierarchies, and measures have been a cornerstone of analytical business intelligence tools for decades. However, the standard data models and system implementations (OLAP) for multidimensional databases cannot handle ''Big Multidimensional Data'', very large amounts of complex and highly dynamic multidimensional data that occur in a number of emerging domains such as energy, transport, logistics, as well as science. This talk will discuss similarities and differences between traditional BI and Big Data, present examples of Big Multidimensional data with the characteristics of large volume, high velocity (fast data), and/or high variety (complex data) and discuss how to manage Big Multidimensional Data, including modeling, algorithmic, implementation, as well as practical, issues.
Founder & Chairman of Social Quant, Inc., Morten has received his MBA from Henley Management College in the UK and holds not one, but two Ph.D.’s – one from Rushmore University in the US, where he published the groundbreaking book about Computer Aided Leadership and Management (CALM) and the other from Aalborg University regarding his revolutionary data mining mechanism, Sentinels. This man-machine synergy within the decision process is as much practical as it is revolutionary; in fact, Dr. Middelfart’s CALM thought-leadership is applicable to both contemporary and future computer systems. His second Ph.D. presents a series of so-called Sentinel algorithms within the field of artificial intelligence, namely data mining, in which patterns for decision making are autonomously detected by computers in large sums of data. In addition to his academic research, Dr. Middelfart’s software inventions are embedded in TARGIT’s products and include 25 patents worldwide.
Morten has been the keynote speaker at 45 events within the past two years. This includes his participation in the first Business Intelligence talk show ever.
Big Data and the Dawn of Algorithms in Everything
The mainstream adoption of the internet as a source for knowledge and interaction for the past decades has given rise to new data sources that are characterized by large sizes and rapid creation. In addition, sensory data from mobile devices and machinery are on the rise with similar characteristics. All these sources have the commonality that they will tell us something new or something more detailed than before. From a business standpoint these data sources holds the opportunity to create more customized services and improved products in practically anything, however, they also present a challenge since they are big and typically residing outside the traditional server structure of organizations. This talk will explore the challenges of integrating these new, so-called Big Data, in decision processes. Specifically, we will explore the paradigm shifts when external data become equally or more important than internal data. We will also explore the emerging shift in decision making becoming algorithmic as opposed to human discovery driven.
Thomas Baudel is Research Director at the IBM France Lab and at the Institute for the Energy Efficiency of Sustainable Cities. His current focus is on providing city planners and decision makers with tools to manage energy transition. Recently, he has been involved in the flagship OptimodLyon project, whose goal is to improve mobility by providing better information to city travelers, encouraging them to switch transportation modes when needed, and helping professional travelers to reduce their costs by optimizing their rounds taking forecast traffic into account.
Prior to tackling the challenges of Sustainable Cities from an information systems perspective, he has contributed to many areas of research in interactive computer systems, starting as HCI Researcher at the LRI, University of Paris-Sud, then contributing to the development of Alias|Wavefront Maya, shifting his research interests to Information Visualization and Visual Analytics at ILOG and IBM in the 2000's, while on his spare time contributing to innovation in Computer Music.
Challenges and Opportunities in HCI, Visual Analytics and Knowledge Management for the development of Sustainable Cities.
While overtly exposed in the media, the challenges faced by our societies to transition towards sustainable energy use are quite formidable. A simple visual refresher of the cold hard facts should amply reveal the importance of visualization to assess the situation. Private companies, such as IBM, and public research centers are joining forces and investing to design and evaluate novel approaches to build and manage Cities, defined as the rational organisation of dense human habitat. Information and Communication technologies are certainly part of the answers, in particular in areas related to knowledge management, data mining, HCI and social computing,
Illustrated with telltaling examples of research work carried at IBM, the CSTB and the Efficacity Institute, I will argue that Interactive Information Technologies can help managing the energy transition of cities in 3 key aspects:
- 1. to support the city design process, notably computer supported tooling and information infrastructure that help taming the complexity of the intertwinning actors and interests at play,
- 2. to help understand better the city's dynamics, identifiy inefficiencies and reveal optimization opportunities, where knowledge management and extraction is crucial,
- 3. and foremost, to ease the necessary changes that will have to happen in our mobility and housing habits with novel tools and services that alleviate our energy needs.