The new millenium has introduced technologies that are transitioning computing from hardware- and software-enabled platforms to cloud-hosted resources. In parallel with cloud computing, we have witnessed several other advances that are transforming the Internet into a global social and work platform. These include crowd sourcing, social networks and collaboration technologies. These technologies provide a common interaction and sharing infrastructure. Advances in collaboration and composition are increasing transparency, awareness, and participants’ productivity. Crowd sourcing leverages the wisdom of large groups and communities to work independently to solve problems in the same way open source did for software development. For instance, Amazon’s Mechanical Turk (MTurk)1 provides on-demand access to task forces for micro-tasks such as image recognition, language translation, etc. Several organizations including DARPA and various world health and relief agencies are using platforms such as MTurk and Ushahidi to crowd-source information through multiple channels, including SMS, email, Twitter and the Web in general. Social engagement and digital Internet services are clearly emerging as a cornerstone to the future of digital processes at all levels. This talk will provide an overview of some of the opportunities in education, research, and development. We discuss some challenges in the process of leveraging social engagement and digital services to ICT enabled transformation.

There has been a growing trend toward the automated generation of massive data at multiple distributed locations, leading to a future of computing that is data-rich, heterogeneous, distributed, and rife with uncertainty. Examples include systems to monitor the physical world, such as wireless sensor networks, and systems to monitor complex infrastructures, such as distributed Internet monitors. This trend will likely continue. Most information available today on the Internet is fabricated by human data entry. While such this type of information will continue to be produced, it will be only a small fraction of the volume of information generated by automated factories. This trend raises a number of key questions: How to fuse, process, reason with and analyze this tremendous amount of automated data streams? How to integrate raw information with high-level information available in traditional media and reason about uncertainty? How to recognize emergent communities of users in this new scenario? How to reason about security in an uncertain data environment? Our talk will focus on information-generating factories in networks of fixed and mobile heterogeneous smart sensing devices. Our goal in this area is to develop a unified model, which captures the characteristics of both the new information generating factories and the traditional information available in the cyberspace, including distribution, heterogeneity, self-emergence, dynamic resource management, reaction to complex chains of events, continuous evolution, context-awareness, and uncertainty.

Textbook database examples are often wrong and simplistic. Unfortunately Data is never born clean or pure. Errors, missing values, repeated entries, inconsistent instances and unsatisfied business rules are the norm rather than the exception. Data cleaning (also known as data cleansing, record linkage and many other terminologies) is growing as a major application requirement and an interdisciplinary research area. In this talk, we will start by discussing some of the major issues and challenges facing creating effective and efficient data cleaning solutions. Then we will discuss some challenges and criticize current conservative approaches to this very critical problem. Finally we will discuss some of our work at QCRI in this area.