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\neScience Workshop 2011-Transforming Scholarly Communication<\/a>
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This tenth annual Microsoft eScience Workshop continued the ongoing dialogue centered on applications in broad areas of scientific investigation, such as environmental studies, bioinformatics, and climate understanding; presented new results in data modeling; and provided an opportunity for open discourse on developments in urban computing. Discussions covered eScience computing needs from data collection, data analytics, and machine learning to visualization. The topics selected for this year\u2019s program created the opportunity for a rich, interdisciplinary exchange of ideas.<\/p>\n \t\t\t \t<\/div>\n\t<\/p> \t \t<\/div>\n\t<\/p>\t\t\t<\/div>\n\t\t<\/div>\n\t\t<\/p>\n Each year, the eScience Workshop provides a forum for scientists and researchers to share their experiences and expertise with the academic and research communities. The eScience Workshop fosters collaboration, facilitates the sharing of software components and techniques, and defines rich, open scientific challenges. Microsoft has been actively pursuing research in eScience for more than 10 years; the book, The Fourth Paradigm: Data-Intensive Scientific Discovery<\/em><\/a>, provides a background on its many areas of focus.<\/p>\n \t Opens in a new tab<\/span><\/p>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t<\/div>\n\tOpens in a new tab<\/span><\/p>\n \t Tutorial 1: Azure Platform for Cloud Computing | video<\/a><\/strong><\/p>\n Chair: <\/strong>Gebi Liang, Microsoft Asia-Pacific R&D Group<\/p>\n Speakers:<\/strong> Michael Wang, Larry Zhang, and\u00a0Wei Sun, Microsoft Asia-Pacific R&D Group<\/p>\n Tutorial 2: Kinect for Windows in Science Applications | video<\/a><\/strong><\/p>\n Chair: <\/strong>Stewart Tansley, Microsoft Research Redmond<\/p>\n Speakers:<\/strong> Wei Liu, Microsoft Server and Tools; Cherry Wang, Microsoft Kinect for Windows China; Stewart Tansley, Microsoft Research Redmond<\/p>\n Tutorial 3: Data-Constrained Environmental Modeling: FetchClimate, Filzbach, and Distribution Modeller<\/strong> | video<\/a><\/strong><\/p>\n Speaker: <\/strong>Drew Purves, Microsoft Research Cambridge<\/p>\n Opens in a new tab<\/span><\/p>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t<\/div>\n\t<\/p>\n \t What’s eScience? | video<\/a><\/strong><\/p>\n Speaker: <\/strong>Kenji Takeda<\/a>, Microsoft Research Cambridge<\/p>\n The nature of scientific discovery is continuously accelerating as the culture of research is profoundly affected by technology. From the development of instruments such as the microscope, to developments in mathematics and the tremendous advances in scientific computing, scientists are able to explore, understand, and describe the world around us in more ways than ever before. We are now in the midst of a Fourth Paradigm of data-intensive science<\/a> in which instruments, sensors, and simulations are generating huge amounts of data that must be processed, analyzed, shared, and discussed to generate knowledge and opportunities to solve the major challenges of our global society. This new collaborative approach to research is the core of eScience. This talk will explore how eScience is transforming every discipline, and how cloud computing provides new opportunities for all researchers<\/a>.<\/p>\n<\/blockquote>\n Opens in a new tab<\/span><\/p>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/li>\n\t\t Data Driven Applications | video<\/a><\/strong><\/p>\n Speaker: <\/strong>Prakash Sundaresan, CTO, Microsoft Asia-Pacific R&D Group<\/p>\n Data has always been at the heart of applications. Over the last 30 years, application architectures have gone through some key paradigm shifts: from monolithic mainframe applications, to client-server architecture, to three-tier web architectures, and now converging on device+cloud as the dominant contemporary application architecture. The relationship of data to the application has also evolved through these paradigm shifts. A convergence of technology trends\u2014proliferation of devices, cloud computing and big data techniques\u2014is now putting data at the center of a new generation of\u00a0data driven applications\u00a0that are transforming fields as diverse as technology, commerce, government, and science. In this talk, we\u2019ll examine these trends and show some examples of leading-edge data driven applications from a variety of fields from around the world. We\u2019ll also look at some of the innovative tools and technologies that are enabling these new applications.<\/p>\n<\/blockquote>\n Emerging Trends in Online Education and Research<\/strong> | video<\/a><\/strong><\/p>\n Speaker:<\/strong> Roy Zimmermann<\/a>, director of Education and Scholarly Communication, Microsoft Research Connections<\/p>\n While online education and research services continue to emerge, it is still debatable whether they will bring revolutionary change or more evolutionary enhancements to existing platforms and services. Some services, like MOOCs, that just a short while ago were expected to be disruptive and to flip the entire education domain on its head, are now nesting themselves in more traditional education systems. The result is they are working more as background service providers than radical paradigm shifting mechanisms. Likewise, the emerging field of online research services is growing more crowded and niche driven with some entire services dedicated to bibliometrics, citation analysis, and alternative metrics for evaluating impact. This session will highlight a few education and research services as trend setters for the rest of their domains.<\/p>\n<\/blockquote>\n Opens in a new tab<\/span><\/p>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/li>\n\t\t eScience in the Medical Domain | video<\/a><\/strong><\/p>\n Chair:<\/b> Junichi Tsujii, Microsoft Research Asia<\/p>\n Speakers<\/b>: Simon Mercer, Microsoft Research; Lai Maode, China Pharmaceutical University; Hoifung Poon<\/a>, Microsoft Research; James Hogan, Queensland University of Technology<\/p>\n eScience research has the potential to change future scientific endeavors in the medical domain through the promotion of community-wide efforts to share data, software, and services, the advantages of big data and big text for the extraction of new knowledge, and the dissemination of knowledge in new ways, such as visualization and the collaborative construction of biological pathways. This session will explore a range of research projects seeking to provide elements of the infrastructure needed to realize this vision.<\/p>\n<\/blockquote>\n Opens in a new tab<\/span><\/p>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/li>\n\t\t Conducting Scientific Research in the Cloud<\/strong> | video<\/a><\/strong><\/p>\n Chair: <\/b>Dennis Gannon, Microsoft Research<\/p>\n Speakers: <\/b>Honglin He, Chinese Academy of Sciences; <\/b>Chunmiao Zheng\u00a0and Yingying Yao, Peking University; Liang Lin, Sun Yat-Sen University<\/p>\n Cloud computing is based on harnessing the power of massive online data centers to support dynamically deployed user applications and data collections. Because clouds can scale on-demand from single core virtual machines to large numbers of servers, they are ideal for many eScience applications that require analysis of large data collections. Clouds are the engines of the fourth paradigm of science. This session describes three examples of new research projects in China that are using the Windows Azure cloud platform for eScience applications.<\/p>\n<\/blockquote>\n Interactive Visual Analytics for Scientific Discovery | video<\/a><\/strong><\/p>\n Chair: <\/b>Shixia Liu, Microsoft Research Asia<\/p>\n Speakers:<\/b> Klaus Mueller, Stony Brook University; Huamin Qu, Hong Kong University of Science and Technology; Daniel Keim, University of Konstanz<\/p>\n Interactive visual analytics, the science of analytical reasoning facilitated by interactive visual interfaces, could help analysts explore and understand large-scale, complex data to support the analysts\u2019 sense-making processes. It has been successfully applied to solving a wide range of real-world problems. Nevertheless, designing an effective visual analytics system remains challenging. This panel brings together recognized leaders in visual analytics to share their success stories and rich expertise in designing effective visual analytics systems for a variety of eScience applications. The panelists will describe the practical problems they explore, the visualization techniques they develop, and the interesting findings they discover. Finally, the panelists will provide guidance and suggestions for how scientists can effectively apply visual analytics techniques to facilitating scientific discovery and decision making.<\/p>\n<\/blockquote>\n Opens in a new tab<\/span><\/p>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t<\/div>\n\t<\/p>\n \t IEEE eScience Keynote: From Genes to Stars | video<\/a><\/strong><\/p>\n Speaker: <\/strong>Alex Szalay, Johns Hopkins University<\/p>\n Student Session: Learning Cloud Computing, Environmental Science, and You | video<\/a><\/strong><\/p>\n Speaker: <\/strong>Wenming Ye, Microsoft Research<\/p>\n Studies revealing the impact of human activities on nature demonstrate the increasing importance of environmental science to help control pollution and reverse its effects. While social media and Web 2.0 companies have been enjoying the growth and benefits of cloud computing and Big Data, the general research and scientific computing communities are just starting to discover this powerful new computing paradigm. In this session, we will explore ways to use cloud computing and sensor networks to help solve interesting problems in environmental science today. Learning to use cloud computing and Big Data tools enables future scientists to better understand and solve the most challenging problems in protecting and preserving our environmental resources.<\/p>\n<\/blockquote>\n Opens in a new tab<\/span><\/p>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/li>\n\t\t From Smart Sensors to City OS (I)<\/strong> | video<\/a><\/strong><\/p>\n Chair<\/b>: Feng Zhao, Microsoft Research Asia<\/p>\n Speakers<\/b>: Yuqi Bai, Tsinghua University; Hao-Hua Chu, National Taiwan University; Rajesh Krishna Balan, Singapre Management University; Huayi Wu, Wuhan University<\/p>\n With the proliferation of the IoT (Internet of Things) ecosystem, mobile sensors, and \u201csoft\u201d sensors, we are increasingly seeing opportunities to collect rich data sets that were previously unavailable. In turn, the market demands an end-to-end Big Sensor Data (BSD) platform for data collection<\/i>, data storage<\/i>, data-driven analysis<\/i>, and feedback loop<\/i>. The significance of BSD is not just in the data quantity, but also in the real-world insights that they reveal. In this session, we will discuss research challenges that are related to the four stages of BSD above.<\/p>\n First, how have the limits and boundaries of sensing and actuation been pushed by technological advances, such as the maturity of cloud-computing and the miniaturization of devices? Second, how should techniques and analytical tools from years of Big Data research impact the work on BSD, and streamline the BSD adaption? Third, from the pioneering work on modeling parts of our physical world with data, what do we need to model the missing pieces?<\/p>\n<\/blockquote>\n Opens in a new tab<\/span><\/p>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/li>\n\t\t Data-Constrained Environmental Modelling: FetchClimate, Filzbach, and Distribution Modeller<\/b> | video<\/a><\/strong><\/p>\n Chair: <\/b>Drew Purves, Microsoft Research Cambridge<\/p>\n Speakers: <\/b>Youngryel Ryu, <\/b>Seoul National University; Peng Gong, Tsinghua University; Drew Purves, Microsoft Research Cambridge<\/p>\n There is an obvious and urgent need to build predictive models of important environmental phenomena. Such models need to describe how variation in different aspects of the environment\u2014such as climate and soil\u2014affect the phenomenon of interest, for example, primary productivity of plants, agricultural yield, or even land-use change. But to date, the building of such predictive models has been held back by a host of technical barriers, placing it outside the reach of many environmental scientists (and making it annoyingly difficult and slow for the rest!).<\/p>\n In this session, we\u2019ll continue to walk you through three useful tools: FetchClimate, Filzbach, and Distribution Modeller, and will demonstrate how and why researchers are using them in real-world research.<\/p>\n<\/blockquote>\n Opens in a new tab<\/span><\/p>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/li>\n\t\t From Smart Sensors to City OS (II) <\/b><\/p>\n Chair: <\/b>Xing Xie<\/a>, Microsoft Research Asia<\/p>\n Speakers: <\/b>Ryosuke Shibasaki<\/a>, University of Tokyo; Lei Chen<\/a>, Hong Kong University of Science and Technology; Guangzhong Sun, University of Science and Technology of China; Zhen Liu<\/a>, Microsoft Asia-Pacific R&D Group<\/p>\n In recent years, real-world data reflecting city dynamics has become widely available, including users\u2019 mobile phone signal, GPS traces of vehicles and people, ticketing data in public transportation systems, data from transportation sensor networks (camera and loop sensors), and environment sensor networks (temperature and air quality), as well as data from the Internet of Things. As a result, we are ready to carry out real urban computing activities that lead to better and smarter cities. By better sensing and understanding the city dynamics, we are more likely to design effective strategies and intelligent systems for improving life in urban areas. In this session, we are interested in discussing how we use the huge amount of sensor data to benefit different urban application scenarios, including, but not limited to, e-campus, environment, transportation, and smart building.<\/p>\n<\/blockquote>\n Opens in a new tab<\/span><\/p>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/li>\n\t\t\t\t\t\t<\/ul>\n\t<\/div>\n\t<\/p>\n \t Large-Scale Data Analysis for Biomedical and Social Sciences<\/strong><\/p>\n Chair: <\/b>Yi Ma, Microsoft Research Asia<\/p>\n Speakers:<\/b> Kun Huang, Ohio State University; Takayuki Okatani<\/a>, Tohoku University; Tom Cai<\/a>, University of Sydney<\/p>\n![\"collage-image270x180\"](\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/09\/collage-image270x180.png\")
The 2013 Microsoft eScience Workshop\u00a0was held October 22 to 25 at the China National Convention Center, Beijing, in conjunction with the\u00a0ninth IEEE International Conference on e-Science (opens in new tab)<\/span><\/a>. Discussions and presentations explored how computing continues to take us From Data to Discovery<\/em>.<\/p>\n\n
eScience Workshop co-chairs<\/h2>\n
![\"dan-fay\"](\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/09\/dan-fay.jpg\")
Dan Fay<\/a> Director of Earth, Energy, and Environment, Microsoft Research Connections<\/p>![\"eric-chang\"](\"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/09\/eric-chang.jpg\")
Eric Chang<\/a>\u00a0Senior Director\u00a0of Technology Strategy and Communications, Microsoft Research Asia<\/p>About the workshop<\/h2>\n
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Tuesday, October 22, 2013<\/h2>\n
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Thursday, October 24, 2013<\/h2>\n
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Friday, October 25, 2013<\/h2>\n
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