This document summarizes a keynote presentation given by Jeffrey F. Naughton on the past and future of database management systems (DBMS) research. Naughton discusses how the seeds of DBMS research were planted decades ago through early commercial interest in data processing, common challenges around data management, and problems amenable to abstraction. While these factors still exist today, Naughton worries that pressure to publish many papers, low conference acceptance rates, and poor reviewing are discouraging creativity and risk-taking in the research community. He presents a "doomsday scenario" where DBMS research feels like studying for exams rather than fulfilling work. Naughton argues the community should refocus on the meaningful problems and intellectual excitement that initially drove the field.
Knowledge From Crowds - Better with Institutions + AlgorithmsShaun Abrahamson
Crowds can support learning and knowledge creation. A framework using institutions and algorithms can help assure good outcomes - Wikipedia, Edx.org and Giffgaff are used to explain the framework.
Presentation for KM 2012 in Sao Paulo, Brazil.
This document discusses how large-scale crowdsourcing and peer production can drive innovation through idea generation, evaluation, and implementation. It provides examples of how open challenges and crowdsourcing transformed industries like transportation and medical devices. The key points are that crowds can access critical resources like ideas, capital, data and influence change at a vast scale; that the right incentives, questions, and ecosystems are needed to engage participants and achieve results; and monitoring participation is important for picking the best ideas and retaining contributors over time.
Roseville city school district gone google presentation.pdfMorgan Wheeler
The document discusses why the school district is considering moving to Google Apps now. The current email and calendar system is outdated and cannot meet growing communication needs, and replacing it with Exchange 2010 would be too costly. Google Apps offers a browser-based solution at a lower cost that would provide benefits like access from any device and redundancy. The transition is planned for March to August 2010 to replace the current system with Google Apps by July 1, 2010.
Collaborative writing and common core standards in the classroom slideshareVicki Davis
This document discusses collaborative writing and Common Core standards in the classroom. It introduces several educators who are involved with the Flat Classroom project and discusses how collaborative writing groups can help students meet writing standards. Specific standards around argument, informative/explanatory, and narrative writing are covered. Case studies are presented on projects like NaNoWriMo that use collaborative writing approaches.
ECCV2010 tutorial: statisitcal and structural recognition of human actions pa...zukun
1. Structural methods use human pose as a representation for action recognition by capturing information about actions while being invariant to clothing and lighting variations.
2. There are two broad classes of approaches: matching templates or exemplars, and fitting a human body model.
3. Recent work has focused on recognizing actions from still images by retrieving similar poses and analyzing image evidence, showing that pose is essential for video-based action recognition as well.
CVPR2010: Advanced ITinCVPR in a Nutshell: part 4: additional slideszukun
This document discusses probability density function estimation using isocontours and its applications to image registration and filtering. It proposes estimating densities from image intensities using the areas enclosed by isocontours rather than histograms. This density estimation technique is applied to mutual information-based image registration and anisotropic neighborhood filtering.
ECCV2008: MAP Estimation Algorithms in Computer Vision - Part 1zukun
The document describes various algorithms for maximum a posteriori (MAP) estimation in computer vision problems. It discusses how MAP estimation involves defining an energy function consisting of unary and pairwise potentials, and finding the labeling that minimizes this energy function. Common computer vision problems addressed include binary image segmentation, object detection using parts-based models, and stereo correspondence. Computational challenges are discussed as MAP estimation is NP-hard in general, though approximate algorithms can be used.
Knowledge From Crowds - Better with Institutions + AlgorithmsShaun Abrahamson
Crowds can support learning and knowledge creation. A framework using institutions and algorithms can help assure good outcomes - Wikipedia, Edx.org and Giffgaff are used to explain the framework.
Presentation for KM 2012 in Sao Paulo, Brazil.
This document discusses how large-scale crowdsourcing and peer production can drive innovation through idea generation, evaluation, and implementation. It provides examples of how open challenges and crowdsourcing transformed industries like transportation and medical devices. The key points are that crowds can access critical resources like ideas, capital, data and influence change at a vast scale; that the right incentives, questions, and ecosystems are needed to engage participants and achieve results; and monitoring participation is important for picking the best ideas and retaining contributors over time.
Roseville city school district gone google presentation.pdfMorgan Wheeler
The document discusses why the school district is considering moving to Google Apps now. The current email and calendar system is outdated and cannot meet growing communication needs, and replacing it with Exchange 2010 would be too costly. Google Apps offers a browser-based solution at a lower cost that would provide benefits like access from any device and redundancy. The transition is planned for March to August 2010 to replace the current system with Google Apps by July 1, 2010.
Collaborative writing and common core standards in the classroom slideshareVicki Davis
This document discusses collaborative writing and Common Core standards in the classroom. It introduces several educators who are involved with the Flat Classroom project and discusses how collaborative writing groups can help students meet writing standards. Specific standards around argument, informative/explanatory, and narrative writing are covered. Case studies are presented on projects like NaNoWriMo that use collaborative writing approaches.
ECCV2010 tutorial: statisitcal and structural recognition of human actions pa...zukun
1. Structural methods use human pose as a representation for action recognition by capturing information about actions while being invariant to clothing and lighting variations.
2. There are two broad classes of approaches: matching templates or exemplars, and fitting a human body model.
3. Recent work has focused on recognizing actions from still images by retrieving similar poses and analyzing image evidence, showing that pose is essential for video-based action recognition as well.
CVPR2010: Advanced ITinCVPR in a Nutshell: part 4: additional slideszukun
This document discusses probability density function estimation using isocontours and its applications to image registration and filtering. It proposes estimating densities from image intensities using the areas enclosed by isocontours rather than histograms. This density estimation technique is applied to mutual information-based image registration and anisotropic neighborhood filtering.
ECCV2008: MAP Estimation Algorithms in Computer Vision - Part 1zukun
The document describes various algorithms for maximum a posteriori (MAP) estimation in computer vision problems. It discusses how MAP estimation involves defining an energy function consisting of unary and pairwise potentials, and finding the labeling that minimizes this energy function. Common computer vision problems addressed include binary image segmentation, object detection using parts-based models, and stereo correspondence. Computational challenges are discussed as MAP estimation is NP-hard in general, though approximate algorithms can be used.
This document provides guidance on how to conduct high-quality research and write good papers. It discusses that research can involve solving existing problems using existing methods, improving existing solutions, or identifying new problems and generalizing solutions. The most innovative and impactful research involves identifying new problems. It emphasizes the importance of conducting new and useful research. It then provides tips for training innovation through extensive reading, writing, and rewriting to develop ideas. It discusses finding meaningful topics by starting from real problems and convincing others of the topic's importance. The document concludes by offering writing techniques such as overcoming language barriers, using an active voice, including visual elements, and being specific rather than vague.
Escaping the Knowledge Management Black Hole: New Approaches to Leveraging Or...Paul Culmsee
The document discusses challenges with managing tacit knowledge and debates different approaches. It argues that fully codifying tacit knowledge into explicit documentation is difficult and can have downsides. Instead, it proposes capturing experts' reflections on video and linking them to dialogue maps that represent the rationale without over-codifying details. This preserves context while allowing others to navigate complex discussions. The approach aims to efficiently leverage expert time and knowledge within SharePoint systems.
This document discusses the intersection of machine learning and search-based software engineering (ML & SBSE). It provides examples of how data miners can find signals in software engineering artifacts using machine learning techniques. It then discusses how better algorithms do not necessarily lead to better mining yet and emphasizes the importance of sharing data, models, and analysis methods. Finally, it outlines a vision for "discussion mining" to guide teams in walking across the space of local models, with the goal of building a science of localism in ML and SBSE.
Career introduction of Engineering Student SSVIT rizwanRizwan Khan
This document provides career guidance for senior secondary students. It discusses why career guidance is important, current trends in career selection, who is responsible for career guidance, and an overview of the career cycle. It emphasizes the importance of selecting a career and planning for one's future. Students are advised to discover their interests and strengths, consider their education and career options, and prepare for obstacles through hard work and perseverance. Engineering is presented as a field that applies math and science to solve problems and improve life. Several types of engineering careers are outlined, including descriptions of the work and major employers.
Summary of ICSE 2011 Panel on "What Industry wants from Research". This is a summary of all the presentations from that panel that I presented in an invited talk at the CSER meeting in Toronto, November, 2011.
Forty Years of Crisis, Ten Years of Agile, Now What?Morendil
The document discusses the history and future of agile software development. It begins by looking back at the origins of concerns over software failures in the 1960s. While practices like scrum and extreme programming became popular in the 2000s, software engineering remains the dominant approach despite not achieving success. The document frames agile as a disruptive innovation that challenges entrenched interests. It argues agile values people and collaboration over mechanistic approaches. However, agile still faces challenges to build an empirical evidence base, achieve consensus on practices and contracts, and improve education. The document calls for addressing these challenges to further agile's role in software development.
Social media & sentiment analysis splunk conf2012Michael Wilde
This presentation was delivered at Splunk's User Conference (conf2012). It covers info about social media data, how to index / use it with Splunk and a lot of content around Sentiment Analysis.
Business intelligence practices have been creating reports to help organizations make decisions for decades, but when it comes to social data, the usual models seem to fall apart. Social data doesn't neatly fit into tables, is often too large for charts, and too ill-defined for maps. Many businesses have defined social media as important, but getting that "down on paper" is still a struggle.
Join us for our upcoming webinar as we go through the three key strategies for turning your social data into an impactful report. We'll use our SocialScape Restaurant Report (a syndicated social media report sold by M/A/R/C®) as an example, going all the way back to concepts and sketches to show how we got to the final. We'll also highlight other work we've seen that can inspire your best work.
Get ready for a lot of data, a lot of answers, and a lot of tools you can take to your desk when you leave.
A technology trend presentation for activities professionals. Includes a brief introduction to Red Rover, a new piece of web software embodying the ideas presented in the session.
The document summarizes Lyn Murnane's career journey to becoming a Knowledge Manager. It discusses her past roles at companies like Telstra and Medibank where she helped redesign intranets and knowledge management systems. Currently, Lyn works as a Knowledge Manager at IDP Education, managing a global knowledge system with over 130,000 pieces of information that supports 700 staff across 27 countries. The document also provides an overview of concepts in knowledge management and Lyn's knowledge management framework.
By current estimates, we’re about a decade away from having exascale computing capability. That’s a pretty long time – especially in our world of HPC. What will the world be like in 2022? What form will exascale computing take when it’s real? These are difficult questions to answer. Never before has the HPC community focused so intensely on a machine so far beyond its grasp. Nevertheless, stalwart cadres around the globe are drafting strategies, plans, and roadmaps to get from here to exascale. So, what about the rest of us? Are there useful things we could do while waiting - or instead of waiting - for exascale? Perhaps there are. In this talk we’ll take a look at a few possibilities, including:
• Education
• eScience
• Big Data
• Broad HPC Deployment
• Computing in Industry
• Public Engagement
• Infrastructure Development and Build Out
• Success Metrics
Exascale computing may be a decade away, but there’s a lot to accomplish to be ready to exploit it. We’ll explore a few options here. We make no claim that these constitute the right agenda for the coming decade – nor do we suggest that we’ve given an exhaustive to-do list. Our intention is rather to open the conversation about what we should do while “waiting” for exascale.
SharePoint Governance. Stop features thinking, Patrick Sledz
The document discusses a different approach to SharePoint governance that focuses on achieving shared understanding among stakeholders rather than technical features. It advocates using issue mapping techniques to help groups develop a shared understanding of problems and potential solutions with less conflict. Key points include recognizing that requirements will change as understanding increases, avoiding platitudes in objectives that cannot be measured, and ensuring all voices are heard to prevent technical biases from dominating discussions.
The document discusses issues with traditional software engineering and data mining research and proposes new directions for the field. It notes that simply predicting outcomes is no longer sufficient and that research should aim to develop controllers and management methods. It asks why there is so much focus on software engineering and data mining, and argues it is due to an information explosion in software projects. The document calls for research that addresses broader issues and questions in the field, such as understanding the impact of data mining tools and techniques. It also stresses the importance of industry relevance and addressing conclusion instability in research.
This document introduces a talk on the relationship between research libraries and research enterprises. It notes increasing data production, openness, and interdisciplinarity in scholarship. It also highlights problems like unpublished results ending up in desk drawers, increased retractions, weak incentives for preserving evidence, and low compliance with replication policies. The talk will discuss how knowledge is a public good and the roles of libraries in subsidizing knowledge production and ensuring long-term access and reuse of digital content.
Search, citation and plagiarism: skills for a digital age have to be taught!CIT, NUS
The document discusses problems with students' writing skills in the digital age and proposes solutions to improve digital literacy. It notes issues like poor essay structure, referencing, and an inability to effectively search for and evaluate online sources. The proposed solutions include integrating writing assignments into core modules with feedback, teaching efficient search strategies, building vocabulary, evaluating site credibility, understanding citations, and providing clear guidelines. The goal is to explicitly teach digital skills that are assumed but often not learned, like searching, evaluating sources, and avoiding plagiarism.
Tablet apps, or the future of Digital Scholarly Editions?Elena Pierazzo
This document discusses the potential for tablet apps to promote digital scholarly editions (DSE). It notes that while DSEs offer new editing possibilities, their usage and citations remain low. Tablets could help by making DSE reading more pleasant. However, existing eBooks and DSEs do not fully utilize tablets' interactive capabilities. The document proposes research questions around whether tablets can bridge print and web for DSEs. It also outlines technological, design, and sustainability considerations for developing DSE apps.
The document outlines the objectives, outcomes, and learning outcomes of a course on artificial intelligence. The objectives include conceptualizing ideas and techniques for intelligent systems, understanding mechanisms of intelligent thought and action, and understanding advanced representation and search techniques. Outcomes include developing an understanding of AI building blocks, choosing appropriate problem solving methods, analyzing strengths and weaknesses of AI approaches, and designing models for reasoning with uncertainty. Learning outcomes include knowledge, intellectual skills, practical skills, and transferable skills in artificial intelligence.
This document discusses support for gifted children in classrooms. It suggests that the quality of thinking is critical for gifted students and outlines several strategies to support them both in and out of the classroom. These include using computers, independent study, having students teach others, and extracurricular activities. The document also discusses identifying gifted students and building lessons around their interests and passions. It proposes blended learning models and innovative opportunities like 3D printing to engage gifted students.
Mylyn helps address information overload and context loss when multi-tasking. It integrates tasks into the IDE workflow and uses a degree-of-interest model to monitor user interaction and provide a task-focused UI with features like view filtering, element decoration, automatic folding and content assist ranking. This creates a single view of all tasks that are centrally managed within the IDE.
This document provides an overview of OpenCV, an open source computer vision and machine learning software library. It discusses OpenCV's core functionality for representing images as matrices and directly accessing pixel data. It also covers topics like camera calibration, feature point extraction and matching, and estimating camera pose through techniques like structure from motion and planar homography. Hints are provided for Android developers on required permissions and for planar homography estimation using additional constraints rather than OpenCV's general homography function.
More Related Content
Similar to ICDE2010: DBMS: Lessons from the First 50 Years, Speculations for the Next 50
This document provides guidance on how to conduct high-quality research and write good papers. It discusses that research can involve solving existing problems using existing methods, improving existing solutions, or identifying new problems and generalizing solutions. The most innovative and impactful research involves identifying new problems. It emphasizes the importance of conducting new and useful research. It then provides tips for training innovation through extensive reading, writing, and rewriting to develop ideas. It discusses finding meaningful topics by starting from real problems and convincing others of the topic's importance. The document concludes by offering writing techniques such as overcoming language barriers, using an active voice, including visual elements, and being specific rather than vague.
Escaping the Knowledge Management Black Hole: New Approaches to Leveraging Or...Paul Culmsee
The document discusses challenges with managing tacit knowledge and debates different approaches. It argues that fully codifying tacit knowledge into explicit documentation is difficult and can have downsides. Instead, it proposes capturing experts' reflections on video and linking them to dialogue maps that represent the rationale without over-codifying details. This preserves context while allowing others to navigate complex discussions. The approach aims to efficiently leverage expert time and knowledge within SharePoint systems.
This document discusses the intersection of machine learning and search-based software engineering (ML & SBSE). It provides examples of how data miners can find signals in software engineering artifacts using machine learning techniques. It then discusses how better algorithms do not necessarily lead to better mining yet and emphasizes the importance of sharing data, models, and analysis methods. Finally, it outlines a vision for "discussion mining" to guide teams in walking across the space of local models, with the goal of building a science of localism in ML and SBSE.
Career introduction of Engineering Student SSVIT rizwanRizwan Khan
This document provides career guidance for senior secondary students. It discusses why career guidance is important, current trends in career selection, who is responsible for career guidance, and an overview of the career cycle. It emphasizes the importance of selecting a career and planning for one's future. Students are advised to discover their interests and strengths, consider their education and career options, and prepare for obstacles through hard work and perseverance. Engineering is presented as a field that applies math and science to solve problems and improve life. Several types of engineering careers are outlined, including descriptions of the work and major employers.
Summary of ICSE 2011 Panel on "What Industry wants from Research". This is a summary of all the presentations from that panel that I presented in an invited talk at the CSER meeting in Toronto, November, 2011.
Forty Years of Crisis, Ten Years of Agile, Now What?Morendil
The document discusses the history and future of agile software development. It begins by looking back at the origins of concerns over software failures in the 1960s. While practices like scrum and extreme programming became popular in the 2000s, software engineering remains the dominant approach despite not achieving success. The document frames agile as a disruptive innovation that challenges entrenched interests. It argues agile values people and collaboration over mechanistic approaches. However, agile still faces challenges to build an empirical evidence base, achieve consensus on practices and contracts, and improve education. The document calls for addressing these challenges to further agile's role in software development.
Social media & sentiment analysis splunk conf2012Michael Wilde
This presentation was delivered at Splunk's User Conference (conf2012). It covers info about social media data, how to index / use it with Splunk and a lot of content around Sentiment Analysis.
Business intelligence practices have been creating reports to help organizations make decisions for decades, but when it comes to social data, the usual models seem to fall apart. Social data doesn't neatly fit into tables, is often too large for charts, and too ill-defined for maps. Many businesses have defined social media as important, but getting that "down on paper" is still a struggle.
Join us for our upcoming webinar as we go through the three key strategies for turning your social data into an impactful report. We'll use our SocialScape Restaurant Report (a syndicated social media report sold by M/A/R/C®) as an example, going all the way back to concepts and sketches to show how we got to the final. We'll also highlight other work we've seen that can inspire your best work.
Get ready for a lot of data, a lot of answers, and a lot of tools you can take to your desk when you leave.
A technology trend presentation for activities professionals. Includes a brief introduction to Red Rover, a new piece of web software embodying the ideas presented in the session.
The document summarizes Lyn Murnane's career journey to becoming a Knowledge Manager. It discusses her past roles at companies like Telstra and Medibank where she helped redesign intranets and knowledge management systems. Currently, Lyn works as a Knowledge Manager at IDP Education, managing a global knowledge system with over 130,000 pieces of information that supports 700 staff across 27 countries. The document also provides an overview of concepts in knowledge management and Lyn's knowledge management framework.
By current estimates, we’re about a decade away from having exascale computing capability. That’s a pretty long time – especially in our world of HPC. What will the world be like in 2022? What form will exascale computing take when it’s real? These are difficult questions to answer. Never before has the HPC community focused so intensely on a machine so far beyond its grasp. Nevertheless, stalwart cadres around the globe are drafting strategies, plans, and roadmaps to get from here to exascale. So, what about the rest of us? Are there useful things we could do while waiting - or instead of waiting - for exascale? Perhaps there are. In this talk we’ll take a look at a few possibilities, including:
• Education
• eScience
• Big Data
• Broad HPC Deployment
• Computing in Industry
• Public Engagement
• Infrastructure Development and Build Out
• Success Metrics
Exascale computing may be a decade away, but there’s a lot to accomplish to be ready to exploit it. We’ll explore a few options here. We make no claim that these constitute the right agenda for the coming decade – nor do we suggest that we’ve given an exhaustive to-do list. Our intention is rather to open the conversation about what we should do while “waiting” for exascale.
SharePoint Governance. Stop features thinking, Patrick Sledz
The document discusses a different approach to SharePoint governance that focuses on achieving shared understanding among stakeholders rather than technical features. It advocates using issue mapping techniques to help groups develop a shared understanding of problems and potential solutions with less conflict. Key points include recognizing that requirements will change as understanding increases, avoiding platitudes in objectives that cannot be measured, and ensuring all voices are heard to prevent technical biases from dominating discussions.
The document discusses issues with traditional software engineering and data mining research and proposes new directions for the field. It notes that simply predicting outcomes is no longer sufficient and that research should aim to develop controllers and management methods. It asks why there is so much focus on software engineering and data mining, and argues it is due to an information explosion in software projects. The document calls for research that addresses broader issues and questions in the field, such as understanding the impact of data mining tools and techniques. It also stresses the importance of industry relevance and addressing conclusion instability in research.
This document introduces a talk on the relationship between research libraries and research enterprises. It notes increasing data production, openness, and interdisciplinarity in scholarship. It also highlights problems like unpublished results ending up in desk drawers, increased retractions, weak incentives for preserving evidence, and low compliance with replication policies. The talk will discuss how knowledge is a public good and the roles of libraries in subsidizing knowledge production and ensuring long-term access and reuse of digital content.
Search, citation and plagiarism: skills for a digital age have to be taught!CIT, NUS
The document discusses problems with students' writing skills in the digital age and proposes solutions to improve digital literacy. It notes issues like poor essay structure, referencing, and an inability to effectively search for and evaluate online sources. The proposed solutions include integrating writing assignments into core modules with feedback, teaching efficient search strategies, building vocabulary, evaluating site credibility, understanding citations, and providing clear guidelines. The goal is to explicitly teach digital skills that are assumed but often not learned, like searching, evaluating sources, and avoiding plagiarism.
Tablet apps, or the future of Digital Scholarly Editions?Elena Pierazzo
This document discusses the potential for tablet apps to promote digital scholarly editions (DSE). It notes that while DSEs offer new editing possibilities, their usage and citations remain low. Tablets could help by making DSE reading more pleasant. However, existing eBooks and DSEs do not fully utilize tablets' interactive capabilities. The document proposes research questions around whether tablets can bridge print and web for DSEs. It also outlines technological, design, and sustainability considerations for developing DSE apps.
The document outlines the objectives, outcomes, and learning outcomes of a course on artificial intelligence. The objectives include conceptualizing ideas and techniques for intelligent systems, understanding mechanisms of intelligent thought and action, and understanding advanced representation and search techniques. Outcomes include developing an understanding of AI building blocks, choosing appropriate problem solving methods, analyzing strengths and weaknesses of AI approaches, and designing models for reasoning with uncertainty. Learning outcomes include knowledge, intellectual skills, practical skills, and transferable skills in artificial intelligence.
This document discusses support for gifted children in classrooms. It suggests that the quality of thinking is critical for gifted students and outlines several strategies to support them both in and out of the classroom. These include using computers, independent study, having students teach others, and extracurricular activities. The document also discusses identifying gifted students and building lessons around their interests and passions. It proposes blended learning models and innovative opportunities like 3D printing to engage gifted students.
Similar to ICDE2010: DBMS: Lessons from the First 50 Years, Speculations for the Next 50 (20)
Mylyn helps address information overload and context loss when multi-tasking. It integrates tasks into the IDE workflow and uses a degree-of-interest model to monitor user interaction and provide a task-focused UI with features like view filtering, element decoration, automatic folding and content assist ranking. This creates a single view of all tasks that are centrally managed within the IDE.
This document provides an overview of OpenCV, an open source computer vision and machine learning software library. It discusses OpenCV's core functionality for representing images as matrices and directly accessing pixel data. It also covers topics like camera calibration, feature point extraction and matching, and estimating camera pose through techniques like structure from motion and planar homography. Hints are provided for Android developers on required permissions and for planar homography estimation using additional constraints rather than OpenCV's general homography function.
This document provides information about the Computer Vision Laboratory 2012 course at the Institute of Visual Computing. The course focuses on computer vision on mobile devices and will involve 180 hours of project work per person. Students will work in groups of 1-2 people on topics like 3D reconstruction from silhouettes or stereo images on mobile devices. Key dates are provided for submitting a work plan, mid-term presentation, and final report. Contact information is given for the lecturers and teaching assistant.
This document summarizes a presentation on natural image statistics given by Siwei Lyu at the 2009 CIFAR NCAP Summer School. The presentation covered several key topics:
1) It discussed the motivation for studying natural image statistics, which is to understand representations in the visual system and develop computer vision applications like denoising.
2) It reviewed common statistical properties found in natural images like 1/f power spectra and non-Gaussian distributions.
3) Maximum entropy and Bayesian models were presented as approaches to model these statistics, with Gaussian and independent component analysis discussed as specific examples.
4) Efficient coding principles from information theory were introduced as a framework for understanding neural representations that aim to decorrelate and
Camera calibration involves determining the internal camera parameters like focal length, image center, distortion, and scaling factors that affect the imaging process. These parameters are important for applications like 3D reconstruction and robotics that require understanding the relationship between 3D world points and their 2D projections in an image. The document describes estimating internal parameters by taking images of a calibration target with known geometry and solving the equations that relate the 3D target points to their 2D image locations. Homogeneous coordinates and projection matrices are used to represent the calibration transformations mathematically.
Brunelli 2008: template matching techniques in computer visionzukun
The document discusses template matching techniques in computer vision. It begins with an overview that defines template matching and discusses some common computer vision tasks it can be used for, like object detection. It then covers topics like detection as hypothesis testing, training and testing techniques, and provides a bibliography.
The HARVEST Programme evaluates feature detectors and descriptors through indirect and direct benchmarks. Indirect benchmarks measure repeatability and matching scores on the affine covariant testbed to evaluate how features persist across transformations. Direct benchmarks evaluate features on image retrieval tasks using the Oxford 5k dataset to measure real-world performance. VLBenchmarks provides software for easily running these benchmarks and reproducing published results. It allows comparing features and selecting the best for a given application.
This document summarizes VLFeat, an open source computer vision library. It provides concise summaries of VLFeat's features, including SIFT, MSER, and other covariant detectors. It also compares VLFeat's performance to other libraries like OpenCV. The document highlights how VLFeat achieves state-of-the-art results in tasks like feature detection, description and matching while maintaining a simple MATLAB interface.
This document summarizes and compares local image descriptors. It begins with an introduction to modern descriptors like SIFT, SURF and DAISY. It then discusses efficient descriptors such as binary descriptors like BRIEF, ORB and BRISK which use comparisons of intensity value pairs. The document concludes with an overview section.
This document discusses various feature detectors used in computer vision. It begins by describing classic detectors such as the Harris detector and Hessian detector that search scale space to find distinguished locations. It then discusses detecting features at multiple scales using the Laplacian of Gaussian and determinant of Hessian. The document also covers affine covariant detectors such as maximally stable extremal regions and affine shape adaptation. It discusses approaches for speeding up detection using approximations like those in SURF and learning to emulate detectors. Finally, it outlines new developments in feature detection.
The document discusses modern feature detection techniques. It provides an introduction and agenda for a talk on advances in feature detectors and descriptors, including improvements since a 2005 paper. It also discusses software suites and benchmarks for feature detection. Several application domains are described, such as wide baseline matching, panoramic image stitching, 3D reconstruction, image search, location recognition, and object tracking.
System 1 and System 2 were basic early systems for image matching that used color and texture matching. Descriptor-based approaches like SIFT provided more invariance but not perfect invariance. Patch descriptors like SIFT were improved by making them more invariant to lighting changes like color and illumination shifts. The best performance came from combining descriptors with color invariance. Representing images as histograms of visual word occurrences captured patterns in local image patches and allowed measuring similarity between images. Large vocabularies of visual words provided more discriminative power but were costly to compute and store.
This document summarizes a research paper on internet video search. It discusses several key challenges: [1] the large variation in how the same thing can appear in images/videos due to lighting, viewpoint etc., [2] defining what defines different objects, and [3] the huge number of different things that exist. It also notes gaps in narrative understanding, shared concepts between humans and machines, and addressing diverse query contexts. The document advocates developing powerful yet simple visual features that capture uniqueness with invariance to irrelevant changes.
The document discusses computer vision techniques for object detection and localization. It describes methods like selective search that group image regions hierarchically to propose object locations. Large datasets like ImageNet and LabelMe that provide training examples are also discussed. Performance on object detection benchmarks like PASCAL VOC is shown to improve significantly over time. Evaluation standards for concept detection like those used in TRECVID are presented. The document concludes that results are impressively improving each year but that the number of detectable concepts remains limited. It also discusses making feature extraction more efficient using techniques like SURF that take advantage of integral images.
This document provides an outline and overview of Yoshua Bengio's 2012 tutorial on representation learning. The key points covered include:
1) The tutorial will cover motivations for representation learning, algorithms such as probabilistic models and auto-encoders, and analysis and practical issues.
2) Representation learning aims to automatically learn good representations of data rather than relying on handcrafted features. Learning representations can help address challenges like exploiting unlabeled data and the curse of dimensionality.
3) Deep learning algorithms attempt to learn multiple levels of increasingly complex representations, with the goal of developing more abstract, disentangled representations that generalize beyond local patterns in the data.
Advances in discrete energy minimisation for computer visionzukun
This document discusses string algorithms and data structures. It introduces the Knuth-Morris-Pratt algorithm for finding patterns in strings in O(n+m) time where n is the length of the text and m is the length of the pattern. It also discusses common string data structures like tries, suffix trees, and suffix arrays. Suffix trees and suffix arrays store all suffixes of a string and support efficient pattern matching and other string operations in linear time or O(m+logn) time where m is the pattern length and n is the text length.
This document provides a tutorial on how to use Gephi software to analyze and visualize network graphs. It outlines the basic steps of importing a sample graph file, applying layout algorithms to organize the nodes, calculating metrics, detecting communities, filtering the graph, and exporting/saving the results. The tutorial demonstrates features of Gephi including node ranking, partitioning, and interactive visualization of the graph.
EM algorithm and its application in probabilistic latent semantic analysiszukun
The document discusses the EM algorithm and its application in Probabilistic Latent Semantic Analysis (pLSA). It begins by introducing the parameter estimation problem and comparing frequentist and Bayesian approaches. It then describes the EM algorithm, which iteratively computes lower bounds to the log-likelihood function. Finally, it applies the EM algorithm to pLSA by modeling documents and words as arising from a mixture of latent topics.
This document describes an efficient framework for part-based object recognition using pictorial structures. The framework represents objects as graphs of parts with spatial relationships. It finds the optimal configuration of parts through global minimization using distance transforms, allowing fast computation despite modeling complex spatial relationships between parts. This enables soft detection to handle partial occlusion without early decisions about part locations.
Iccv2011 learning spatiotemporal graphs of human activities zukun
The document presents a new approach for learning spatiotemporal graphs of human activities from weakly supervised video data. The approach uses 2D+t tubes as mid-level features to represent activities as segmentation graphs, with nodes describing tubes and edges describing various relations. A probabilistic graph mixture model is used to model activities, and learning estimates the model parameters and permutation matrices using a structural EM algorithm. The learned models allow recognizing and segmenting activities in new videos through robust least squares inference. Evaluation on benchmark datasets demonstrates the ability to learn characteristic parts of activities and recognize them under weak supervision.
This presentation was provided by Racquel Jemison, Ph.D., Christina MacLaughlin, Ph.D., and Paulomi Majumder. Ph.D., all of the American Chemical Society, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
How Barcodes Can Be Leveraged Within Odoo 17Celine George
In this presentation, we will explore how barcodes can be leveraged within Odoo 17 to streamline our manufacturing processes. We will cover the configuration steps, how to utilize barcodes in different manufacturing scenarios, and the overall benefits of implementing this technology.
Leveraging Generative AI to Drive Nonprofit InnovationTechSoup
In this webinar, participants learned how to utilize Generative AI to streamline operations and elevate member engagement. Amazon Web Service experts provided a customer specific use cases and dived into low/no-code tools that are quick and easy to deploy through Amazon Web Service (AWS.)
A Visual Guide to 1 Samuel | A Tale of Two HeartsSteve Thomason
These slides walk through the story of 1 Samuel. Samuel is the last judge of Israel. The people reject God and want a king. Saul is anointed as the first king, but he is not a good king. David, the shepherd boy is anointed and Saul is envious of him. David shows honor while Saul continues to self destruct.
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
Beyond Degrees - Empowering the Workforce in the Context of Skills-First.pptxEduSkills OECD
Iván Bornacelly, Policy Analyst at the OECD Centre for Skills, OECD, presents at the webinar 'Tackling job market gaps with a skills-first approach' on 12 June 2024
Gender and Mental Health - Counselling and Family Therapy Applications and In...PsychoTech Services
A proprietary approach developed by bringing together the best of learning theories from Psychology, design principles from the world of visualization, and pedagogical methods from over a decade of training experience, that enables you to: Learn better, faster!
This presentation was provided by Rebecca Benner, Ph.D., of the American Society of Anesthesiologists, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
Elevate Your Nonprofit's Online Presence_ A Guide to Effective SEO Strategies...TechSoup
Whether you're new to SEO or looking to refine your existing strategies, this webinar will provide you with actionable insights and practical tips to elevate your nonprofit's online presence.
Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
Chapter wise All Notes of First year Basic Civil Engineering.pptx
ICDE2010: DBMS: Lessons from the First 50 Years, Speculations for the Next 50
1. DBMS Research:
First 50 Years,
Next 50 Years
Jeffrey F. Naughton
Jeffrey F. Naughton
2. Reactions
to
This
Keynote
From
Colleagues…
Jeffrey
F.
Naughton
Assistant
“Cool,
I
look
forward
to
it.”
Professor
?
(upon
hearing
what
I
proposed
to
talk
about):
Associate
“But
how
are
you
going
to
make
that
Professor
#1
?
interesting?”
“Well,
you
have
reached
the
age
where
Associate
Professor
?
you
can
scratch
your
butt
in
public,
go
#2
ahead.”
Emeritus
“Don’t
do
it.
Giving
a
keynote
means
Professor
?
you
are
a
washed-‐up
has-‐been.”
2
3. My
Goals…
Talk
about
why
I
think
DBMS
research
has
been
so
rewarding
over
the
past
50
years
Some
personal
anecdotes
from
a
“washed-‐up
has-‐been”
about
fun
work
that
would
be
discouraged
today
Discuss
why
the
next
50
years
are
at
risk
and
what
we
can
do
about
it
Avoid
scratching
Make
this
“interesting”
4. Long,
Long
Ago…
William
McGee
published
a
J.
ACM
paper
“Generalization: Key to
Successful Electronic Data
Processing.”
[Jan. ’59]
Great
first
sentence:
“The wholesale acceptance of
electronic data processing
machines […] is ample proof
that management is beginning
to recognize the potential of
this new tool.”
5. The
More
Things
Change…
Another
sentence
from
McGee’s
intro:
“management is
increasingly concerned over
the continued high cost of
installing and maintaining
data processing systems.”
7. More
On
The
702
• Memory
(cathode
ray
tubes):
20K
bytes.
• Disk
(magnetic
drum):
60K
bytes.
• CPU:
10MIPH
– MIPH
=
Million
Instructions
Per
Hour
– For
those
of
you
without
calculators,
that
is
about
0.000278
MIPS
– Or,
if
you
like,
a
0.000000278
GHz
processor.
7
8. A
Note
About
This
Early
History…
The
commercial,
technical,
and
intellectual
seeds
that
grew
into
our
community
were
planted
long
ago
8
9. Problem:
File-‐Dependent
Programming
• Write
a
sort
program
for
the
payroll
file
• Write
another
sort
program
for
the
accounts
receivable
file
• No
sharing
– between
files
– between
applications
– between
institutions
Solution:
“generalized
programming”
9
10. What
Do
You
Need
for
Generalized
Programming?
• A
description
of
the
record
layouts
in
the
file
• Ideally,
in
some
place
should
also
capture
elements
in
common
to
multiple
files
Schemas
• Programs
that
– Interpret
these
descriptions
and
– Make
it
easy
to
express
generally
useful
operations
(sorting,
reporting)
on
the
files
Data
Manipulation
Languages
10
11. Another
Problem:
Updates
• How
do
you
undo
mistakes?
• How
do
you
handle
failures
in
middle
of
processing?
Solution:
in
a
separate
file,
write
before/after
images
of
updated
records.
(Logging)
11
12. So
What’s
the
Point?
1940S 1950s … 1970s 1990s 2000s … TODAY
The
seeds
of
a
rich
and
vibrant
database
management
research
community
were
planted
In
particular,
• Strong
commercial
interest
with
$$$
behind
it
• Common
non-‐trivial
technical
challenges
related
to
data
management
• A
set
of
problems
amenable
to
abstraction
and
generalization
13. Fast
Forward
to
Today…
1940S 1950s … 1970s 1990s 2000s … TODAY
• These
three
key
factors
– commercial
interest
– common
data
management
challenges
– attractive
problems
are
present
now
more
than
ever
That
is
the
good
news!
13
14. What
About
the
Research
Community?
• Maybe
it
is
in
good
shape
– But
I
am
not
so
sure
• Maybe
it
is
headed
in
a
good
direction
– But
I
am
less
sure
Modern DB Research
• We
worry
a
lot
about
what
to
work
on
– I
am
not
worried
about
this
• We
are
increasingly
valuing
and
rewarding
the
wrong
things
– I
am
worried
about
this
14
15. The
Problem
I
Worry
About
The
combination
of:
– Pressure
to
publish
lots
of
papers
+
– Low
acceptance
rates
+
– Bad
reviewing
is
sucking
the
air
out
of
our
community
Modern
Database
Researcher
15
16. Doomsday
Scenario
Being
a
database
researcher
means
a
life
filled
with
all
the
joy,
meaning,
and
creativity
of
studying
for
and
taking
college
entrance
exams
16
17. Doomsday
is
Here
• We
behave
as
if
–
Researchers
are
“students”
–
PC
members
are
“graders”
–
Publications
pose
“exam
questions”
–
New
submissions
are
“answers”
• These
“exams”
are
perceived
as
the
only
path
to
success
in
the
community
17
18. Some
More
on
the
Analogy…
• The
“students”
are
not
that
interested
in
the
questions
• The
“graders”
are
even
less
interested
in
the
answers
• No
one
else
is
interested
in
either,
caring
only
about
the
scores
Everyone
what’s the score?
18
19. So
What
is
Wrong
With
This?
What
kind
of
people
will
Who
wants
to
spend
their
life
this
scenario
attract
to
our
taking
meaningless
exams?
field?
What
kind
of
work
will
be
+”
common
in
this
“A environment?
19
20. My
Take…
The
problem
isn’t
“Researchers
today!
They
need
to
be
more
like
the
researchers
in
the
good
old
days!”
Rather,
it
is
more
“we
need
to
re-‐think
the
environment
we
have
created
and
what
it
encourages”
More
on
this
later,
first
some
“old
war
stories”
20
22. War
Story
#1:
The
Sorting
Record
1940S 1950s … 1970s 1980s 2000s … TODAY
DeWitt
had
a
parallel
DBMS
project
(Gamma)
• Very
fortunately
for
me,
he
let
me
join
• One
of
the
things
we
worked
on:
– parallel
sorting
on
an
Intel
iPSC-‐2
Hypercube
– (Donovan
Schneider
was
key
to
this
project.)
• Our
main
idea:
– Use
parallel
sampling
to
probabilistically
pick
range
partitioning
cutoffs
– Repartition
the
data
– Sort
locally
22
23. In
Those
Days…
• It
still
made
(a
little)
sense
to
try
the
original
sort
benchmark:
– 1M
100
byte
records
(now
perhaps
known
as
wristwatch
sort)
• I
think
our
time
was
something
like
30
seconds
• We
mentioned
it
to
Jim
Gray
when
he
visited
Wisconsin.
– (it
seemed
a
safe
enough
thing
to
do)
23
24. Maybe
6
Months
Later…
• Gray
called
me
up
and
invited
me
to
visit
the
DEC
Bay
Area
Research
Center
• Said
they
wanted
to
hear
about
my
work
(that
alone
should
have
made
me
suspicious)
24
25. With
Some
Trepidation
I
Flew
Out
(folks
from
Wisconsin
don’t
require
too
much
reason
to
fly
to
CA
in
the
winter)
CA
WI
25
26. At
the
Talk…
• Oddly,
quite
a
few
people
were
there
• At
the
end,
they
asked
“are
you
finished?”
• When
I
said
yes,
– A
lot
of
cameras
appeared.
– Also
a
large
trophy
World’s
Record for
Sorting
• They
handed
it
to
me
and
said
we
had
set
the
world
record
for
sorting!
26
27. Continuing
With
the
Story…
• I
basked
in
the
glory
for
about
5
seconds
• Then
they
announced:
– “We
have
beaten
your
record.”
– “Please
hand
the
trophy
to
Chris,
we
want
a
picture
of
the
hand-‐over.”
27
28. Would
You
Do
This
Today?
• It
was
perhaps
6
months
work
for
three
researchers
• Yielded
one
paper
in
a
minor
conference
Today
it
would
be
zero
papers!
I
can
see
the
reviews:
“Reject:
Not
enough
math,
can’t
be
deep.”
“Reject:
Superficial
performance
evaluation.”
“Reject:
Their
sorting
program
cannot
converse
in
English
like
the
Star
Trek
computer.”
28
29. Today
We
Probably
Couldn’t
Spare
the
Time
to
do
This
• A
team
of
halfway
decent
researchers:
– should
(must?)
write
more
than
one
paper
in
six
months
– should
do
much
more
reviewer-‐proof
work
than
implementing
and
running
a
sorting
algorithm
29
30. Was
it
Worth
Doing?
Yes!
– Taught
me
a
ton
about
sampling
in
parallel
DBMS
– Convinced
me
of
the
importance
of
processor
architecture
in
performance
• the
BARC
guys
smoked
us
with
a
uniprocessor
implementation
by
making
clever
use
of
the
cache
YOU BET!
– It
was
really
fun
and
kept
me
interested
and
connected
with
the
field
30
31. War
Story
#2:
007
Benchmark
Carey,
DeWitt,
and
I
decided
to
benchmark
object
oriented
DBMS
+
+
=
• We
– designed
the
benchmark
– negotiated
with
four
vendors
to
get
them
involved
– implemented
it
on
five
systems
• four
commercial
plus
our
own
– started
running
tests
This
was
a
huge
amount
of
work!
31
32. After
Months
of
Work…
• We
received
a
fax
from
a
law
firm
representing
one
of
the
companies
• The
fax
ordered
us
FAX
– to
stop
benchmarking
their
system
– and
to
destroy
all
copies
of
their
system
that
we
might
have
We
reacted
extremely
maturely
as
usual…
32
33. The
Next
Morning…
• I
woke
up
early
• Made
a
big
pot
of
coffee
• Drank
most
of
it
• Fired
off
an
angry
fax
– demanding
that
the
company
destroy
all
copies
of
our
benchmark
implementation
We
knew
they
were
using
it
for
internal
testing.
We
were
pissed.
33
34. 15
Minutes
After
Sending
the
Fax
• I
received
a
phone
call
• The
following
conversation
ensued:
– Confused Woman: “Professor Naughton?”
– Indignant Professor: “Yes?”
– Confused Woman: “This is First National Bank, we
received a fax from you about destroying a
benchmark…”
– Sheepish Professor: “OK, please comply, thanks.”
34
35. Would
This
Project
be
Smart
Now?
• Probably
not
#1:
ie wer
– Three
profs,
18+
months,
one
paper?
Rev
– Again,
today
would
be
zero
papers.
Reject.
No new algorithms!
Rej
• Reviews
today
would
be:
Sho
uld ect.
co
SPE mpare
Cma with
rk!
Accept.
Lots of graphs!
Reviewer
#3:
35
36. Worth
It?
• We
certainly
learned
a
lot
about:
– OODBMS
technology
– Stresses
companies
(and
researchers)
are
under
with
respect
to
benchmarking
– Legal
issues
– Pitfalls
in
designing
benchmarks
– Interaction
with
popular
tech
press
Positive
for
all
of
us,
but
would
be
discouraged
by
today’s
environment
36
37. Point
of
the
War
Stories…
• At
least
for
me,
some
of
the
most
rewarding
work
did
not
have
a
publication
as
its
goal
Goal
• At
least
for
me,
some
of
the
most
rewarding
work
did
not
result
in
many
publications
Result
• At
least
for
me,
some
of
the
most
rewarding
work
did
not
result
in
any
papers
that
would
pass
today’s
program
committees
Result
Accept.
37
38. These
days
I
fear
we
are
• Discouraging
work
motivated
by
asking:
– Can
we
learn
something?
– Can
we
build
something?
– Can
we
prove
something?
– Can
we
improve
something?
• Encouraging
work
motivated
by
asking:
– Can
I
write
a
paper
before
the
deadline?
38
39. Today…
• We
are
so
frenetically
pursuing
the
next
conference
deadline
…under
the
watchful
glare
of
bad
reviewing,
…that
the
freedom
required
to
do
exploratory
work
is
disappearing.
39
40. Three
Factors
Causing
Problems
Low
acceptance
rates
Emphasis
on
paper
count
Bad
reviewing
Let’s
consider
them
in
order
41. The
Problem
With
Low
Acceptance
Rates
• Very
discouraging
• Reduces
tolerance
for
errors
in
reviewing
• Enforces
evaluation
of
work
by
three
randomly
chosen
reviewers
rather
than
the
community
• Makes
major
event
in
the
course
of
research
acceptance/rejection,
not
scientific
or
engineering
progress
41
42. How
to
Fix
Low
Acceptance
Rates
• Increase
acceptance
rates
(duh!)
• Mandate
a
target
• Hoped
for
effects:
– Fewer
rejections
– Fewer
papers
sloshing
from
conference
to
conference
– Reduce
the
damage
done
by
bad
reviewing
42
43. Turning
to
Paper
Count
• Paper
count
inflation
paper
count
– To
be
a
success,
people
feel
one
has
to
publish
a
lot
of
papers
– To
publish
a
lot
of
papers,
one
has
to
get
past
a
lot
of
program
committees
• To
do
this
is
a
more
than
full
[No Time to Explore]
time
job
• Leaves
too
little
room
for
activities
not
focused
on
generating
publications
43
44. Tough
to
Fix,
but…
Let
people
in
on
a
secret:
– In
general
paper
count
is
much
less
important
in
evaluaAons
than
you
might
think.
– Stars
are
never
evaluated
by
paper
count
It
is
OK
to
write
a
lot
of
papers.
– Just
don’t
make
it
the
primary
metric
moAvaAng
researchers.
– Don’t
let
it
block
those
who
have
a
different
“research
style.”
Paper
Count
=
Quality
Measure
44
45. Acceptance
Rate
Again
• Hypothesis:
emphasis
on
paper
count
can
be
somewhat
ameliorated
by
increasing
acceptance
rate
– If
it
is
easier
to
publish
papers,
publishing
lots
of
them
will
be
perceived
as
less
impressive
– ShiR
the
focus
from
paper
count
to
paper
quality
45
46. Third
Issue:
Bad
Reviewing
• Very
hard
to
fix
• Very
important
to
fix
• Extremely
important
to
discuss
because
it
gives
me
a
chance
to
vent
Reviewing
System
Reviewer
Paper
Reviewer
Reviewer
46
47. Caveat!
• I
have
received
extremely
helpful
while
ulAmately
negaAve
reviews.
• These
reviews
have
dramaAcally
helped
me
and
my
co-‐authors
with
the
presentaAon
and
content
of
the
work.
• I
am
very
grateful
to
those
reviewers.
• These
“helpful
but
negaAve”
reviews
are
not
the
same
as
the
“bad”
reviews
I
will
discuss
next!
47
48. One
problem:
Reviewers
Hate
EVERYTHING!
• One
anecdote:
SIGMOD
2010
Anonymous
•
350
submissions
Reviewer
– Number
of
papers
with
all
reviews
“accept”
or
higher:
1
– Number
of
papers
with
average
“accept”
or
higher:
4
Either
we
all
suck
or
something
is
broken!
48
49. PC
Reviewing
is
Important
• This
is
the
primary
place
most
researchers
get
most
of
their
outside
feedback
• This
feedback
trains
most
researchers
in:
– What
to
do
for
their
next
submission
– How
to
evaluate
others
Feedback
Feedback
Feedback
Feedback
Receiving
dysfunctional
reviews
begets
writing
dysfunctional
reviews
49
50. Why
is
This
Bad?
• Discouraging
for
authors
• Devastating
when
it
occurs
in
grant
proposal
reviewing
– Funding
agencies
believe
us
when
we
say
we
suck
• The
absolute
score
can
be
fixed
by
enforced
scaling
More
fundamental
problem:
papers
are
being
rejected
for
the
wrong
reasons
50
51. What
is
Modern
Reviewing
Most
Like?
Your
paper
is
not
bullet
proof.
• Today
reviewing
is
like
grading
• Perhaps
because
so
many
reviewers
are
professsors
or
JECT
RE
students
or
former
students?
OK,
I
will
focus
all
my
energy
on
fixing
that
before
the
next
deadline.
51
52. But
Reviewing
is
Not
Grading
• When
grading
exams,
zero
credit
goes
for
thinking
of
the
question
– (good)
reviewing:
acknowledges
that
the
question
can
be
the
major
contribution
• When
grading
exams,
zero
credit
goes
for
a
novel
approach
to
solution.
– (good)
reviewing:
acknowledges
that
a
novel
approach
can
be
more
important
than
the
existence
of
the
solution
52
53. Bad
Reviewing:
Rejection
Checklist
Reviewing
• Rejection
checklist:
– Is
it
“difficult”?
– Is
it
“complete”?
– Can
I
find
any
flaw?
– Can
I
kill
it
quickly?
• Writing
negative
reviews
à
you
are
intelligent
and
have
high
standards
• Finding
the
positive
in
a
flawed
paper
à
you
are
soft,
stupid,
and
have
low
standards
53
54. Bad
Reviewing
2
• The
“dog
and
bone”
model
of
reviewing
– The
reviewer
is
a
dog
– The
reviewer’s
previous
work
is
a
bone
– The
author
of
the
new
paper
is
another
dog
trying
to
steal
the
bone
– Response
by
the
reviewer:
growl
like
hell
Reviewer’s
response
Grrrrrrrrrrrrrr…
Reviewer
Reviewer’s
previous
work
Systems
folks
seem
much
much
worse
about
this
than
theoreticians
54
55. Bad
Reviewing
3
• The
ignorant
but
I’ll
fake
it
Ull
I
confident
reviewer
make
it
• Doesn’t
know
what
is
going
on
but
would
rather
fake
it
than
admit
it
• Seems
to
feel
admission
of
lack
of
knowledge
would
reveal
a
weakness
– The
exact
opposite
is
true
55
56. Why
Are
Things
Bad?
• One
explanaUon:
reviewers
are
bad
people
• More
likely:
reviewers
are
being
poorly
trained
• In
prehistoric
Ames
– We
had
face-‐to-‐face
PC
meeAngs
– There
was
a
lot
of
accountability
pressure
– There
was
a
lot
of
coaching
and
mentoring
Experience
Experience
Exp
Exp
56
57. What
Is
the
Training
Today?
• Reviewers
are
trained
by
receiving
bad
reviews
from
other
reviewers
who
have
received
bad
reviews
in
the
past
57
58. Can
We
Change
This?
• Here
are
some
ideas,
with
the
goal:
– Encourage
discussion
– Argue
that
change
is
possible
– Agitate
for
change
– Some
are
deliberately
far
fetched!
58
59. Idea
#1:
Disarm
the
Killers
• A
large
part
of
“success”
in
conference
submissions
is
getting
a
lucky
assignment
of
reviewers
– If
you
get
a
“killer”
reviewer,
you
are
dead
– So
you
resubmit
until
you
have
three
non-‐killers
• Possible
solution:
– Mandate
a
certain
percentage
of
“accepts”
from
each
reviewer
59
60. Idea
#2:
Shine
Light
on
the
Process
• Publish
reviews
– Might
already
encourage
more
care
in
reviewing
– At
the
very
least
it
would
be
cathartic
• Allow
voting
for
best
reviews
– Somehow
reward
best
reviewers?
• Allow
voting
for
worst
reviews
– And?
60
61. Idea
#3:
Return
to
the
Past
• Require
face-‐to-‐face
PC
meetings
• Perhaps
have
partitioned
committees
to
make
this
tractable
• Restore
accountability
for
reviews
• Create
opportunities
for
mentorship
Mentorship
Accountability
61
62. Proposal
#4:
Single-‐Blind
Reviewing
• But
reverse
it:
– Reviewer
doesn’t
know
author
– Author
knows
reviewer
• So
– You
know
who
is
criticizing
you,
but
not
who
you
are
criticizing
– Would
certainly
encourage
more
thoughtful
reviewing
Reviewers
Authors
62
63. Proposal
#5:
Eliminate
the
Problem
• No
reviewing!
• Accept
everything.
• Let
the
community
sort
things
out
over
time.
• Why
are
we
still
behaving
as
if
our
proceedings
are
printed
by
overworked
monks
on
a
Gutenberg
press?
63
64. Wrapping
Up
the
Talk
• There
is
a
lot
of
angst
in
the
field
– Where
are
the
big
new
ideas?
– What
defines
us
as
a
community?
– How
did
we
miss
the
web?
– How
long
is
this
guy
going
to
talk
in
this
keynote?
• These
are
all
great
questions,
worthy
of
discussion
But
I
don’t
think
our
success
in
the
next
50
years
depends
on
answering
them
64
65. Looking
Forward
• My
crystal
ball
cannot
see
specific
technical
trends
50
years
out
• It
does
predict
that
the
three
drivers
– commercial
interest
– common
data
management
challenges
– attractive
problems
will
exist
in
for
another
50
years
65
66. So
what
do
we
need?
• We
will
be
OK
if
we:
– Periodically
reconnect
to
these
three
drivers
– Create
an
environment
that
attracts
good
people
and
gives
them
the
freedom
and
incentive
to
do
good
work
• Our
success
depends
on
both
of
these.
66
67. This
is
Important
• As
a
research
community,
despite
commercial
interest
and
great
problems
to
work
on,
we
will
not
thrive
if
we
create
a
stifling,
depressing
environment
that
discourages
a
diversity
of
work.
67
68. Who
is
Going
to
Fix
This?
• This
is
not
“us
vs.
them”
• There
is
only
us.
• Don’t
wait
for
“them”
to
change
things.
• We
are
“them.”
68
69. Are
Things
Really
So
Bad?
• Not
entirely,
not
yet.
– Somehow
good
work
still
gets
done.
– Somehow
great
papers
still
get
written.
– Somehow
great
new
people
still
join
the
community.
– The
community
is
beginning
to
respond
with
great
initiatives
at
various
conferences.
• But
the
overall
trend
is
not
good.
• If
we
don’t
address
this,
innovative
data
management
research
will
get
done,
but
probably
not
by
us.
69
70. The
Next
Big
Research
Idea
• Maybe
the
next
big
idea
is
not
a
new
data
model.
• Maybe
it
is
a
new
community
model.
– How
we
create,
disseminate,
and
evaluate
research.
– How
we
attract,
evaluate,
and
motivate
researchers.
• The
ideas
in
this
keynote
are
incremental.
• Can
some
brilliant
person
come
up
with
a
paradigm-‐changing
idea
for
the
community?
70
71. Acknowledgements
• I’d
like
to
thank
the
many
colleagues
near
and
far
whose
ideas
I
have
used
in
this
talk.
• I’d
like
to
apologize
to
the
many
colleagues
near
and
far
whose
ideas
I
should
have
used
in
this
talk
but
didn’t.
• I’d
like
to
thank
an
anonymous
colleague
for
heroic
work
making
these
slides
much
less
visually
boring
than
is
typical
for
a
Naughton
talk.
71
72. Closing
Thought:
We
Are
In
It
for
the
Long
Haul
1959 … 1980 … 2009 … 2040 … 2060
Past
Future
• The
McGee
paper
I
discussed
was
from
1959
• His
most
recent
publication
was
in
2009
• So
note
to
youngsters
first
publishing
in
this
conference:
you
should
still
be
publishing
in
2060!
So
it
is
REALLY
in
your
interest
to
decide
how
you
would
like
to
spend
the
next
50
years…
72