Presentation by Alain Tamayo during the Sensor Web Ontology and Semantics paper session of the Sensor Web Enablement workshop (held during the 2011 Cybera Summit).
Dynamo Systems - QCon SF 2012 PresentationShanley Kane
A look at Dynamo-based systems: the architectural principles, use cases and requirements; where they differ from relational databases; and where they are going.
Big Data projects overview at EMC Labs China
• Introduction to Cloud Databases
• Data analytics in the cloud
– Parallel DBMS
– MapReduce
• FlexDB - A cloud-scale database engine based on Hadoop
The document provides an overview and introduction to NoSQL databases. It discusses what triggered the NoSQL movement, common characteristics of NoSQL systems, and business benefits. The agenda covers topics such as what NoSQL is, differences from big data and cloud computing, core concepts, example implementations, and selecting the right NoSQL system for a project.
IBM Watson Jeopardy! white paper which explains Watson’s workload optimised system design based on IBM DeepQA architecture and POWER7® processor-based servers.
This document provides an overview of Watson, an IBM computer system designed to answer questions posed in natural language. It summarizes that Watson uses IBM's DeepQA architecture to analyze natural language questions and evidence from 200 million pages of text to generate hypotheses and answer questions. Watson competed successfully on the Jeopardy! quiz show in 2011, answering questions faster and as accurately as human experts. The document describes how Watson harnesses massive parallel processing across 2880 POWER7 cores in a cluster of 90 servers to perform the complex analytics required for natural language question answering at scale.
Cybera International Strategic Advisory Committee - 2011 Cybera AGM ReportCybera Inc.
Brian Unger, Chair of Cybera's International Strategic Advisory Committee (ISAC), presented this recap of the ISAC's 2011 conclusions and recommendations. The ISAC is comprised of leading technology research and industry representatives from around the world. For more information on this committee, please visit the Cybera website: http://www.cybera.ca/international-strategic-advisory-committee
Pervasive Cloud Computing in Alberta - Robin Winsor, CyberaCybera Inc.
Robin Winsor, President & CEO of Cybera, presented these slides as part of the Cybera Summit 2010 session "Pervasive Cloud Infrastructure: Opportunities in Alberta". For more information, please visit http://www.cybera.ca/pervasive-cloud-infrastructure-opportunities-alberta
Dynamo Systems - QCon SF 2012 PresentationShanley Kane
A look at Dynamo-based systems: the architectural principles, use cases and requirements; where they differ from relational databases; and where they are going.
Big Data projects overview at EMC Labs China
• Introduction to Cloud Databases
• Data analytics in the cloud
– Parallel DBMS
– MapReduce
• FlexDB - A cloud-scale database engine based on Hadoop
The document provides an overview and introduction to NoSQL databases. It discusses what triggered the NoSQL movement, common characteristics of NoSQL systems, and business benefits. The agenda covers topics such as what NoSQL is, differences from big data and cloud computing, core concepts, example implementations, and selecting the right NoSQL system for a project.
IBM Watson Jeopardy! white paper which explains Watson’s workload optimised system design based on IBM DeepQA architecture and POWER7® processor-based servers.
This document provides an overview of Watson, an IBM computer system designed to answer questions posed in natural language. It summarizes that Watson uses IBM's DeepQA architecture to analyze natural language questions and evidence from 200 million pages of text to generate hypotheses and answer questions. Watson competed successfully on the Jeopardy! quiz show in 2011, answering questions faster and as accurately as human experts. The document describes how Watson harnesses massive parallel processing across 2880 POWER7 cores in a cluster of 90 servers to perform the complex analytics required for natural language question answering at scale.
Cybera International Strategic Advisory Committee - 2011 Cybera AGM ReportCybera Inc.
Brian Unger, Chair of Cybera's International Strategic Advisory Committee (ISAC), presented this recap of the ISAC's 2011 conclusions and recommendations. The ISAC is comprised of leading technology research and industry representatives from around the world. For more information on this committee, please visit the Cybera website: http://www.cybera.ca/international-strategic-advisory-committee
Pervasive Cloud Computing in Alberta - Robin Winsor, CyberaCybera Inc.
Robin Winsor, President & CEO of Cybera, presented these slides as part of the Cybera Summit 2010 session "Pervasive Cloud Infrastructure: Opportunities in Alberta". For more information, please visit http://www.cybera.ca/pervasive-cloud-infrastructure-opportunities-alberta
Building Standards-Based Geoprocessing Mobile ClientsAlain Tamayo Fong
1) The document proposes a framework for building standards-based geospatial processing mobile clients.
2) The framework includes a network communication library optimized for mobile devices and a code generator that simplifies XML schemas and produces compact code.
3) It was tested on sample applications and allows mobile clients to execute Web Processing Service requests, though it currently only supports the GML encoding and synchronous requests.
Elastic Caching for a Smarter Planet - Make Every Transaction CountYakura Coffee
Social Media, mobile devices and new innovative infrastructures mean that more data is being used to serve end-users more than ever before. Enterprise customers must act quickly on data stored across their enterprise. IBM Elastic Caching solutions provide the best opportunity for improving your end-users experience in consuming application data. Every business, of every size, in every Industry needs an effective data caching solution. The industry has moved beyond the bottleneck of CPU processing and must address the growing data bottleneck problems which prevent predictable and cost-effective scalability that directly impacts the performance and throughput of every data-intensive application.
IBM Elastic Caching solutions WebSphere eXtreme Scale and the DataPower XC10 Appliance solve these problems better than the competition. Learn how IBM Elastic Caching solutions have evolved to eliminate enterprise data bottlenecks by elastically distributing data among many resources and allowing applications to efficiently access needed data quickly. We beat our competition by not only allowing our customers flexibility to create mission-critical applications that achieve predictable, scalable performance and high availability, but also extending and integrating IBM Elastic Caching into many IBM products covering Retail/Commerce solutions, Mobile Devices, Content Management, Business Rule Management, ESBs, Messaging and more.
With the exploding popularity of mobile devices, mobile application performance has become increasingly critical to the modern Enterprise.
This session will discuss some of the performance pitfalls common to tablets, iPhones and Android devices, and outline the tools available to allow you to effectively test your company’s mobile-based applications.
This presentation was originally given at SoftEd Fusion 2012 (Sydney) on September 13th.
This document presents a case study comparing a traditional single-node approach and a cloud-based approach for analyzing a large dataset of over 150 million domain names to determine which are hosted by SoftLayer. The single-node approach ran on a single server and took approximately 300 hours to complete at a cost of $102.67. A cloud-based approach using multiple servers in parallel could complete the task much faster and potentially at a lower overall cost by leveraging elastic computing resources in the cloud.
The document discusses several topics related to mobile systems engineering including:
1. Data storage options for Android applications including SharedPreferences, internal storage, external storage, SQLite databases, and network connections.
2. The concept of mobile cloud computing including definitions, architectures, advantages and issues.
3. Context-aware computing including definitions, basic functions, and a layered framework.
4. The Internet of Things including definitions, characteristics, enabling technologies, and applications across various domains.
Generated REST Gateways for Mobile ApplicationsWolfgang Frank
The document discusses generating REST gateways for mobile applications. It introduces arconsis IT-Solutions GmbH, who develops agile and lean software using JBoss middleware and focuses on mobile solutions. The presentation aims to show how a domain-specific language approach can simplify creating RESTful mobile apps that integrate with enterprise systems in a simple, fast, and multi-platform way. It demonstrates using a DSL to generate a REST gateway on JBoss AS along with mobile app code and proxies to connect an example mobile app to a backend system.
Kumar Ramaswamy provides services related to developing highly scalable and secure distributed systems using technologies like PostgreSQL, HDFS, Spark and Kafka. He has extensive experience architecting fault tolerant systems and has developed distributed systems for tasks like product tracking and advertisement data processing. His background includes work with technologies such as Unix, Java, distributed databases and big data platforms.
DDS-to-JSON and DDS Real-time Data Storage with MongoDBAbdullah Ozturk
The document discusses using MongoDB to store time-series sensor data transmitted using the Data Distribution Service (DDS) standard. DDS is used to acquire real-time data from sensors and devices, which is then converted to JSON format and stored as documents in MongoDB collections. MongoDB is suitable for this application because it can manage flexible data structures and scale to large volumes of sensor data. The system provides benefits like replay capability, querying, analysis and integration testing using the recorded sensor information.
The document discusses skeuomorphs and metaphors in architecture and databases. It explores how mobile applications can architect for performance when the internet functions like a database. It recommends making applications smarter through profiling, threading, and caching, using networks intelligently through bundling and pipelining requests, and optimizing "databases" through stored procedures, queueing, denormalization, and managing result sets. The document considers whether viewing the internet as a database is a skeuomorph or metaphor, and discusses lessons from the past that can help optimize current mobile and cloud architectures.
UnConference for Georgia Southern Computer Science March 31, 2015Christopher Curtin
I presented to the Georgia Southern Computer Science ACM group. Rather than one topic for 90 minutes, I decided to do an UnConference. I presented them a list of 8-9 topics, let them vote on what to talk about, then repeated.
Each presentation was ~8 minutes, (Except Career) and was by no means an attempt to explain the full concept or technology. Only to wake up their interest.
Skeuomorphs, Databases, and Mobile PerformanceSam Ramji
The document discusses skeuomorphs and metaphors in architecture and databases. It explores how mobile applications can architect for performance by making the application smarter through profiling, threading, and caching, using the network intelligently through bundling and pipelining requests, and optimizing databases through stored procedures, queueing, denormalization, and managing result sets. The document considers whether describing the internet as a database is a skeuomorph or metaphor, and discusses lessons learned from prior database architectures that can help improve mobile performance.
Manik Surtani introduces Infinispan, a new open source data grid that is well-suited as a cloud data store. Data grids provide highly scalable, fault-tolerant distributed caching capabilities. Infinispan improves upon existing data grids with features like consistent hashing for efficient data distribution, a JPA-like API, and client/server capabilities that make it cloud-ready. Infinispan aims to address the challenges of using traditional databases in cloud environments by providing elastic, low-latency access to large amounts of data without bottlenecks.
The Google File System is a scalable distributed file system designed to meet the rapidly growing data storage needs of Google. It provides fault tolerance on inexpensive commodity hardware and high aggregate performance to large numbers of clients. Key aspects of its design include handling frequent component failures as the norm, managing huge files up to multiple gigabytes in size containing many objects, optimizing for file appending and sequential reads of appended data, and co-designing the file system interface to increase flexibility for applications. The largest deployment to date includes over 1,000 storage nodes providing hundreds of terabytes of storage.
The Google File System is a scalable distributed file system designed to meet the rapidly growing data storage needs of Google. It provides fault tolerance on inexpensive commodity hardware and high aggregate performance to large numbers of clients. Key aspects of its design include handling frequent component failures as the norm, managing huge files up to multiple gigabytes in size containing many objects, optimizing for file appending and sequential reads of appended data, and co-designing the file system interface to increase flexibility for applications. The largest deployment to date includes over 1,000 storage nodes providing hundreds of terabytes of storage.
If you're like most of the world, you're on an aggressive race to implement machine learning applications and on a path to get to deep learning. If you can give better service at a lower cost, you will be the winners in 2030. But infrastructure is a key challenge to getting there. What does the technology infrastructure look like over the next decade as you move from Petabytes to Exabytes? How are you budgeting for more colossal data growth over the next decade? How do your data scientists share data today and will it scale for 5-10 years? Do you have the appropriate security, governance, back-up and archiving processes in place? This session will address these issues and discuss strategies for customers as they ramp up their AI journey with a long term view.
This document discusses common use cases for MongoDB and why it is well-suited for them. It describes how MongoDB can handle high volumes of data feeds, operational intelligence and analytics, product data management, user data management, and content management. Its flexible data model, high performance, scalability through sharding and replication, and support for dynamic schemas make it a good fit for applications that need to store large amounts of data, handle high throughput of reads and writes, and have low latency requirements.
Java is an object-oriented programming language designed for use on the Internet that was introduced by Sun Microsystems in 1995. Microsoft's .NET is a set of web services frameworks and technologies based on XML standards. Oracle is the world's largest database and application software vendor founded in 1977 that offers the Oracle database and development tools. A data warehouse is a large store of data for analysis that organizations use to detect patterns and trends by extracting, transforming, and loading data from transaction systems.
This document provides an overview of Google's Megastore database system. It discusses three key aspects: the data model and schema language for structuring data, transactions for maintaining consistency, and replication across datacenters for high availability. The data model takes a relational approach and uses the concept of entity groups to partition data at a fine-grained level for scalability. Transactions provide ACID semantics within entity groups. Replication uses Paxos consensus for strong consistency across datacenters.
Cyber Summit 2016: Technology, Education, and DemocracyCybera Inc.
What are the opportunities and the challenges offered by emerging modes of technologically-inflected communication and decision-making? What is our role and responsibility as educators and as developers of research and teaching digital infrastructures? What do students need in the 21st century? As education institutions and providers struggle to respond to the first two questions, are we abrogating our responsibility to the last?
In this talk, Matt Ratto will describe some of the opportunities and the challenges we currently face, laying out a model of action for how to potentially address the questions raised above. Core to his thinking are two related points; first that we must help students develop a greater sense of how the informational world and its attendant infrastructures helps shape how and what we think, and second, that a good way to do this is to give students the space to engage in reflexive acts of technological production – what Matt has termed ‘critical making.’ He will provide concrete examples from both his research and his teaching that demonstrate the value and importance of reflexive, hands-on work with digital technologies in helping students develop the critical digital literacy skills they need to function in today’s society.
Matt Ratto is an Associate Professor in the Faculty of Information at the University of Toronto and directs the Semaphore Research cluster on Inclusive Design, Mobile and Pervasive Computing and, as part of Semaphore, the Critical Making lab.
Cyber Summit 2016: Understanding Users' (In)Secure BehaviourCybera Inc.
1) The document summarizes a user study on phishing detection that found users still struggle to accurately identify phishing sites, being successful only 53% of the time on phishing sites and 78% on legitimate sites.
2) The study also found that users have only a shallow understanding of security indicators and place more attention on page content than security cues. Nearly half did not recognize a phishing version of their own bank site.
3) The presentation argues that common password policies may do more harm than good by placing unreasonable demands on human memory and behavior. It suggests rethinking such policies and advice to consider human capabilities and provide more practical and beneficial guidance.
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Building Standards-Based Geoprocessing Mobile ClientsAlain Tamayo Fong
1) The document proposes a framework for building standards-based geospatial processing mobile clients.
2) The framework includes a network communication library optimized for mobile devices and a code generator that simplifies XML schemas and produces compact code.
3) It was tested on sample applications and allows mobile clients to execute Web Processing Service requests, though it currently only supports the GML encoding and synchronous requests.
Elastic Caching for a Smarter Planet - Make Every Transaction CountYakura Coffee
Social Media, mobile devices and new innovative infrastructures mean that more data is being used to serve end-users more than ever before. Enterprise customers must act quickly on data stored across their enterprise. IBM Elastic Caching solutions provide the best opportunity for improving your end-users experience in consuming application data. Every business, of every size, in every Industry needs an effective data caching solution. The industry has moved beyond the bottleneck of CPU processing and must address the growing data bottleneck problems which prevent predictable and cost-effective scalability that directly impacts the performance and throughput of every data-intensive application.
IBM Elastic Caching solutions WebSphere eXtreme Scale and the DataPower XC10 Appliance solve these problems better than the competition. Learn how IBM Elastic Caching solutions have evolved to eliminate enterprise data bottlenecks by elastically distributing data among many resources and allowing applications to efficiently access needed data quickly. We beat our competition by not only allowing our customers flexibility to create mission-critical applications that achieve predictable, scalable performance and high availability, but also extending and integrating IBM Elastic Caching into many IBM products covering Retail/Commerce solutions, Mobile Devices, Content Management, Business Rule Management, ESBs, Messaging and more.
With the exploding popularity of mobile devices, mobile application performance has become increasingly critical to the modern Enterprise.
This session will discuss some of the performance pitfalls common to tablets, iPhones and Android devices, and outline the tools available to allow you to effectively test your company’s mobile-based applications.
This presentation was originally given at SoftEd Fusion 2012 (Sydney) on September 13th.
This document presents a case study comparing a traditional single-node approach and a cloud-based approach for analyzing a large dataset of over 150 million domain names to determine which are hosted by SoftLayer. The single-node approach ran on a single server and took approximately 300 hours to complete at a cost of $102.67. A cloud-based approach using multiple servers in parallel could complete the task much faster and potentially at a lower overall cost by leveraging elastic computing resources in the cloud.
The document discusses several topics related to mobile systems engineering including:
1. Data storage options for Android applications including SharedPreferences, internal storage, external storage, SQLite databases, and network connections.
2. The concept of mobile cloud computing including definitions, architectures, advantages and issues.
3. Context-aware computing including definitions, basic functions, and a layered framework.
4. The Internet of Things including definitions, characteristics, enabling technologies, and applications across various domains.
Generated REST Gateways for Mobile ApplicationsWolfgang Frank
The document discusses generating REST gateways for mobile applications. It introduces arconsis IT-Solutions GmbH, who develops agile and lean software using JBoss middleware and focuses on mobile solutions. The presentation aims to show how a domain-specific language approach can simplify creating RESTful mobile apps that integrate with enterprise systems in a simple, fast, and multi-platform way. It demonstrates using a DSL to generate a REST gateway on JBoss AS along with mobile app code and proxies to connect an example mobile app to a backend system.
Kumar Ramaswamy provides services related to developing highly scalable and secure distributed systems using technologies like PostgreSQL, HDFS, Spark and Kafka. He has extensive experience architecting fault tolerant systems and has developed distributed systems for tasks like product tracking and advertisement data processing. His background includes work with technologies such as Unix, Java, distributed databases and big data platforms.
DDS-to-JSON and DDS Real-time Data Storage with MongoDBAbdullah Ozturk
The document discusses using MongoDB to store time-series sensor data transmitted using the Data Distribution Service (DDS) standard. DDS is used to acquire real-time data from sensors and devices, which is then converted to JSON format and stored as documents in MongoDB collections. MongoDB is suitable for this application because it can manage flexible data structures and scale to large volumes of sensor data. The system provides benefits like replay capability, querying, analysis and integration testing using the recorded sensor information.
The document discusses skeuomorphs and metaphors in architecture and databases. It explores how mobile applications can architect for performance when the internet functions like a database. It recommends making applications smarter through profiling, threading, and caching, using networks intelligently through bundling and pipelining requests, and optimizing "databases" through stored procedures, queueing, denormalization, and managing result sets. The document considers whether viewing the internet as a database is a skeuomorph or metaphor, and discusses lessons from the past that can help optimize current mobile and cloud architectures.
UnConference for Georgia Southern Computer Science March 31, 2015Christopher Curtin
I presented to the Georgia Southern Computer Science ACM group. Rather than one topic for 90 minutes, I decided to do an UnConference. I presented them a list of 8-9 topics, let them vote on what to talk about, then repeated.
Each presentation was ~8 minutes, (Except Career) and was by no means an attempt to explain the full concept or technology. Only to wake up their interest.
Skeuomorphs, Databases, and Mobile PerformanceSam Ramji
The document discusses skeuomorphs and metaphors in architecture and databases. It explores how mobile applications can architect for performance by making the application smarter through profiling, threading, and caching, using the network intelligently through bundling and pipelining requests, and optimizing databases through stored procedures, queueing, denormalization, and managing result sets. The document considers whether describing the internet as a database is a skeuomorph or metaphor, and discusses lessons learned from prior database architectures that can help improve mobile performance.
Manik Surtani introduces Infinispan, a new open source data grid that is well-suited as a cloud data store. Data grids provide highly scalable, fault-tolerant distributed caching capabilities. Infinispan improves upon existing data grids with features like consistent hashing for efficient data distribution, a JPA-like API, and client/server capabilities that make it cloud-ready. Infinispan aims to address the challenges of using traditional databases in cloud environments by providing elastic, low-latency access to large amounts of data without bottlenecks.
The Google File System is a scalable distributed file system designed to meet the rapidly growing data storage needs of Google. It provides fault tolerance on inexpensive commodity hardware and high aggregate performance to large numbers of clients. Key aspects of its design include handling frequent component failures as the norm, managing huge files up to multiple gigabytes in size containing many objects, optimizing for file appending and sequential reads of appended data, and co-designing the file system interface to increase flexibility for applications. The largest deployment to date includes over 1,000 storage nodes providing hundreds of terabytes of storage.
The Google File System is a scalable distributed file system designed to meet the rapidly growing data storage needs of Google. It provides fault tolerance on inexpensive commodity hardware and high aggregate performance to large numbers of clients. Key aspects of its design include handling frequent component failures as the norm, managing huge files up to multiple gigabytes in size containing many objects, optimizing for file appending and sequential reads of appended data, and co-designing the file system interface to increase flexibility for applications. The largest deployment to date includes over 1,000 storage nodes providing hundreds of terabytes of storage.
If you're like most of the world, you're on an aggressive race to implement machine learning applications and on a path to get to deep learning. If you can give better service at a lower cost, you will be the winners in 2030. But infrastructure is a key challenge to getting there. What does the technology infrastructure look like over the next decade as you move from Petabytes to Exabytes? How are you budgeting for more colossal data growth over the next decade? How do your data scientists share data today and will it scale for 5-10 years? Do you have the appropriate security, governance, back-up and archiving processes in place? This session will address these issues and discuss strategies for customers as they ramp up their AI journey with a long term view.
This document discusses common use cases for MongoDB and why it is well-suited for them. It describes how MongoDB can handle high volumes of data feeds, operational intelligence and analytics, product data management, user data management, and content management. Its flexible data model, high performance, scalability through sharding and replication, and support for dynamic schemas make it a good fit for applications that need to store large amounts of data, handle high throughput of reads and writes, and have low latency requirements.
Java is an object-oriented programming language designed for use on the Internet that was introduced by Sun Microsystems in 1995. Microsoft's .NET is a set of web services frameworks and technologies based on XML standards. Oracle is the world's largest database and application software vendor founded in 1977 that offers the Oracle database and development tools. A data warehouse is a large store of data for analysis that organizations use to detect patterns and trends by extracting, transforming, and loading data from transaction systems.
This document provides an overview of Google's Megastore database system. It discusses three key aspects: the data model and schema language for structuring data, transactions for maintaining consistency, and replication across datacenters for high availability. The data model takes a relational approach and uses the concept of entity groups to partition data at a fine-grained level for scalability. Transactions provide ACID semantics within entity groups. Replication uses Paxos consensus for strong consistency across datacenters.
Cyber Summit 2016: Technology, Education, and DemocracyCybera Inc.
What are the opportunities and the challenges offered by emerging modes of technologically-inflected communication and decision-making? What is our role and responsibility as educators and as developers of research and teaching digital infrastructures? What do students need in the 21st century? As education institutions and providers struggle to respond to the first two questions, are we abrogating our responsibility to the last?
In this talk, Matt Ratto will describe some of the opportunities and the challenges we currently face, laying out a model of action for how to potentially address the questions raised above. Core to his thinking are two related points; first that we must help students develop a greater sense of how the informational world and its attendant infrastructures helps shape how and what we think, and second, that a good way to do this is to give students the space to engage in reflexive acts of technological production – what Matt has termed ‘critical making.’ He will provide concrete examples from both his research and his teaching that demonstrate the value and importance of reflexive, hands-on work with digital technologies in helping students develop the critical digital literacy skills they need to function in today’s society.
Matt Ratto is an Associate Professor in the Faculty of Information at the University of Toronto and directs the Semaphore Research cluster on Inclusive Design, Mobile and Pervasive Computing and, as part of Semaphore, the Critical Making lab.
Cyber Summit 2016: Understanding Users' (In)Secure BehaviourCybera Inc.
1) The document summarizes a user study on phishing detection that found users still struggle to accurately identify phishing sites, being successful only 53% of the time on phishing sites and 78% on legitimate sites.
2) The study also found that users have only a shallow understanding of security indicators and place more attention on page content than security cues. Nearly half did not recognize a phishing version of their own bank site.
3) The presentation argues that common password policies may do more harm than good by placing unreasonable demands on human memory and behavior. It suggests rethinking such policies and advice to consider human capabilities and provide more practical and beneficial guidance.
Cyber Summit 2016: Insider Threat Indicators: Human BehaviourCybera Inc.
Serious threats to private and governmental organizations do not only come from the outside world, but also come from within. Some employees and contractors with legitimate access to buildings, networks, assets and information deliberately misuse their priviledged access to cause harm to their organization. What are the reasons behind their actions? Is it debts, greed, ideology, disgruntlement, or divided loyalty?
Regardless of their motivations or vulnerabilities, traitors have very similar types of personality and display a certain pattern of behaviours before committing an insider incident. As a prevention measure, it is vital that organizations and employees understand, recognize and detect the common indicators of insider threat. Would you recognize the signs?
Mario Vachon is an Insider Threat Security Specialist with the RCMP Departmental Security Branch.
Cyber Summit 2016: Research Data and the Canadian Innovation ChallengeCybera Inc.
Canada allocates a substantial amount of public funding to research, which is a critical factor in ensuring we remain innovative and competitive. Increasingly this funding is geared to the support and development of digital research infrastructure (DRI), including the underlying networks and the associated data acquisition, storage, analysis and visualization. In order to maximize the benefits of increasingly complex DRI and the research it facilitates, it is important to make sure data is properly stewarded, accessible and reusable. By adopting appropriate approaches to research data management we are better positioned to respond to challenges, such as effectively measuring research impacts, and ensuring the reproducibility, privacy, and security of research outputs.
Research Data Canada (RDC) is a member-driven organization committed to developing a sustainable approach to research data management, one based on interoperability and best practices. This session will provide an update on the efforts of RDC and partner organizations, including: CANARIE, Compute Canada, CARL Portage Network, CASRAI, the TriAgencies, and the Leadership Council for Digital Infrastructure. Intersections with international activities and projects will also be highlighted. These efforts are ultimately designed to faciliate a cohesive national approach to research data management, and one based on a clearly articulated vision for supporting innovation and discovery in Canada.
Mark Leggott is the Executive Director of Research Data Canada.
Cyber Summit 2016: Knowing More and Understanding Less in the Age of Big DataCybera Inc.
The Internet has revolutionized how — and how much — each of us can know. Our digital tools put the knowledge of the world at our fingertips — and soon, maybe, right into our heads. But what kinds of of knowledge do our devices give us, and how are they reshaping and challenging the role that education and libraries should play in our lives?
This talk was delivered by Michael Patrick Lynch, professor of philosophy at the University of Connecticut, where he directs the university’s Humanities Institute.
Cyber Summit 2016: Privacy Issues in Big Data Sharing and ReuseCybera Inc.
This document summarizes a presentation on big data and data reuse given by Bart Custers. It discusses:
1) The Eudeco project which examines big data and data reuse from legal, societal, economic, and technological perspectives across multiple European countries.
2) Issues with data sharing and reuse, including potential privacy violations, discrimination, lack of transparency, and unintended consequences from new uses of data or placing it in new contexts.
3) Potential solutions discussed, including privacy impact assessments, privacy by design, and new approaches focusing more on transparency and responsibility than restricting data access and use.
Cyber Summit 2016: Establishing an Ethics Framework for Predictive Analytics ...Cybera Inc.
This document summarizes a presentation about establishing an ethics framework for predictive analytics using student data in higher education. It discusses how technology has enabled more data collection and predictive modeling of student behavior. However, few guidelines exist for these practices. The presentation advocates developing an ethics framework that safeguards student privacy, promotes transparency, considers unintended consequences, and involves consultation. It also examines existing principles and discusses challenges like opaque predictive models that work against students' interests. The presenter argues universities should internalize norms of respecting trust and serving students, not just avoiding legal issues.
Cyber Summit 2016: The Data Tsunami vs The Network: How More Data Changes Eve...Cybera Inc.
Canada’s National Research and Education Network, like other ultra-speed research networks, has evolved to transfer massive amounts of data at 100Gbps and beyond. But with the volume of data traffic growing at more than 50% per year, the ability to move increasing volumes of data is challenging. What are the kinds of applications in research and education that are driving this growth? What are the implications of the coming data tsunami on our communication networks? And what happens to network economics to keep up with the demand? CANARIE’s Chief Technology Officer, Mark Wolff, explores these topics and offer insights into how the NREN will evolve to continue to meet the unique needs of Canada’s research and education community.
Cyber Summit 2016: Issues and Challenges Facing Municipalities In Securing DataCybera Inc.
The City of Calgary is responsible for providing municipal services to 1.1 million people and 16,000 employees with more than 700 sites and critical infrastructure units. The municipal services represent a $60B asset base including water and wastewater treatment plants, light rapid transit, emergency services, roads and recreation facilities, and has revenue and procurement streams of $4.0B annually. During his tenure, Owen Key, Chief Security Officer and the Chief Information Officer for the City, has implemented enterprise systems for CCTV, access and ID control, physical security information management systems, and has responsibility for information security.
Cyber Summit 2016: Using Law Responsibly: What Happens When Law Meets Technol...Cybera Inc.
This document summarizes issues at the intersection of law and technology in Canada over the next five years. It discusses debates around lawful access to data, encryption, data retention, and network interception capabilities. Other issues addressed include internet taxes, linking and payments between platforms, VPN use, global orders for content removal, localization requirements, and website blocking. The document argues that as these issues are addressed through law and policy, responsibilities must be met to use law responsibly and consider matters like privacy, oversight, safeguards, and technological implications.
This document summarizes a presentation given by Brian Hamilton on privacy, security, and access to data. It discusses the role of the Office of the Information and Privacy Commissioner of Alberta in overseeing privacy laws and reviewing research proposals. It outlines how the office analyzes information sharing and big data initiatives to ensure privacy is protected. Tips are provided for developing privacy controls and gaining approval, including conducting a privacy impact assessment and developing expertise in privacy principles.
Historically, the University of Alberta lacked a centrally managed repository for reporting data, resulting in inconsistency and disparity in access for units across campus. Meaningful and actionable reports were limited, and only focused on the interests and goals of the few units with data analysts who could synthesize the information.
Over the last couple of years, the University of Alberta has undertaken major changes in how information is managed and utilized. At the forefront of this change has been an increased interest in supporting the development of analytics and supporting tools. Beginning with the implementation of a centrally managed data warehouse with self-service capabilities, and the introduction of cloud services with business process analysis tools, the University is just starting down the road of big data.
This presentation explores opportunities and challenges for the University of Alberta in utilizing big data.
Predicting the Future With Microsoft BingCybera Inc.
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11. What is a Jupyter Notebook?
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12. Jupyter Notebooks with Code Examples
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Analysing Performance of XML Data Binding Solutions for SOS Applications
1. Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
Alain
Tamayo,
Carlos
Granell,
Joaquín
Huerta
Geospatial
Technologies
Research
Group,
Universitat
Jaume
I,
Spain
SWE
2011,
Oct
6-‐7,
Banff,
Alberta,
Canada
2. 1
.
Motivation
SOS-‐based
applications
are
commonplace
in
server,
web
and
desktop
environments.
It’s
just
a
matter
of
time
they
become
commonplace
in
mobile
devices
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
2
3. 2
.
Motivation
SOS
protocols
are
based
in
large
schemas
that
describes
the
structure
of
exchanged
messages
in
XML
format
(+700
types,
+80
schema
files)
• Low-‐Level
APIs:
• Tree
APIs:
DOM
• Streaming
APIs:
SAX,
StaX,
…
• XML
Data
Binding:
XMLBeans,
JAXB,
XBinder,
…
Using
low-‐level
APIs
in
the
presence
of
large
schemas
is
time-‐consuming
and
error-‐prone.
Using
XML
data
binding
is
advised,
but
frequently
generated
code
needs
more
computational
resources.
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
3
4. 3
.
Objectives
• To
analyse
to
what
extent
the
use
of
XML
data
binding
solutions
is
a
problem
in
SOS
applications
running
in
different
platforms
(Windows
7
and
Android):
• Execution
speed
(without
including
storage
or
network
transfer
times).
• Memory
consumption
• Size
of
generated
code
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
4
5. 4
.
Experimental
Setup
• 4
datasets
of
real
SOS
data:
• CAPS
(capabilities
files)
• SD
(Sensor
description
files)
• OBS
(Observation
files)
• MEA
(Measurement
files)
• 4
XML
data
binding
tools:
• XMLBeans
(PC)
• JAXB
(PC)
• XBinder
(PC
and
Mobile)
• DBMG
(PC
and
Mobile)
• 2
Hardware
platforms:
• HTC
Desire
Android
Phone
(1
GHz
CPU,
576
RAM)
• Windows
7
PC
(Intel
Quad
Core
i7
2.8
GHz
CPU,
8GB
RAM)
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
5
6. 5
–
Execution
Speed
(CAPS
Dataset)
Mobile
Scenario
PC
Scenario
The
execution
times
for
the
mobile
phone
were
about
60
times
slower
than
for
the
personal
computer.
XML
processing
code
does
not
seem
to
be
a
bottleneck
for
PCs.
High
processing
times
for
mobiles
raises
the
question
if
the
current
SOS
protocol
is
appropriate
for
being
implemented
in
these
devices.
XML
is
a
verbose
format.
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
6
7. 6
–
Execution
Speed
(SD
Dataset)
• SD
dataset:
• SensorML
files
used
to
be
small
(<20KB).
As
a
consequence,
the
execution
times
were
not
high.
• OBS
and
MEA
datasets:
• Observation
files
contains
about
7
times
more
observation
values
than
measurement
files
of
the
same
size.
As
a
consequence,
we
recommend
to
use
the
former
in
mobile
device
SOS
clients.
• Observation
files
represent
observation
values
inside
a
xsd:anyType
element
that
is
not
mapped
successfully
by
some
XML
data
binding
tools.
Additionally,
as
the
“block”
of
observation
values
is
represented
as
a
String
the
application
code
must
parse
this
information
again.
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
7
8. 7
–
Execution
Speed
(Parsers
–
CAPS
Dataset)
PC
Scenario
Small
files
(<100KB)
Large
files
(>100KB)
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
8
9. 8
–
Execution
Speed
(Parsers
–
CAPS
Dataset)
Mobile
Scenario
Writing
XML
processing
code
using
a
manual
approach
do
not
necessarily
produce
a
code
that
is
much
faster
than
code
generated
by
some
tools.
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
9
10. 9
–
Memory
Consumption
(CAPS
dataset)
Small
files
(<100KB)
Large
files
(>100KB)
JAXB
and
XMLBeans
show
higher
memory
consumption,
but
it
does
not
seem
to
represent
a
problem
for
a
desktop
or
server
application.
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
10
11. 10
–
Size
of
Generated
Code
Code
generated
based
on
large
schemas
usually
has
a
large
size.
Customised
code
fits
better
the
limitations
of
mobile
devices.
Customised
code
does
not
necessarily
has
to
be
written
manually.
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
11
12. 11
-‐
Conclusions
We
have
presented
a
study
to
measure
the
influence
of
XML
processing
code
in
the
performance
of
desktop
and
mobile
SOS
applications.
The
results
have
shown
that
XML
processing
does
not
seem
to
be
a
bottleneck
in
PC
applications.
On
the
other
hand,
the
opposite
happens
in
mobile
devices
where
the
time
needed
to
process
large
XML
files
is
very
high
due
to
their
associated
resource
constraints.
Analysing
Performance
of
XML
Data
Binding
Solutions
for
SOS
Applications
12