Yahoo’s data ETL pipeline continuously processes more than tens of terabytes of data every day. Seeking for a good data storage methodology that can store and fetch this data efficiently has always been a challenge for the Yahoo data ETL pipeline. A study done recently inside Yahoo has shown a dramatic data size reduction by switching from Sequence to RC File Format. We have decided to take the approach of converting our data to the RC File Format. The most challenging task is to manually serialize the data objects. We rely on Jute, a Hadoop Record Compiler, to provide serialization code. However, Jute does not support RC File Format. In addition, RC file format does not support native Hadoop writable objects. Therefore writing serialization code becomes complicated and repetitive. Hence, we invented the JuteRC compiler which is an extension to the Hadoop Record Compiler (Jute). It generates serialization/deserialization code for any user defined primitive or composite data types. MapReduce programmer can directly plug in the serialization/deserialization code to generate MapReduce output data file that is in RC File Storage Format. With the help of JuteRC compiler, our experiment against Yahoo audience data showed a 26-28% file size reduction and 40% read/write performance improvement compared to Sequence File. We are currently in the process to open source JuteRC.
Teams working on most projects fall into a broad category of either being a Pizza Team or a Jig-saw Puzzle team. A couple of slides explaining the characteristics of these teams and what it is like to be a part of one of these teams
Mes premiers PERSONAS - Culture ProduitOeil de Coach
Qu'est-ce que les personas ? A quoi servent-ils ? Comment les identifie-t-on ? Sur quels critères les crée-t-on ?
Retrouvez tous ces réponses dans cette présentation PPT sur les personas
Yahoo’s data ETL pipeline continuously processes more than tens of terabytes of data every day. Seeking for a good data storage methodology that can store and fetch this data efficiently has always been a challenge for the Yahoo data ETL pipeline. A study done recently inside Yahoo has shown a dramatic data size reduction by switching from Sequence to RC File Format. We have decided to take the approach of converting our data to the RC File Format. The most challenging task is to manually serialize the data objects. We rely on Jute, a Hadoop Record Compiler, to provide serialization code. However, Jute does not support RC File Format. In addition, RC file format does not support native Hadoop writable objects. Therefore writing serialization code becomes complicated and repetitive. Hence, we invented the JuteRC compiler which is an extension to the Hadoop Record Compiler (Jute). It generates serialization/deserialization code for any user defined primitive or composite data types. MapReduce programmer can directly plug in the serialization/deserialization code to generate MapReduce output data file that is in RC File Storage Format. With the help of JuteRC compiler, our experiment against Yahoo audience data showed a 26-28% file size reduction and 40% read/write performance improvement compared to Sequence File. We are currently in the process to open source JuteRC.
Teams working on most projects fall into a broad category of either being a Pizza Team or a Jig-saw Puzzle team. A couple of slides explaining the characteristics of these teams and what it is like to be a part of one of these teams
Mes premiers PERSONAS - Culture ProduitOeil de Coach
Qu'est-ce que les personas ? A quoi servent-ils ? Comment les identifie-t-on ? Sur quels critères les crée-t-on ?
Retrouvez tous ces réponses dans cette présentation PPT sur les personas
Open Annotation Rollout, Manchester, 2013-06-25
See also PPTX version with Notes: http://www.slideshare.net/soilandreyes/2013-0624annotatingr-osopenannotationmeeting
Open Annotation Rollout, Manchester, 2013-06-25
See also PDF version: http://www.slideshare.net/soilandreyes/2013-0624annotatingr-osopenannotationmeeting-23289491
2013-07-19 myExperiment research objects, beyond workflows and packs (PPTX)Stian Soiland-Reyes
Presentation at BOSC 2013 / ISMB 2013. (PowerPoint 2013 source)
PDF: https://www.slideshare.net/soilandreyes/2013-0719bosc-2013myexperimentresearchobjectsslides
See also poster at http://www.slideshare.net/soilandreyes/2013-0718bosc-2013myexperimentresearchobjectsposter-24242509 or
submitted abstract: https://docs.google.com/document/d/1jaAuPV-EnbsyI14L56HKHBQP7eDVfeXGLlK-LwohnWw/edit?usp=sharing
We have evolved Research Objects as a mechanism to preserve digital resources related to research, by providing mechanisms, formats and architecture for describing aggregated resources (hypothesis, workflow, datasets, scripts, services), their relations (is input for, explains, used by), provenance (graph was derived from dataset A, B and C) and attribution (who contributed what, and when?).
The website myExperiment is already popular for collaborating on, publishing and sharing scientific workflows, however we have found that for understanding and preserving a workflow over time, its definition is not enough, specially faced with workflow decay, services and tools that change over time. We have therefore adapted the research object model as a foundation for the myExperiment packs, allowing uploading of workflow runs, inputs, outputs and other files relevant to the workflow, relating them with annotations and integrated the Wf4Ever architecture for performing decay analysis and tracking a research object’s evolution as it and its constituent resources change over time.
“Publishing and Consuming Linked Data. (Lessons learnt when using LOD in an a...Marta Villegas
Talk given at the "1st Summer Datathon on Linguistic Linked Open Data (SD-LLOD-15)"
In this talk we will describe our experience when publishing and, more crucially, consuming Linked Data at the Spanish CLARIN Knowledge Centre (http://lod.iula.upf.edu). The center includes a Catalog of NLP resources & tools which aims to promote the use of language technology to researches of Humanities and Social Sciences. Though the original data set followed the XML/XSD schema, this was rewritten in accordance to the LOD approach in order to maximize the information contained in our repositories and to be able to enrich the data there.
We will addresses some critical aspects when RDFying XSD/XML data focusing on the strategy followed when mapping controlled vocabularies expressed in XML enumerations; when dealing with certain unstructured data (those where input strings may generate relevant instances); and when addressing identity resolution and linking tasks once the eventual instances are RDFied. Here we will also report on data cleansing, a crucial and unavoidable task which we addressed as an incremental process where SPARQL played an important role. We will see that some of the decisions taken depend on the eventual application we have in mind. The requirements of our Catalog (implemented as a web browser) include: displaying data to the user in a comprehensive way; aggregating external data in a sensitive manner and making hidden implicit relations explicit. In addition, the system needs to provide fresh data (regularly updated) in a quick response time.
Finally, we will report on our experiences when addressing data integration and enrichment (via data mashup). We experimented with different strategies (e.g. using external URIS vs caching local data) and faced different problems (time latency, dereferencing external URIS) that may be useful to share.
Talk about Exploring the Semantic Web, and particularly Linked Data, and the Rhizomer approach. Presented August 14th 2012 at the SRI AIC Seminar Series, Menlo Park, CA
Metadata Provenance Tutorial at SWIB 13, Part 1Kai Eckert
The slides of part one of the Metadata Provenance Tutorial (Linked Data Provenance). Part 2 is here: http://de.slideshare.net/MagnusPfeffer/metadata-provenance-tutorial-part-2-modelling-provenance-in-rdf
BDW Chicago 2016 - Jim Scott, Director, Enterprise Strategy & Architecture - ...Big Data Week
For the past 25 years applications have been getting built using an RDBMS with a predefined schema which forces data to conform with a schema on-write. Many people still think that they must use an RDBMS for applications even though records in their datasets have no relation to one another. Additionally, those databases are optimized for transactional use, and data must be exported for analytics purposes. NoSQL technologies have turned that model on its side to deliver groundbreaking performance improvements.
I will walk through a music database with over 100 tables in the schema and show how to convert that model over for use with a NoSQL database. I will show how to handle creating, updating and deleting records, using column families for different types of data (and why).
Bug bites Elephant? Test-driven Quality Assurance in Big Data Application Dev...inovex GmbH
Around the currently available large piles of Big Data, there's happening quite a mixed gathering: Business Engineers define which insightswould be precious, Analysts build models, Hadoop programmers tame the flood of data, and Operations people setup machines and networks. It's exactly the interplay of all participants which is central to project success. This setup together with the distributed nature of processing poses new challenges to well-established models of assuring software artifact quality: How can non-programmers define acceptance criteria? How can functionalities be tested which depend on cluster execution, orchestration of, e.g., different hadoop jobs without delaying the development process? Which data selection is suited best for simulating the live environment? How can intermediate results in arbitrary serialization formats be inspected?
In this talk, experiences and best practices from approaching these problems in a large-scale log data analysis project will be presented. At 1&1, our team develops hadoop applications which process roughly 1 billion log events (~1 TB) per day. We will give an overview of the hard- and software setup of our quality assurance environment, which includes FitNesse as a wiki-style acceptance testing framework.Starting from a comparison with existing test frameworks like MRUnit, we will explain how we automate the parameterized deployment of our applications, choose test data sampling strategies, perform workflow management and orchestration of jobs / applications, and use Pig for inspection of intermediate results and definition of final acceptance criteria. Our conclusion is that test-driven development in the field of Big Data requires adaption of existing paradigms, but is crucial for maintaining high quality standards for the resulting applications.
Apache Oozie has come a long way and now accounts for over 2.8 Million jobs per month on Yahoo's grid infrastructure. If you are running Hadoop jobs repeatedly and thinking of a smarter way of doing it, Apache Oozie is the answer. Be it running complex data transformation jobs chained one after another or simple daily data copy, Oozie workflows will help you to manage these tasks efficiently. Mona will cover the new features introduced in Apache Oozie 4.x, in particular, Apache HCatalog Integration, Job Notifications and SLA Monitoring for building large-scale and efficient data processing pipelines.
Finding knowledge, data and answers on the Semantic Webebiquity
Web search engines like Google have made us all smarter by providing ready access to the world's knowledge whenever we need to look up a fact, learn about a topic or evaluate opinions. The W3C's Semantic Web effort aims to make such knowledge more accessible to computer programs by publishing it in machine understandable form.
<p>
As the volume of Semantic Web data grows software agents will need their own search engines to help them find the relevant and trustworthy knowledge they need to perform their tasks. We will discuss the general issues underlying the indexing and retrieval of RDF based information and describe Swoogle, a crawler based search engine whose index contains information on over a million RDF documents.
<p>
We will illustrate its use in several Semantic Web related research projects at UMBC including a distributed platform for constructing end-to-end use cases that demonstrate the semantic web’s utility for integrating scientific data. We describe ELVIS (the Ecosystem Location Visualization and Information System), a suite of tools for constructing food webs for a given location, and Triple Shop, a SPARQL query interface which searches the Semantic Web for data relevant to a given query ELVIS functionality is exposed as a collection of web services, and all input and output data is expressed in OWL, thereby enabling its integration with Triple Shop and other semantic web resources.
Video: https://www.youtube.com/watch?v=Rt2oHibJT4k
Technologies such as Hadoop have addressed the "Volume" problem of Big Data, and technologies such as Spark have recently addressed the "Velocity" problem – but the "Variety" problem is largely unaddressed – there is a lot of manual "data wrangling" to mange data models.
These manual processes do not scale well. Not only is the variety of data increasing, also the rate of change in the data definitions is increasing. We can’t keep up. NoSQL data repositories can handle storage, but we need effective models of the data to fully utilize it.
This talk will present tools and a methodology to manage Big Data Models in a rapidly changing world. This talk covers:
Creating Semantic Metadata Models of Big Data Resources
Graphical UI Tools for Big Data Models
Tools to synchronize Big Data Models and Application Code
Using NoSQL Databases, such as Amazon DynamoDB, with Big Data Models
Using Big Data Models with Hadoop, Storm, Spark, Giraph, and Inference
Using Big Data Models with Machine Learning to generate Predictive Models
Developer Collaborative/Coordination processes using Big Data Models and Git
Managing change – Big Data Models with rapidly changing Data Resources
LDQL: A Query Language for the Web of Linked DataOlaf Hartig
I used this slideset to present our research paper at the 14th Int. Semantic Web Conference (ISWC 2015). Find a preprint of the paper here:
http://olafhartig.de/files/HartigPerez_ISWC2015_Preprint.pdf
Open Annotation Rollout, Manchester, 2013-06-25
See also PPTX version with Notes: http://www.slideshare.net/soilandreyes/2013-0624annotatingr-osopenannotationmeeting
Open Annotation Rollout, Manchester, 2013-06-25
See also PDF version: http://www.slideshare.net/soilandreyes/2013-0624annotatingr-osopenannotationmeeting-23289491
2013-07-19 myExperiment research objects, beyond workflows and packs (PPTX)Stian Soiland-Reyes
Presentation at BOSC 2013 / ISMB 2013. (PowerPoint 2013 source)
PDF: https://www.slideshare.net/soilandreyes/2013-0719bosc-2013myexperimentresearchobjectsslides
See also poster at http://www.slideshare.net/soilandreyes/2013-0718bosc-2013myexperimentresearchobjectsposter-24242509 or
submitted abstract: https://docs.google.com/document/d/1jaAuPV-EnbsyI14L56HKHBQP7eDVfeXGLlK-LwohnWw/edit?usp=sharing
We have evolved Research Objects as a mechanism to preserve digital resources related to research, by providing mechanisms, formats and architecture for describing aggregated resources (hypothesis, workflow, datasets, scripts, services), their relations (is input for, explains, used by), provenance (graph was derived from dataset A, B and C) and attribution (who contributed what, and when?).
The website myExperiment is already popular for collaborating on, publishing and sharing scientific workflows, however we have found that for understanding and preserving a workflow over time, its definition is not enough, specially faced with workflow decay, services and tools that change over time. We have therefore adapted the research object model as a foundation for the myExperiment packs, allowing uploading of workflow runs, inputs, outputs and other files relevant to the workflow, relating them with annotations and integrated the Wf4Ever architecture for performing decay analysis and tracking a research object’s evolution as it and its constituent resources change over time.
“Publishing and Consuming Linked Data. (Lessons learnt when using LOD in an a...Marta Villegas
Talk given at the "1st Summer Datathon on Linguistic Linked Open Data (SD-LLOD-15)"
In this talk we will describe our experience when publishing and, more crucially, consuming Linked Data at the Spanish CLARIN Knowledge Centre (http://lod.iula.upf.edu). The center includes a Catalog of NLP resources & tools which aims to promote the use of language technology to researches of Humanities and Social Sciences. Though the original data set followed the XML/XSD schema, this was rewritten in accordance to the LOD approach in order to maximize the information contained in our repositories and to be able to enrich the data there.
We will addresses some critical aspects when RDFying XSD/XML data focusing on the strategy followed when mapping controlled vocabularies expressed in XML enumerations; when dealing with certain unstructured data (those where input strings may generate relevant instances); and when addressing identity resolution and linking tasks once the eventual instances are RDFied. Here we will also report on data cleansing, a crucial and unavoidable task which we addressed as an incremental process where SPARQL played an important role. We will see that some of the decisions taken depend on the eventual application we have in mind. The requirements of our Catalog (implemented as a web browser) include: displaying data to the user in a comprehensive way; aggregating external data in a sensitive manner and making hidden implicit relations explicit. In addition, the system needs to provide fresh data (regularly updated) in a quick response time.
Finally, we will report on our experiences when addressing data integration and enrichment (via data mashup). We experimented with different strategies (e.g. using external URIS vs caching local data) and faced different problems (time latency, dereferencing external URIS) that may be useful to share.
Talk about Exploring the Semantic Web, and particularly Linked Data, and the Rhizomer approach. Presented August 14th 2012 at the SRI AIC Seminar Series, Menlo Park, CA
Metadata Provenance Tutorial at SWIB 13, Part 1Kai Eckert
The slides of part one of the Metadata Provenance Tutorial (Linked Data Provenance). Part 2 is here: http://de.slideshare.net/MagnusPfeffer/metadata-provenance-tutorial-part-2-modelling-provenance-in-rdf
BDW Chicago 2016 - Jim Scott, Director, Enterprise Strategy & Architecture - ...Big Data Week
For the past 25 years applications have been getting built using an RDBMS with a predefined schema which forces data to conform with a schema on-write. Many people still think that they must use an RDBMS for applications even though records in their datasets have no relation to one another. Additionally, those databases are optimized for transactional use, and data must be exported for analytics purposes. NoSQL technologies have turned that model on its side to deliver groundbreaking performance improvements.
I will walk through a music database with over 100 tables in the schema and show how to convert that model over for use with a NoSQL database. I will show how to handle creating, updating and deleting records, using column families for different types of data (and why).
Bug bites Elephant? Test-driven Quality Assurance in Big Data Application Dev...inovex GmbH
Around the currently available large piles of Big Data, there's happening quite a mixed gathering: Business Engineers define which insightswould be precious, Analysts build models, Hadoop programmers tame the flood of data, and Operations people setup machines and networks. It's exactly the interplay of all participants which is central to project success. This setup together with the distributed nature of processing poses new challenges to well-established models of assuring software artifact quality: How can non-programmers define acceptance criteria? How can functionalities be tested which depend on cluster execution, orchestration of, e.g., different hadoop jobs without delaying the development process? Which data selection is suited best for simulating the live environment? How can intermediate results in arbitrary serialization formats be inspected?
In this talk, experiences and best practices from approaching these problems in a large-scale log data analysis project will be presented. At 1&1, our team develops hadoop applications which process roughly 1 billion log events (~1 TB) per day. We will give an overview of the hard- and software setup of our quality assurance environment, which includes FitNesse as a wiki-style acceptance testing framework.Starting from a comparison with existing test frameworks like MRUnit, we will explain how we automate the parameterized deployment of our applications, choose test data sampling strategies, perform workflow management and orchestration of jobs / applications, and use Pig for inspection of intermediate results and definition of final acceptance criteria. Our conclusion is that test-driven development in the field of Big Data requires adaption of existing paradigms, but is crucial for maintaining high quality standards for the resulting applications.
Apache Oozie has come a long way and now accounts for over 2.8 Million jobs per month on Yahoo's grid infrastructure. If you are running Hadoop jobs repeatedly and thinking of a smarter way of doing it, Apache Oozie is the answer. Be it running complex data transformation jobs chained one after another or simple daily data copy, Oozie workflows will help you to manage these tasks efficiently. Mona will cover the new features introduced in Apache Oozie 4.x, in particular, Apache HCatalog Integration, Job Notifications and SLA Monitoring for building large-scale and efficient data processing pipelines.
Finding knowledge, data and answers on the Semantic Webebiquity
Web search engines like Google have made us all smarter by providing ready access to the world's knowledge whenever we need to look up a fact, learn about a topic or evaluate opinions. The W3C's Semantic Web effort aims to make such knowledge more accessible to computer programs by publishing it in machine understandable form.
<p>
As the volume of Semantic Web data grows software agents will need their own search engines to help them find the relevant and trustworthy knowledge they need to perform their tasks. We will discuss the general issues underlying the indexing and retrieval of RDF based information and describe Swoogle, a crawler based search engine whose index contains information on over a million RDF documents.
<p>
We will illustrate its use in several Semantic Web related research projects at UMBC including a distributed platform for constructing end-to-end use cases that demonstrate the semantic web’s utility for integrating scientific data. We describe ELVIS (the Ecosystem Location Visualization and Information System), a suite of tools for constructing food webs for a given location, and Triple Shop, a SPARQL query interface which searches the Semantic Web for data relevant to a given query ELVIS functionality is exposed as a collection of web services, and all input and output data is expressed in OWL, thereby enabling its integration with Triple Shop and other semantic web resources.
Video: https://www.youtube.com/watch?v=Rt2oHibJT4k
Technologies such as Hadoop have addressed the "Volume" problem of Big Data, and technologies such as Spark have recently addressed the "Velocity" problem – but the "Variety" problem is largely unaddressed – there is a lot of manual "data wrangling" to mange data models.
These manual processes do not scale well. Not only is the variety of data increasing, also the rate of change in the data definitions is increasing. We can’t keep up. NoSQL data repositories can handle storage, but we need effective models of the data to fully utilize it.
This talk will present tools and a methodology to manage Big Data Models in a rapidly changing world. This talk covers:
Creating Semantic Metadata Models of Big Data Resources
Graphical UI Tools for Big Data Models
Tools to synchronize Big Data Models and Application Code
Using NoSQL Databases, such as Amazon DynamoDB, with Big Data Models
Using Big Data Models with Hadoop, Storm, Spark, Giraph, and Inference
Using Big Data Models with Machine Learning to generate Predictive Models
Developer Collaborative/Coordination processes using Big Data Models and Git
Managing change – Big Data Models with rapidly changing Data Resources
LDQL: A Query Language for the Web of Linked DataOlaf Hartig
I used this slideset to present our research paper at the 14th Int. Semantic Web Conference (ISWC 2015). Find a preprint of the paper here:
http://olafhartig.de/files/HartigPerez_ISWC2015_Preprint.pdf
Rethinking Online SPARQL Querying to Support Incremental Result VisualizationOlaf Hartig
These are the slides of my invited talk at the 5th Int. Workshop on Usage Analysis and the Web of Data (USEWOD 2015): http://usewod.org/usewod2015.html
The abstract of this talks is given as follows:
To reduce user-perceived response time many interactive Web applications visualize information in a dynamic, incremental manner. Such an incremental presentation can be particularly effective for cases in which the underlying data processing systems are not capable of completely answering the users' information needs instantaneously. An example of such systems are systems that support live querying of the Web of Data, in which case query execution times of several seconds, or even minutes, are an inherent consequence of these systems' ability to guarantee up-to-date results. However, support for an incremental result visualization has not received much attention in existing work on such systems. Therefore, the goal of this talk is to discuss approaches that enable query systems for the Web of Data to return query results incrementally.
An Overview on PROV-AQ: Provenance Access and QueryOlaf Hartig
The slides which I used at the Dagstuhl seminar on Principles of Provenance (Feb.2012) for presenting the main contributions and open issues of the PROV-AQ document created by the W3C provenance working group.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Welocme to ViralQR, your best QR code generator.ViralQR
Welcome to ViralQR, your best QR code generator available on the market!
At ViralQR, we design static and dynamic QR codes. Our mission is to make business operations easier and customer engagement more powerful through the use of QR technology. Be it a small-scale business or a huge enterprise, our easy-to-use platform provides multiple choices that can be tailored according to your company's branding and marketing strategies.
Our Vision
We are here to make the process of creating QR codes easy and smooth, thus enhancing customer interaction and making business more fluid. We very strongly believe in the ability of QR codes to change the world for businesses in their interaction with customers and are set on making that technology accessible and usable far and wide.
Our Achievements
Ever since its inception, we have successfully served many clients by offering QR codes in their marketing, service delivery, and collection of feedback across various industries. Our platform has been recognized for its ease of use and amazing features, which helped a business to make QR codes.
Our Services
At ViralQR, here is a comprehensive suite of services that caters to your very needs:
Static QR Codes: Create free static QR codes. These QR codes are able to store significant information such as URLs, vCards, plain text, emails and SMS, Wi-Fi credentials, and Bitcoin addresses.
Dynamic QR codes: These also have all the advanced features but are subscription-based. They can directly link to PDF files, images, micro-landing pages, social accounts, review forms, business pages, and applications. In addition, they can be branded with CTAs, frames, patterns, colors, and logos to enhance your branding.
Pricing and Packages
Additionally, there is a 14-day free offer to ViralQR, which is an exceptional opportunity for new users to take a feel of this platform. One can easily subscribe from there and experience the full dynamic of using QR codes. The subscription plans are not only meant for business; they are priced very flexibly so that literally every business could afford to benefit from our service.
Why choose us?
ViralQR will provide services for marketing, advertising, catering, retail, and the like. The QR codes can be posted on fliers, packaging, merchandise, and banners, as well as to substitute for cash and cards in a restaurant or coffee shop. With QR codes integrated into your business, improve customer engagement and streamline operations.
Comprehensive Analytics
Subscribers of ViralQR receive detailed analytics and tracking tools in light of having a view of the core values of QR code performance. Our analytics dashboard shows aggregate views and unique views, as well as detailed information about each impression, including time, device, browser, and estimated location by city and country.
So, thank you for choosing ViralQR; we have an offer of nothing but the best in terms of QR code services to meet business diversity!
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
FIDO Alliance Osaka Seminar: Passkeys at Amazon.pdf
Brief Introduction to the Provenance Vocabulary (for W3C prov-xg)
1. The Provenance Vocabulary
http://purl.org/net/provenance/
Olaf Hartig
Jun Zhao
W3C Provenance Incubator Group call May 14, 2010
2. Our Goal
● Integrate provenance metadata into the Web of
data to enable information quality assessment
● Vocabulary to describe provenance of Linked
Data on the Web
● Easy to use
● By people who provide Linked Data
● By developers of Linked Data publishing tools
May 14, 2010 The Provenance Vocabulary 2
3. Overview of the Vocabulary
● Defined as an OWL ontology
● Partitioned into:
● Core ontology
● Supplementary modules: types, integrity verification
May 14, 2010 The Provenance Vocabulary 3
4. Overview of the Vocabulary
May 14, 2010 The Provenance Vocabulary 4
5. Example
< > a prv:DataItem ;
foaf:primaryTopic <http://example.org/gene/0030840> .
prv:createdBy [
a prv:DataCreation ;
prv:performedAt "2010-03-01...00:00"^^xsd:dateTime ;
prv:performedBy <http://example.org/triplify> ;
prv:usedGuideline _:a ;
prv:usedData _:b ] .
<http://example.org/triplify> a prv:NonHumanActor ;
rdfs:comment "Instance of Triplify V0.5" ;
prv:operatedBy <http://olafhartig.de/foaf.rdf#olaf> .
The data item was created by a process, performed at a given time and
performed by a service ex:triplify that was operated by myfoaf:olaf.
May 14, 2010 The Provenance Vocabulary 5
6. Example cont.
_:a a prvTypes:TriplifyConfiguration , prv:CreationGuideline;
prv:createdBy [ a prv:DataCreation ;
prv:performedBy <http://olafhartig.de/foaf.rdf#olaf> ] .
_:b a prv:DataItem ;
prv:retrievedBy [
a prv:DataAccess ;
prv:performedAt "2010-03-01T12...00:00"^^xsd:dateTime ;
prv:performedBy <http://example.org/triplify> ;
prv:accessedService [
a prv:DataProvidingService , prvTypes:JDBCService ;
foaf:homepage <http://flybase.org/> ]
].
The source data item _:b –used to create the data item described before–
was retrieved by ex:triplify by accessing a public JDBC access point.
May 14, 2010 The Provenance Vocabulary 6
7. Design Principles
● Usability and understandability
● No specific granularity prescribed
● void:Dataset rdfs:subClassOf prv:DataItem
● rdf:Statement rdfs:subClassOf prv:DataItem
● Other vocabularies for more detailed
descriptions of certain aspects
● OPMV, PML, HTTP vocab, Changeset, etc.
● Schema-level links to related Vocabularies
● e.g. prv:Actor owl:equivalentClass foaf:Agent
May 14, 2010 The Provenance Vocabulary 7
8. Provenance-enabled Publication
● Metadata components
for widely used Linked
Data publishing tools
● Triplify
● Pubby
● D2R Server
● Automatic generation
of provenance metadata
● Simple configuration
May 14, 2010 The Provenance Vocabulary 8
9. Future Work
● Alignment with other provenance-related
vocabularies and models
● Additional modules for specific aspects that
are not covered by other vocabularies
● Integration in other publication tools
May 14, 2010 The Provenance Vocabulary 9
10. These slides have been created by
Jun Zhao and Olaf Hartig
This work is licensed under a
Creative Commons Attribution-Share Alike 3.0 License
(http://creativecommons.org/licenses/by-sa/3.0/)
May 14, 2010 The Provenance Vocabulary 10
11. Idea for a Mapping to OPM <>
wasGeneratedBy(prv:DataCreation)
_:b
wasGeneratedBy(prv:retrievedBy)
or better used(prv:usedData)
wasGeneratedBy(prv:DataAccess) ?
used(prv:usedGuideline)
wasControlledBy(prvTypes:DataCreatingService)
_:a
wasControlledBy(prv:DataAccessor) or better
or better wasControlledBy(prv:performedBy) ?
wasControlledBy(prv:performedBy) ?
ex:triplify
wasControlledBy(prv:DataProvidingService)
or better myfoaf:olaf wasGeneratedBy(prv:DataCrea
wasControlledBy(prv:accessedService) ?
wasControlledBy(prvTypes:DataCreatingEntity)
May 14, 2010 The Provenance Vocabulary 11
