The presenter studied computer science and has over 5 years of experience with .NET and C#. He currently works for Infusion Development and has contributed to dotNetRDF for 1.5 years.
DotNetRDF is an open source .NET library for working with RDF data. It was started in 2009 as part of a PhD project and provides APIs for loading, querying, and updating RDF graphs from triple stores and serializations. The core concepts include nodes, triples, and graphs. It also supports SPARQL queries and triple store access.
The presenter discussed ongoing work to improve standards compliance and add features like OWL reasoning and SPIN. He has contributed APIs for fluent S
dotNetRDF - A Semantic Web/RDF Library for .Net DevelopersRob Vesse
A quick overview and introduction to the dotNetRDF Project given in the Technical Lightning Talk session at SemTech West 2011 at the Hilton Union Square, San Fransisco
EKAW - Publishing with Triple Pattern FragmentsRuben Taelman
Slides for the presentation on Publishing with Triple Pattern Fragments in the Modeling, Generating and Publishing knowledge as Linked Data tutorial at EKAW 2016.
dotNetRDF - A Semantic Web/RDF Library for .Net DevelopersRob Vesse
A quick overview and introduction to the dotNetRDF Project given in the Technical Lightning Talk session at SemTech West 2011 at the Hilton Union Square, San Fransisco
EKAW - Publishing with Triple Pattern FragmentsRuben Taelman
Slides for the presentation on Publishing with Triple Pattern Fragments in the Modeling, Generating and Publishing knowledge as Linked Data tutorial at EKAW 2016.
Postgres has the unique ability to act as a powerful data aggregator or information hub in many IT centers bringing together data from different databases and in different formats.
This presentation reviews Postgres' extensibility, foreign data wrappers, and ability to work with structured relational and unstructured NoSQL-like information such as documents and key-value data.
The Postgres capabilities are unrivaled in enabling a complete view of customers or businesses, analyzing disparate data together, and breaking down data silos within the enterprise.
If you would like to listen to the recording please visit EnterpriseDB > Resources > Webcasts > Ondemand Webcasts.
To speak to someone about EnterpriseDB's solutions and services please email sales@enterprisedb.com.
Talk given at the London Semantic Web Meetup February 17th 2015. Discusses projects that aim to bridge the gap between the RDF and the Hadoop ecosystems primarily focusing on Apache Jena Elephas.
Extending Pandas using Apache Arrow and NumbaUwe Korn
With the latest release of Pandas the ability to extend it with custom dtypes was introduced. Using Apache Arrow as the in-memory storage and Numba for fast, vectorized computations on these memory regions, it is possible to extend Pandas in pure Python while achieving the same performance of the built-in types. In the talk we implement a native string type as an example.
Semantic Integration with Apache Jena and StanbolAll Things Open
All Things Open 2014 - Day 1
Wednesday, October 22nd, 2014
Phillip Rhodes
Founder & President of Fogbeam Labs
Big Data
Semantic Integration with Apache Jena and Stanbol
Hacktoberfest 2020 'Intro to Knowledge Graph' with Chris Woodward of ArangoDB and reKnowledge. Accompanying video is available here: https://youtu.be/ZZt6xBmltz4
Efficient processing of large and complex XML documents in HadoopDataWorks Summit
Many systems capture XML data in Hadoop for analytical processing. When XML documents are large and have complex nested structures, processing such data repeatedly would be inefficient as parsing XML becomes CPU intensive, not to mention the inefficiency of storing XML in its native form. The problem is compounded in the Big Data space, when millions of such documents have to be processed and analyzed within a reasonable time. In this talk an efficient method is proposed by leveraging the Avro storage and communication format, which is flexible, compact and specifically built for Hadoop environments to model complex data structures. XML documents may be parsed and converted into Avro format on load, which can then be accessed via Hive using a SQL-like interface, Java MapReduce or Pig. A concrete use-case is provided that validates this approach along with variations of the same and their relative trade-offs.
GraphTech Ecosystem - part 1: Graph DatabasesLinkurious
The graph ecosystem presentation lists and introduces a vast majority of storage systems for graph-like data: native graph databases, RDF databases, multi-model systems or systems with a graph API.
Postgres has the unique ability to act as a powerful data aggregator or information hub in many IT centers bringing together data from different databases and in different formats.
This presentation reviews Postgres' extensibility, foreign data wrappers, and ability to work with structured relational and unstructured NoSQL-like information such as documents and key-value data.
The Postgres capabilities are unrivaled in enabling a complete view of customers or businesses, analyzing disparate data together, and breaking down data silos within the enterprise.
If you would like to listen to the recording please visit EnterpriseDB > Resources > Webcasts > Ondemand Webcasts.
To speak to someone about EnterpriseDB's solutions and services please email sales@enterprisedb.com.
Talk given at the London Semantic Web Meetup February 17th 2015. Discusses projects that aim to bridge the gap between the RDF and the Hadoop ecosystems primarily focusing on Apache Jena Elephas.
Extending Pandas using Apache Arrow and NumbaUwe Korn
With the latest release of Pandas the ability to extend it with custom dtypes was introduced. Using Apache Arrow as the in-memory storage and Numba for fast, vectorized computations on these memory regions, it is possible to extend Pandas in pure Python while achieving the same performance of the built-in types. In the talk we implement a native string type as an example.
Semantic Integration with Apache Jena and StanbolAll Things Open
All Things Open 2014 - Day 1
Wednesday, October 22nd, 2014
Phillip Rhodes
Founder & President of Fogbeam Labs
Big Data
Semantic Integration with Apache Jena and Stanbol
Hacktoberfest 2020 'Intro to Knowledge Graph' with Chris Woodward of ArangoDB and reKnowledge. Accompanying video is available here: https://youtu.be/ZZt6xBmltz4
Efficient processing of large and complex XML documents in HadoopDataWorks Summit
Many systems capture XML data in Hadoop for analytical processing. When XML documents are large and have complex nested structures, processing such data repeatedly would be inefficient as parsing XML becomes CPU intensive, not to mention the inefficiency of storing XML in its native form. The problem is compounded in the Big Data space, when millions of such documents have to be processed and analyzed within a reasonable time. In this talk an efficient method is proposed by leveraging the Avro storage and communication format, which is flexible, compact and specifically built for Hadoop environments to model complex data structures. XML documents may be parsed and converted into Avro format on load, which can then be accessed via Hive using a SQL-like interface, Java MapReduce or Pig. A concrete use-case is provided that validates this approach along with variations of the same and their relative trade-offs.
GraphTech Ecosystem - part 1: Graph DatabasesLinkurious
The graph ecosystem presentation lists and introduces a vast majority of storage systems for graph-like data: native graph databases, RDF databases, multi-model systems or systems with a graph API.
Transient and persistent RDF views over relational databases in the context o...Nikolaos Konstantinou
As far as digital repositories are concerned, numerous benefits emerge from the disposal of their contents as Linked Open Data (LOD). This leads more and more repositories towards this direction. However, several factors need to be taken into account in doing so, among which is whether the transition needs to be materialized in real-time or in asynchronous time intervals. In this paper we provide the problem framework in the context of digital repositories, we discuss the benefits and drawbacks of both approaches and draw our conclusions after evaluating a set of performance measurements. Overall, we argue that in contexts with infrequent data updates, as is the case with digital repositories, persistent RDF views are more efficient than real-time SPARQL-to-SQL rewriting systems in terms of query response times, especially when expensive SQL queries are involved.
Comparative study on the processing of RDF in PHPMSGUNC
Sharing of content on the Web is already possible through other
technologies such as FTP. It is therefore difficult to understand the need for a
single Web-based format when already there are enough formats such as
relational databases with annotated data that can be reused by other systems.
Putting information into RDF files, makes it possible for computer programs to
search, discover, pick up, collect, analyze and process information from the
web. Using RDF, a Web browser should be able to reuse the data, requiring no
additional work on the part of users, and here comes the tricky part to make
easier for web programmers to work with RDF by using some RDF libraries.
Presentation give on the Mobile Campus Assistant software and MyMobileBristol project at "Open Source Junction: cross-platform mobile apps", 30 March 2011, Trinity College, Oxford
WebSpa is a tool that allows the quick, intuitive (and even fun) interrogation of arbitrary SPARQL endpoints. WebSpa runs in the web browser and does not require the installation of any additional software. The tool manages a large variety of pre-defined SPARQL endpoints and allows the addition of new ones. An user account gives the possibility of saving both the interrogation and its results on the local computer, as well as further editing of the queries. The application is written in both Java and Flex. It uses Jena and ARQ application programming interface in order to perform the queries, and the results are processed and displayed using Flex.
Quadrupling your elephants - RDF and the Hadoop ecosystemRob Vesse
Presentation given at ApacheCon EU 2014 in Budapest on technologies aiming to bridge the gap between the RDF and the Hadoop ecosystems.
Talks primarily about RDF Tools for Hadoop (part of the Apache Jena) project and Intel Graph Builder (extensions to Pig)
A Tale of Three Apache Spark APIs: RDDs, DataFrames, and Datasets with Jules ...Databricks
Of all the developers’ delight, none is more attractive than a set of APIs that make developers productive, that are easy to use, and that are intuitive and expressive. Apache Spark offers these APIs across components such as Spark SQL, Streaming, Machine Learning, and Graph Processing to operate on large data sets in languages such as Scala, Java, Python, and R for doing distributed big data processing at scale. In this talk, I will explore the evolution of three sets of APIs-RDDs, DataFrames, and Datasets-available in Apache Spark 2.x. In particular, I will emphasize three takeaways: 1) why and when you should use each set as best practices 2) outline its performance and optimization benefits; and 3) underscore scenarios when to use DataFrames and Datasets instead of RDDs for your big data distributed processing. Through simple notebook demonstrations with API code examples, you’ll learn how to process big data using RDDs, DataFrames, and Datasets and interoperate among them. (this will be vocalization of the blog, along with the latest developments in Apache Spark 2.x Dataframe/Datasets and Spark SQL APIs: https://databricks.com/blog/2016/07/14/a-tale-of-three-apache-spark-apis-rdds-dataframes-and-datasets.html)
My presentation on RDFauthor at EKAW2010, Lisbon. For more information on RDFauthor visit http://aksw.org/Projects/RDFauthor; for the code visit http://code.google.com/p/rdfauthor/.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
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
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
2. About the presenter
Studied Computer Science at Wrocław University of Technology
Graduated in 2010
Currently works for Infusion Development in Wrocław
Over 5 year of experience with .NET and C#
1.5 years of experience with the Semantic Web
Contributes to dotNetRDF and side projects
Łódzkie Forum Semantic Web, 7.03.2013
4. Library overview
Main author is Rob Vesse
Contributor to Jena
Active member of http://answers.semanticweb.com
Project started in 2009 as part of PhD a project
Released for multiple .NET versions including Windows Phone, Silverlight and Mono
Actively developed; currently approaching version 1.0
Provides a powerful uniform API
Standards-compliant
Łódzkie Forum Semantic Web, 7.03.2013
7. Nodes, triples and graphs
INode interface: IGraph & INodeFactory interfaces
URI node Represents an RDF document
Literal node Enumerable collection of Triples
Blank node Loaded from documents, triple stores or
Variable node as the result of SPARQL queries
Nodes are created in scope of a graph Uses namespace mapper to resolve
using a node factory prefixed names (QNames)
Three nodes form a triple
Convenience methods for handling RDF
lists
Łódzkie Forum Semantic Web, 7.03.2013
8. Loading and saving graphs
Two way support of multiple RDF
serializations:
Turtle, NTriples, N3
RDF/XML
RDF/JSON
TriG, TriX, NQuads
Graphs can be loaded directly from the
web
Triple stores can load graphs
automatically based on URI
Łódzkie Forum Semantic Web, 7.03.2013
9. Triple store support
In memory triple store Support for 3rd party stores
SPARQL support Virtuoso
Serialization into quad datasets Stardog
Multiple interfaces defining store AllegroGraph
capabilities Fuseki
Transactions Dydra
SPARQL Query FourStore
SPARQL Update Sesame-compatible stores
Inferencing Can use a SPARQL endpoint as read-only
triple store
Łódzkie Forum Semantic Web, 7.03.2013
10. Querying and updating
Representing and processing queries Leviathan query processor
Uniform API to query graphs and stores Full SPARQL 1.1 support
(both in-memory and remote) SPARQL Update support
ADO.NET-like parametrized queries Leviathan function library
Fluent query API (coming soon) Jena ARQ function library
Extensible API for handling queries and XPath function library
results Full text queries using Lucene
Optimizers available and extensible
Łódzkie Forum Semantic Web, 7.03.2013
12. Ontologies and inferencing
Ontology API as abstraction over triples
Based on Jena’s API
Limited reasoning support
RDFS resoner @forall :x .
SKOS reasoner { :x a ex:Car } => { :x a ex:Vehicle }
N3 rules reasoner
Remote Pellet Server reasoning
Reasoning easily applied to individual
graphs, in-memory triple stores
Łódzkie Forum Semantic Web, 7.03.2013
13. Configuration API
RDF vocabulary _:store a dnr:TripleStore ;
Configure commonly used objects for dnr:type "VDS.RDF.TripleStore" ;
easy retrieval at runtime: dnr:usingGraph _:a ;
Graphs dnr:usingGraph _:b .
Stores
Endpoints _:a a dnr:Graph ;
Many more dnr:type "VDS.RDF.Graph" ;
Can split configuration into multiple files dnr:fromFile "example.rdf" .
Easily extensible via IObjectFactory
_:b a dnr:Graph ;
dnr:type "VDS.RDF.Graph" ;
dnr:fromUri dbpedia:Southampton .
Łódzkie Forum Semantic Web, 7.03.2013
14. dotNetRDF toolkit
Command line:
rdfConvert
rdfOptStats
rdfQuery
soh (SPARQL over HTTP)
rdfWebDeploy
rdfServer
Window:
SparqlGUI
rdfEditor
Store Manager
rdfServerGui
Łódzkie Forum Semantic Web, 7.03.2013
15. What is missing/roadmap
Current effort focused on: Key missing reatures
Maintenance OWL reasoning
W3C standards compatibility SPIN
Portable Class Library RDFa
JSON-LD
Łódzkie Forum Semantic Web, 7.03.2013
16. My work with dotNetRDF
Łódzkie Forum Semantic Web, 7.03.2013
18. R2RML processor and API
Almost full compliance with R2RML
recommendation
Default mapping generator
RDBMS R2RML RDF
Import and export mappings
API for creating mapping programatically
Processor for actual RDB to RDF
conversion
Łódzkie Forum Semantic Web, 7.03.2013