DBpedia Spotlight: a configurable annotation tool to support a variety of use cases. Given input text in English, we extract DBpedia Resources and generate annotations according to user-provided configuration parameters. These parameters can include score thresholds, entity types, and even arbitrary "type" definitions through SPARQL queries.
This is the presentation at the best paper award session at I-SEMANTICS 2011.
OBA: An Ontology-Based Framework for Creating REST APIs for Knowledge Graphsdgarijo
In this presentation we describe the Ontology-Based APIs framework (OBA), our approach to automatically create REST APIs from ontologies while following RESTful API best
practices. Given an ontology (or ontology network) OBA uses standard technologies familiar to web developers (OpenAPI Specification, JSON) and combines them with W3C standards (OWL, JSON-LD frames and SPARQL) to create maintainable APIs with documentation, units tests, automated validation of resources and clients (in Python, Javascript, etc.) for non Semantic Web experts to access the contents of a target
knowledge graph. We showcase OBA with three examples that illustrate the capabilities of the framework for different ontologies.
"SPARQL Cheat Sheet" is a short collection of slides intended to act as a guide to SPARQL developers. It includes the syntax and structure of SPARQL queries, common SPARQL prefixes and functions, and help with RDF datasets.
The "SPARQL Cheat Sheet" is intended to accompany the SPARQL By Example slides available at http://www.cambridgesemantics.com/2008/09/sparql-by-example/ .
Does your search application include a custom query syntax with various search operators such as Booleans, proximity, term or phrase frequency, capitalization, quoted text or as-is operator, and other advanced operators? Although most search applications offer a natural language-oriented search box, some advanced applications may also offer a custom query syntax for advanced users or automated tasks. The Lucene "classic" query operators that are supported by the Solr edismax query parser (Boolean, phrase with slop, wildcard, etc.) cover a good amount of use cases, but they only get you so far. In this talk, we will explore various strategies to support a custom and advanced query syntax in Solr, covering a spectrum of options from leveraging the out-of-the-box Solr query DSL, to a custom Solr query parser, and hybrid solutions in between. We will identify the options' pros and cons, discuss relevancy considerations, and illustrate the options in Java.
Extending DSpace 7: DSpace-CRIS and DSpace-GLAM for empowered repositories an...4Science
Presentation given at OR2019 in Hamburg, Germany
In recent years there has been an increasing need to position institutional repositories in a broader context that enhances research opportunities and facilitates the discovery of resources. This presentation is about DSpace-CRIS and DSpace-GLAM, in their new version compatible with DSpace 7, with renewed features built with the updated technology stack of DSpace 7: Angular and REST API, their characteristics and novelties, and how their adoption can empower the role of repositories within academic, research, and cultural heritage institutions. The migration process for both DSpace-CRIS/GLAM and DSpace users that want to enhance their repository with the additional features and capabilities provided by version 7 will be presented. DSpace-CRIS and GLAM are continuously being aligned with DSpace versions and support is provided through the same community channels. Finally, the future roadmap of the project will be discussed, in the same way as in the last ten years when ideas and features blossomed in DSpace-CRIS were later adopted by the standard DSpace distribution. The community is numerous and growing and the exchange of experiences is beneficial for all organizations.
OBA: An Ontology-Based Framework for Creating REST APIs for Knowledge Graphsdgarijo
In this presentation we describe the Ontology-Based APIs framework (OBA), our approach to automatically create REST APIs from ontologies while following RESTful API best
practices. Given an ontology (or ontology network) OBA uses standard technologies familiar to web developers (OpenAPI Specification, JSON) and combines them with W3C standards (OWL, JSON-LD frames and SPARQL) to create maintainable APIs with documentation, units tests, automated validation of resources and clients (in Python, Javascript, etc.) for non Semantic Web experts to access the contents of a target
knowledge graph. We showcase OBA with three examples that illustrate the capabilities of the framework for different ontologies.
"SPARQL Cheat Sheet" is a short collection of slides intended to act as a guide to SPARQL developers. It includes the syntax and structure of SPARQL queries, common SPARQL prefixes and functions, and help with RDF datasets.
The "SPARQL Cheat Sheet" is intended to accompany the SPARQL By Example slides available at http://www.cambridgesemantics.com/2008/09/sparql-by-example/ .
Does your search application include a custom query syntax with various search operators such as Booleans, proximity, term or phrase frequency, capitalization, quoted text or as-is operator, and other advanced operators? Although most search applications offer a natural language-oriented search box, some advanced applications may also offer a custom query syntax for advanced users or automated tasks. The Lucene "classic" query operators that are supported by the Solr edismax query parser (Boolean, phrase with slop, wildcard, etc.) cover a good amount of use cases, but they only get you so far. In this talk, we will explore various strategies to support a custom and advanced query syntax in Solr, covering a spectrum of options from leveraging the out-of-the-box Solr query DSL, to a custom Solr query parser, and hybrid solutions in between. We will identify the options' pros and cons, discuss relevancy considerations, and illustrate the options in Java.
Extending DSpace 7: DSpace-CRIS and DSpace-GLAM for empowered repositories an...4Science
Presentation given at OR2019 in Hamburg, Germany
In recent years there has been an increasing need to position institutional repositories in a broader context that enhances research opportunities and facilitates the discovery of resources. This presentation is about DSpace-CRIS and DSpace-GLAM, in their new version compatible with DSpace 7, with renewed features built with the updated technology stack of DSpace 7: Angular and REST API, their characteristics and novelties, and how their adoption can empower the role of repositories within academic, research, and cultural heritage institutions. The migration process for both DSpace-CRIS/GLAM and DSpace users that want to enhance their repository with the additional features and capabilities provided by version 7 will be presented. DSpace-CRIS and GLAM are continuously being aligned with DSpace versions and support is provided through the same community channels. Finally, the future roadmap of the project will be discussed, in the same way as in the last ten years when ideas and features blossomed in DSpace-CRIS were later adopted by the standard DSpace distribution. The community is numerous and growing and the exchange of experiences is beneficial for all organizations.
Importing Data into Neo4j quickly and easily - StackOverflowNeo4j
In this GraphConnect presentation Mark and Michael show several ways to import large amounts of highly connected data from different formats into Neo4j. Both Cypher's LOAD CSV as well as the bulk importer is demonstrated along with many tips.
We use the well know StackOverflow Q&A site data which is interestingly very graphy.
SPARQL introduction and training (130+ slides with exercices)Thomas Francart
Full SPARQL training
Covers all SPARQL : basic graph patterns, FILTERs, functions, property paths, optional, negation, assignation, aggregation, subqueries, federated queries.
Does not cover except SPARQL updates.
Includes exercices on DBPedia.
CC BY license
Model Your Application Domain, Not Your JSON StructuresMarkus Lanthaler
Presentation of the paper "Model Your Application Domain, Not Your JSON Structures" at the 4th International Workshop on RESTful Design (WS-REST 2013) at the WWW2013 in Rio de Janeiro, Brazil
This PPT is about my best friends, HTML, CSS and JS. Here I am just talk/show few features of them. all three combined make our web site more powerful in this WWW world.
A tutorial on how to create mappings using ontop, how inference (OWL 2 QL and RDFS) plays a role answering SPARQL queries in ontop, and how ontop's support for on-the-fly SQL query translation enables scenarios of semantic data access and data integration.
Or2019 DSpace 7 Enhanced submission & workflow4Science
The last two years have been very intense for the DSpace community. A great effort has been put into finalizing the development of a DSpace release, 7.0, which has many changes from previous releases, particularly with regard to UI technology.
As part of the activities related to the creation of DSpace 7, particularly innovative is the submission and workflow process that can be associated with the different collections.
The presentation will provide a deep dive into the new Enhanced Submission and Workflow features of DSpace 7, including how to configure, customize & use this feature (and differences with DSpace 6 and below)
Although RDF is a corner stone of semantic web and knowledge graphs, it has not been embraced by everyday programmers and software architects who need to safely create and access well-structured data. There is a lack of common tools and methodologies that are available in more conventional settings to improve data quality by defining schemas that can later be validated. Two technologies have recently been proposed for RDF validation: Shape Expressions (ShEx) and Shapes Constraint Language (SHACL). In the talk, we will review the history and motivation of both technologies. We will also and enumerate some challenges and future work with regards to RDF validation.
Understand about what JSON is
Understand the difference between JSON and XML
Understand the context of using JSON with AJAX
Know how to read and write JSON data using PHP
These are slides from our Big Data Warehouse Meetup in April. We talked about NoSQL databases: What they are, how they’re used and where they fit in existing enterprise data ecosystems.
Mike O’Brian from 10gen, introduced the syntax and usage patterns for a new aggregation system in MongoDB and give some demonstrations of aggregation using the new system. The new MongoDB aggregation framework makes it simple to do tasks such as counting, averaging, and finding minima or maxima while grouping by keys in a collection, complementing MongoDB’s built-in map/reduce capabilities.
For more information, visit our website at http://casertaconcepts.com/ or email us at info@casertaconcepts.com.
This is a brief introduction about HTML5. You will learn that what is new in HTML5. I will tell what and when changes happened in HTML which Hyper Text markup language. Html is a language which is used to create web pages that we have seen on the internet. For website development and web hosting visit https://tekfold.com
A Virtuous Cycle of Semantic Enhancement with DBpedia Spotlight - SemTech Ber...Pablo Mendes
A Virtuous Cycle of Semantic Enhancement with DBpedia Spotlight
Presented at SemTech Berlin 2012
Wikipedia is one of the most important repositories of human knowledge, containing millions of interlinked articles. The DBpedia project extracts and combines Wikipedia information into a large multilingual knowledge base that enables semantic processing in a wide range of applications. We have built DBpedia Spotlight, a tool that recognizes ambiguous terms in text and automatically assigns unambiguous definitions to those terms by connecting them to DBpedia. Such interconnection enriches information by providing explicit semantic relationships, enabling semantic indexing, faceted exploration, among other data processing enhancements. In this talk we will describe how DBpedia Spotlight can be applied to establish a virtuous cycle of semantic enhancement. On the one hand, it can enhance knowledge interconnectivity in document collections. On the other hand, it learns how to better annotate from user feedback. Such a positive feedback loop can be applied on Wikipedia itself, or in enterprises to alleviate the cold start problem and knowledge management costs.
DBpedia Spotlight is a tool employed in the Extraction stage of the LOD Lyfe Cycle, performing Entity Recognition and Linking. Although the tool currently specializes in English language, the support for other languages is currently being tested, and demos for German, Dutch and others are available or underway. The tool can be used to enable faceted browsing, semantic search, among other applications. In this webinar we will describe what is DBpedia Spotlight, how it works and how can you benefit from it in your application.
If you are interested in Linked (Open) Data principles and mechanisms, LOD tools & services and concrete use cases that can be realised using LOD then join us in the free LOD2 webinar series!
http://lod2.eu/BlogPost/webinar-series
Importing Data into Neo4j quickly and easily - StackOverflowNeo4j
In this GraphConnect presentation Mark and Michael show several ways to import large amounts of highly connected data from different formats into Neo4j. Both Cypher's LOAD CSV as well as the bulk importer is demonstrated along with many tips.
We use the well know StackOverflow Q&A site data which is interestingly very graphy.
SPARQL introduction and training (130+ slides with exercices)Thomas Francart
Full SPARQL training
Covers all SPARQL : basic graph patterns, FILTERs, functions, property paths, optional, negation, assignation, aggregation, subqueries, federated queries.
Does not cover except SPARQL updates.
Includes exercices on DBPedia.
CC BY license
Model Your Application Domain, Not Your JSON StructuresMarkus Lanthaler
Presentation of the paper "Model Your Application Domain, Not Your JSON Structures" at the 4th International Workshop on RESTful Design (WS-REST 2013) at the WWW2013 in Rio de Janeiro, Brazil
This PPT is about my best friends, HTML, CSS and JS. Here I am just talk/show few features of them. all three combined make our web site more powerful in this WWW world.
A tutorial on how to create mappings using ontop, how inference (OWL 2 QL and RDFS) plays a role answering SPARQL queries in ontop, and how ontop's support for on-the-fly SQL query translation enables scenarios of semantic data access and data integration.
Or2019 DSpace 7 Enhanced submission & workflow4Science
The last two years have been very intense for the DSpace community. A great effort has been put into finalizing the development of a DSpace release, 7.0, which has many changes from previous releases, particularly with regard to UI technology.
As part of the activities related to the creation of DSpace 7, particularly innovative is the submission and workflow process that can be associated with the different collections.
The presentation will provide a deep dive into the new Enhanced Submission and Workflow features of DSpace 7, including how to configure, customize & use this feature (and differences with DSpace 6 and below)
Although RDF is a corner stone of semantic web and knowledge graphs, it has not been embraced by everyday programmers and software architects who need to safely create and access well-structured data. There is a lack of common tools and methodologies that are available in more conventional settings to improve data quality by defining schemas that can later be validated. Two technologies have recently been proposed for RDF validation: Shape Expressions (ShEx) and Shapes Constraint Language (SHACL). In the talk, we will review the history and motivation of both technologies. We will also and enumerate some challenges and future work with regards to RDF validation.
Understand about what JSON is
Understand the difference between JSON and XML
Understand the context of using JSON with AJAX
Know how to read and write JSON data using PHP
These are slides from our Big Data Warehouse Meetup in April. We talked about NoSQL databases: What they are, how they’re used and where they fit in existing enterprise data ecosystems.
Mike O’Brian from 10gen, introduced the syntax and usage patterns for a new aggregation system in MongoDB and give some demonstrations of aggregation using the new system. The new MongoDB aggregation framework makes it simple to do tasks such as counting, averaging, and finding minima or maxima while grouping by keys in a collection, complementing MongoDB’s built-in map/reduce capabilities.
For more information, visit our website at http://casertaconcepts.com/ or email us at info@casertaconcepts.com.
This is a brief introduction about HTML5. You will learn that what is new in HTML5. I will tell what and when changes happened in HTML which Hyper Text markup language. Html is a language which is used to create web pages that we have seen on the internet. For website development and web hosting visit https://tekfold.com
A Virtuous Cycle of Semantic Enhancement with DBpedia Spotlight - SemTech Ber...Pablo Mendes
A Virtuous Cycle of Semantic Enhancement with DBpedia Spotlight
Presented at SemTech Berlin 2012
Wikipedia is one of the most important repositories of human knowledge, containing millions of interlinked articles. The DBpedia project extracts and combines Wikipedia information into a large multilingual knowledge base that enables semantic processing in a wide range of applications. We have built DBpedia Spotlight, a tool that recognizes ambiguous terms in text and automatically assigns unambiguous definitions to those terms by connecting them to DBpedia. Such interconnection enriches information by providing explicit semantic relationships, enabling semantic indexing, faceted exploration, among other data processing enhancements. In this talk we will describe how DBpedia Spotlight can be applied to establish a virtuous cycle of semantic enhancement. On the one hand, it can enhance knowledge interconnectivity in document collections. On the other hand, it learns how to better annotate from user feedback. Such a positive feedback loop can be applied on Wikipedia itself, or in enterprises to alleviate the cold start problem and knowledge management costs.
DBpedia Spotlight is a tool employed in the Extraction stage of the LOD Lyfe Cycle, performing Entity Recognition and Linking. Although the tool currently specializes in English language, the support for other languages is currently being tested, and demos for German, Dutch and others are available or underway. The tool can be used to enable faceted browsing, semantic search, among other applications. In this webinar we will describe what is DBpedia Spotlight, how it works and how can you benefit from it in your application.
If you are interested in Linked (Open) Data principles and mechanisms, LOD tools & services and concrete use cases that can be realised using LOD then join us in the free LOD2 webinar series!
http://lod2.eu/BlogPost/webinar-series
Summary: Graphs are structures commonly used in computer science that model the interactions among entities. I will start from introducing the basic formulations of graph based machine learning, which has been a popular topic of research in the past decade and led to a powerful set of techniques. Particularly, I will show examples on how it acts as a generic data mining and predictive analytic tool. In the second part, I am going to discuss applications of such learning techniques in media analytics: (1) image analysis, where visually coherent objects are isolated from images; (2) social analysis of videos, where actors' social properties are predicted from videos. Materials in this part are based on our recent publications in highly selective venues (papers on https://sites.google.com/site/leiding2010/ ).
Bio: Lei Ding is a researcher making sense of large amounts of data in all media types. He currently works in Intent Media as a scientist, focusing on data analytics and applied machine learning in online advertising. Previously, he has worked in several research institutions including Columbia University, UIUC and IBM Research on digital / social media analysis and understanding. He received a Ph.D. degree in Computer Science and Engineering from The Ohio State University, where he was a Distinguished University Fellow.
How to use Latent Semantic Analysis to Glean Real Insight - Franco AmalfiSocial Media Camp
Latent Semantic Analysis (LSA) is an advanced form of statistical language modeling that cuts through the noise to expose contextual meaning, and is a key feature of Oracle Social Relationship Management platform.
Come and learn how LSA delivers more accurate,contextualized, precise and relevant insights. Oracle SRM listening capabilities go well beyond keyword and Boolean searches to reveal insights like consumer intent, political intent, product likes/dislikes, and customer service issues.
From the NYC Machine Learning meetup on Jan 17, 2013: http://www.meetup.com/NYC-Machine-Learning/events/97871782/
Video is available here: http://vimeo.com/57900625
The slideset used to conduct an introduction/tutorial
on DBpedia use cases, concepts and implementation
aspects held during the DBpedia community meeting
in Dublin on the 9th of February 2015.
(slide creators: M. Ackermann, M. Freudenberg
additional presenter: Ali Ismayilov)
Filtering Inaccurate Entity Co-references on the Linked Open Dataebrahim_bagheri
A method for identifying incorrect sameAs links on the Linked Open Data cloud
Details published in:
John Cuzzola, Ebrahim Bagheri, Jelena Jovanovic:
Filtering Inaccurate Entity Co-references on the Linked Open Data. DEXA (1) 2015: 128-143
5 Lessons Learned from Designing Neural Models for Information RetrievalBhaskar Mitra
Slides from my keynote talk at the Recherche d'Information SEmantique (RISE) workshop at CORIA-TALN 2018 conference in Rennes, France.
(Abstract)
Neural Information Retrieval (or neural IR) is the application of shallow or deep neural networks to IR tasks. Unlike classical IR models, these machine learning (ML) based approaches are data-hungry, requiring large scale training data before they can be deployed. Traditional learning to rank models employ supervised ML techniques—including neural networks—over hand-crafted IR features. By contrast, more recently proposed neural models learn representations of language from raw text that can bridge the gap between the query and the document vocabulary.
Neural IR is an emerging field and research publications in the area has been increasing in recent years. While the community explores new architectures and training regimes, a new set of challenges, opportunities, and design principles are emerging in the context of these new IR models. In this talk, I will share five lessons learned from my personal research in the area of neural IR. I will present a framework for discussing different unsupervised approaches to learning latent representations of text. I will cover several challenges to learning effective text representations for IR and discuss how latent space models should be combined with observed feature spaces for better retrieval performance. Finally, I will conclude with a few case studies that demonstrates the application of neural approaches to IR that go beyond text matching.
We now have larger Knowledge Bases than ever before. (10 billion facts is now a small number).
We now have the instruments to observe and analyse these very large Knowledge Bases.
We can use these insights for better tools for querying, inferencing, publishing, maintaining, visualising and explaining.
It is a NYC Open Data Meetup event. All credits went to Kannan and Roman.
Event link: http://www.meetup.com/NYC-Open-Data/events/141123082/ Blog Post: http://www.nycopendata.com/2014/02/11/mongodb/
An overview of the Network Overview Discovery and Exploration add-in for Excel 2007 (NodeXL), a social network analysis add-in for the familiar spreadsheet application. Visualize twitter, flickr, facebook, and email networks with just a few mouse clicks.
Guest lecture at the Syracuse University School of Information Studies eScience Librarianship Lecture Series (08 Dec 2011).
Description: It’s your government, is it your data? New approaches to building interlinked catalogs of government-produced data. Dr. John S. Erickson, Director of Web Science Operations for the Tetherless World Constellation at Rensselaer Polytechnic Institute will present technical methods being developed to manage the delivery of large-scale open government data projects based on semantic web and linked data best practices.
Query logs record the actual usage of search systems and
their analysis has proven critical to improving search engine
functionality. Yet, despite the deluge of information, query
log analysis often suffers from the sparsity of the query space.
Based on the observation that most queries pivot around a
single entity that represents the main focus of the user’s
need, we propose a new model for query log data called the
entity-aware click graph. In this representation, we decom-
pose queries into entities and modifiers, and measure their
association with clicked pages. We demonstrate the benefits
of this approach on the crucial task of understanding which
websites fulfill similar user needs, showing that using this
representation we can achieve a higher precision than other
query log-based approaches.
Sieve - Data Quality and Fusion - LWDM2012Pablo Mendes
Presentation at the LWDM workshop at EDBT 2012.
The Web of Linked Data grows rapidly and already contains data originating from hundreds of data sources. The quality of data from those sources is very diverse, as values may be out of date, incomplete or incorrect. Moreover, data sources
may provide conflicting values for a single real-world object. In order for Linked Data applications to consume data from this global data space in an integrated fashion, a number of challenges have to be overcome. One of these challenges is to rate and to integrate data based on their quality.
However, quality is a very subjective matter, and nding a canonical judgement that is suitable for each and every task is not feasible.
To simplify the task of consuming high-quality data, we present Sieve, a framework for flexibly expressing quality assessment methods as well as fusion methods. Sieve is integrated into the Linked Data Integration Framework (LDIF), which handles Data Access, Schema Mapping and Identity
Resolution, all crucial preliminaries for quality assessment and fusion.
We demonstrate Sieve in a data integration scenario importing data from the English and Portuguese versions of DBpedia, and discuss how we increase completeness, conciseness and consistency through the use of our framework.
Ligado nos Políticos at ESWC'2011 WorkshopPablo Mendes
Publishing Linked Data from Brazilian Politicians on the Web
Lucas de Ramos Araújo
Pablo N. Mendes
Jairo Francisco de Souza
At the Workshop on Semantics in Governance and Policy Modelling, Extended Semantic Web Conference 2011 ESWC2010.
May 30, 2011 - Crete, Greece
Dados Ligados (Linked Data) CONSEGI 2011Pablo Mendes
A Web é um espaço global de informações baseado na idéia de estabelecer hiperlinks entre documentos. De forma semelhante, tecnologias de Dados Ligados (Linked Data) permitem o estabelecimento de links entre registros em bancos de dados, interconectando estes bancos em um espaço global de dados. Tecnologias de Dados Ligados vem sendo adotadas por um número crescente de provedores de dados, resultando em aproximadamente 20 bilhões de ítens de dados que incluem dados sobre entidades governamentais e geográficas, pessoas, companhias, comunidades online, filmes, músicas, livros e publicações científicas. Pablo Mendes apresentou em sua palestra uma visão geral sobre infraestrutura, técnicas e software livre que abordam questões críticas que surgem em tal Web de Dados Ligados. Durante sua apresentação, ele descreveu como as pesquisas no grupo WBSG da Freie Universität Berlin vem usando conhecimento extraído da Wikipedia para semear um ecossistema de dados, software e usuários da Web de forma a habilitar integração de dados em escala global, seguindo um estilo evolucionário pay-as-you-go (link por link) que distribui esforços e acumula recompensas.
Uma das conclusões da apresentação é que se compartilharmos dados interligados - ou ainda melhor, se compartilharmos mecanismos de interligação - através da Web, poderemos dividir tanto o esforço de interligar, quanto as recompensas de se realizar consultas por sobre dados interligados.
Cuebee is a flexible, extensible application for querying the semantic web. It provides a friendly interface to guide users through the process of formulating complex queries. No technical knowledge of query languages or the semantic web is required.
They key enabler of the query builder is the ontology schema. The schema provides the types and possible interconnections of data to guide the user in creating a query.
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!
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
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.
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/
Enhancing Performance with Globus and the Science DMZGlobus
ESnet has led the way in helping national facilities—and many other institutions in the research community—configure Science DMZs and troubleshoot network issues to maximize data transfer performance. In this talk we will present a summary of approaches and tips for getting the most out of your network infrastructure using Globus Connect Server.
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
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.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...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.
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In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
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In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
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One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
DBpedia Spotlight at I-SEMANTICS 2011
1. DBpedia SpotlightShedding Light on the Web of Documents Pablo N. Mendes, Max Jakob, Andrés Garcia-Silva, Christian Bizer pablo.mendes@fu-berlin.de I-SEMANTICS, Graz, Austria September 9th 2011 1
2. Agenda What is text annotation? What can you build with it? Why is it difficult? How did we approach the challenge? How well did it work? What are the next steps? 2 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
4. Text Annotation From: To: (…) Upon their return, Lennon and McCartney went to New York to announce the formation of Apple Corps. (…) Upon their return, Lennon and McCartney went to New York to announce the formation of Apple Corps. http://dbpedia.org/resource/New_York_City http://dbpedia.org/resource/Apple_Corps 4 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
5. Challenge: Term Ambiguity 5 ...this apple on the palm of my hand... ...Apple tried to acquire Palm Inc.... ...eating an apple sitted by a palm tree... What do “apple” and “palm” mean in each case? Our objective is to recognize entities and disambiguate their meaning, generating DBpedia annotation in text. Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
6. What can you do with annotations? Links to complementary information “More about this” Faceted browsing of blog posts Show only posts with topics related to Sports Rich snippets on Google Search engines start to display info from annotations More expressive filtering of information streams Twarql (entry at I-SEMANTICS 2010 Challenge) 6 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
7. Rich Snippets Search Engines already benefit from some kinds of annotations 7 http://www.google.com/webmasters/tools/richsnippets Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
8. Twarql Example Use Case What competitors of my product are being mentioned with my product on Twitter? - comparative opinion! SELECT ? competitor WHERE { dbpedia:IPadskos:subject ?category . ?competitor skos:subject ?category . ?tweet moat:taggedWith ?competitor . } ?tweet moat:taggedWithdbpedia:Ipad . 8 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
9. Twarql Example Use Case (2) Incoming microposts… Background Knowledge (e.g. DBpedia) @anonymized Loremipsumblabla this is an example tweet dbpedia:IPad skos:subject ?category ?category ?competitor skos:subject skos:subject moat:taggedWith Competition is modeled as two products in the same category in DBpedia ?tweet 9 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
10. Twarql Example Use Case (3) Incoming microposts… Background Knowledge (e.g. DBpedia) @anonymized Loremipsumblabla this is an example tweet category:Wi-Fi dbpedia:IPad category:Touchscreen skos:subject ?category ?category ?competitor skos:subject skos:subject moat:taggedWith Background knowledge is dynamically “brought into” microposts. ?tweet 10 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
11. Twarql Example Use Case (4) Background Knowledge (e.g. DBpedia) @anonymized Loremipsumblabla this is an example tweet category:Wi-Fi dbpedia:IPad category:Touchscreen skos:subject ?category ?category ?competitor skos:subject skos:subject moat:taggedWith ?tweet Trigger action if micropost matches constraints. 11 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
12. DBpedia Spotlight DBpedia is a collection of entity descriptions extracted from Wikipedia & shared as linked data DBpedia Spotlight uses data from DBpedia and text from associated Wikipedia pages Learns how to recognize that a DBpedia resource was mentioned Given plain text as input, generates annotated text 12 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
14. Dataset overview Volume of Wikipedia 56,9 GB in raw text data Occurrences of Ambiguous Terms in Wikipedia: 58.8% Sparsity: less data for some DBpedia resources 14 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
15. Histogram: URI occurrences Many “rare” URIs, (few links on Wikipedia) Most of previous work deals with these entities: People, Organization, Location Few “popular” URIs (lots of links on Wikipedia) log(n(uri)))) 15 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
16. Histogram: Surface Form Ambiguity Many “unambiguous” surface forms Max: 1199 (log=7.08) Min: 1 Mean: 1.328949 Few very “ambiguous” surface forms log(n(uri,sf)))) 16 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
17. Ambiguity 17 What are the most ambiguous surface forms? Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
18. Name Variation 18 What are the URIs with many surface forms? Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
20. A 4-stage approach Spotting Candidate Mapping Disambiguation Linking 20 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
21. Stage 1: Spotting Find substrings that seem worthy of annotation Naïve implementation (impractical) all n-grams of length (1,|text|) Input: (…) Upon their return, Lennon and McCartney went to New York to announce the formation of Apple Corps. Output: “Lennon”, “McCartney”, “New York”, “Apple Corps” 21 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
22. Spotting in DBpedia Spotlight Detect that the label (surface form) of a DBpedia Resource was mentioned Lexicalized, Aho-Corasick algorithm (LingPipe) Name variations from redirects, disambiguation pages, anchor texts Advantages: Simple implementation, well studied problem, Produces a reduced set of spots, Relies on user provided terms. Drawback: high memory requirements (~7G) 22 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
23. Stage 2: Candidate Mapping What are the possible senses of a given surface form (the candidate DBpedia resources)? Input: “Lennon”, “McCartney”, “New York”, “Apple Corps” Output: “Lennon”: { Lennon_(album), Lennon,_Michigan, … } “McCartney”: { McCartney(surname), Paul_McCartney, … } “New York”: { New_York_State, New_York_City, … } “Apple Corps”: { Apple_Corps} 23 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
24. Candidate Mapping in DBpedia Spotlight Sources of mappings between surface forms and DBpedia Resources Page titles offer “chosen names” for resources Redirects offer alternative spellings, aliases, etc. Disambiguation Pages: link a common term to many resources 24 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
25. Candidate Map: Disambiguation Pages Collectively provide a list of ambiguous terms and meanings for each 25 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
26. Candidate Map: Redirects AAPL Apple (Company) Apple (Computers) Apple (company) Apple (computer) Apple Company Apple Computer Apple Computer Co. Apple Computer Inc. Apple Computer Incorporated Apple Computer, Inc Apple Computer, Inc. Apple Computers Apple Inc Apple Incorporate Apple Incorporated Apple India Apple comp Apple compputer Apple computer Apple computer Inc Apple computers Apple inc Apple inc. Apple incoporated Apple incorporated Apple pc Apple's Apple, Inc Apple, Inc. Apple,inc. Apple.com AppleComputer Bowman Bank Cripple Inc. Inc. Apple Computer Jobs and Wozniak Option-Shift-K Inc. 26 Apple_Inc Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
27. Stage 3: Disambiguation Select the correct candidate DBpedia Resource for a given surface form. Decision is made based on the context(1) the surface form was mentioned con·text (kntkst)n. 1. the parts of a discourse that surround a word or passage and can throw light on its meaning 2. The circumstances in which an event occurs; a setting. 27 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents http://mw1.merriam-webster.com/dictionary/context
28. Learning the Context for a resource Collect context for DBpedia Resources from Wikipedia Types of context Wikipedia Pages Definitions from disambiguation pages Paragraphs that link to resources 28 (…) Upon their return, Lennon and McCartney went to New York to announce the formation of Apple Corps. Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
29. Disambiguation in DBpedia Spotlight Model DBpedia Resources as vectors of terms found in Wikipedia text Define functions for term scoring and vector similarity (e.g. frequency and cosine) Rank candidate resource vectors based on their similarity with vector of input text Choose highest ranking candidate 29 Lennon = {Beatles,McCartney,rock,guitar,...} Lennon = {tf(Beatles)=320,tf(McCartney)=100,...} Cos(Input,Lennon) = 0.12 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
30. Scoring Strategies TF*IDF (Term Freq. * Inverse Doc. Freq.) TF: insight into the relevance of the term in the context of a DBpedia Resource IDF: insight into the rarity of the term. Co-occurrence of rare terms is more informative ICF: Inverse Candidate Frequency IDF is the “rarity” in the entire Wikipedia ICF is the rarity of a word with relation to the possible senses only 30 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
31. Context-Independent Strategies NAÏVE Use surface form to build URI: “berlin” -> dbpedia:Berlin PROMINENCE P(u): n(u) / N (what is the ‘popularity’/importance of this URL) n(u): number of times URI u occurred N: total number of occurrences Intuition: URIs that have appeared a lot are more likely to appear again DEFAULT SENSE P(u|s): n(u,s) / n(s) n(u,s): number of times URI u occurred with surface form s Intuition: some surface forms are strongly associated to some specific URIs 31 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
32. Linking (Configuration) Decide which spots to annotate with links to the disambiguated resources Different use cases have different needs Only annotate prominent resources? Only if you’re sure disambiguation is correct? Only people? Only things related to Berlin? 32 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
33. Linking in DBpedia Spotlight Can be configured based on: Thresholds Confidence Prominence (support) Whitelist or Blacklist of types Hide all people, Show only organizations Complex definition of a “type” through a SPARQL query. 33 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
35. Evaluation: Disambiguation Used held out (unseen) Wikipedia occurrences as test data Evaluates accuracy of disambiguation stage Baselines Random: performs well with low ambiguity Default Sense: only prominence, without context Default Similarity (TF*IDF) : Lucene implementation 35 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
37. Evaluation: Annotation News text, different topics Hand-annotated examples by 4 annotators Gold standard from agreement Evaluates precision and recall of annotations. 37 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
38. Annotation Evaluation Results (2) 38 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
39. Annotation Evaluation Results 39 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
40. Conclusions DBpedia Spotlight: a configurable annotation tool to support a variety of use cases Very simple methods work surprisingly well for disambiguation More work is needed to alleviate sparsity Most challenging step is linking More evaluation on larger annotation datasets is needed 40 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
42. A preview of next release CORS-enabled + jQuery client One line to annotate any web page: A new demo interface: based on the plugin Types: DBpedia 3.7, Freebase, Schema.org New configuration parameters E.g. perform smarter spotting Easier install: maven2, jar, debian package 42 $(“div”).annotate() Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
43. 43 Preview: Temporarily available for I-SEMANTICS 2011 http://spotlight.dbpedia.org/dev/demo Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
44. Future work Internationalization (German, Spanish,...) More sophisticated spotting New disambiguation strategies Global disambiguation: one disambiguation decision helps the other decisions Sparsity problems: try smoothing, dimensionality reduction, etc. Store user feedback, learn from mistakes 44 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
45. We are open Tell us about your use cases Hack something with us Drupal/Wordpress Plugin Semantic Media Wiki integration Are you a good engineer? Help us make it faster, smaller! Are you a good researcher? Let’s collaborate on your/our ideas. 45 Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents Licensed as Apache v2.0 (Business friendly)
46. Thank you! On Twitter: @pablomendes E-mail: pablo.mendes@fu-berlin.de Web: http://pablomendes.com Special thanks to Jo Daiber (working with us for the next release) Partially funded by LOD2.eu and Neofonie Gmbh 46 http://spotlight.dbpedia.org Mendes, Jakob, Garcia-Silva, Bizer. DBpedia Spotlight: Shedding Light on the Web of Documents
Editor's Notes
This use case requires merging streaming data with background knowledge information (e.g. from DBpedia). Examples of ?category include category:Wi-Fi devices and category:Touchscreen portable media players amongst others. As a result, without having to elicit all products of interest as keywords to lter a stream, a user is able to leverage relationships in background knowledge to more effectively narrow down the stream of tweets to a subset of interest.
This use case requires merging streaming data with background knowledge information (e.g. from DBpedia). Examples of ?category include category:Wi-Fi devices and category:Touchscreen portable media players amongst others. As a result, without having to elicit all products of interest as keywords to lter a stream, a user is able to leverage relationships in background knowledge to more effectively narrow down the stream of tweets to a subset of interest.
This use case requires merging streaming data with background knowledge information (e.g. from DBpedia). Examples of ?category include category:Wi-Fi devices and category:Touchscreen portable media players amongst others. As a result, without having to elicit all products of interest as keywords to lter a stream, a user is able to leverage relationships in background knowledge to more effectively narrow down the stream of tweets to a subset of interest.