Presentation at the International Workshop on Semantic Big Data (SBD 2016), held in conjunction with the 2016 ACM SIGMOD Conference in San Francisco, USA. Authored by Pieter Pauwels, Tarcisio Mendes de Farias, Chi Zhang, Ana Roxin, Jakob Beetz, Jos De Roo, Christophe Nicolle.
BabelNet Workshop 2016 - Making sense of building data and building product dataPieter Pauwels
Presentation at the 2016 BabelNet Workshop on 2 March 2016 IN Luxembourg (http://babelnet.org/lux): "Making sense of building data and building product data". Together with Thomas Krijnen (TUEindhoven) and Jakob Beetz (TUEindhoven). The paper is available at http://babelnet.org/lux/index.html#program_section.
ECPPM2016 - SimpleBIM: from full ifcOWL graphs to simplified building graphsPieter Pauwels
Presentation at the 11th European Conference on Product and Process Modelling (2016), in Limassol, Cyprus. Presentation and article are authored by Pieter Pauwels and Ana Roxin.
LOA seminar 2017 - Product and 3D geometry ontologies at action in constructi...Pieter Pauwels
Presentation given at the 2nd Workshop on Ontology and Engineering in Tandem, at LOA in Trento, Italy: Product and 3D geometry ontologies at action in construction industry: from manufacturer to demolition.
BuildingSMART Standards Summit 2015 - JBeetz - Product Room - Use Cases for i...Pieter Pauwels
Presentation held by Jakob Beetz at the BuildingSMART Standards Summit 2015 in Singapore. The presentation was made in the Product Room and aimed at investigating and discussing the relation between the Linked Data Working Group (LDWG) and the buildingSMART Data Dictionary (bSDD) Working Group.
Presentation about the current status of IFC2RDF tools for the Accelerating BIM workshop, held on October 2015 in Eindhoven (NL), collocated with the CIB W78 2015 conference.
BabelNet Workshop 2016 - Making sense of building data and building product dataPieter Pauwels
Presentation at the 2016 BabelNet Workshop on 2 March 2016 IN Luxembourg (http://babelnet.org/lux): "Making sense of building data and building product data". Together with Thomas Krijnen (TUEindhoven) and Jakob Beetz (TUEindhoven). The paper is available at http://babelnet.org/lux/index.html#program_section.
ECPPM2016 - SimpleBIM: from full ifcOWL graphs to simplified building graphsPieter Pauwels
Presentation at the 11th European Conference on Product and Process Modelling (2016), in Limassol, Cyprus. Presentation and article are authored by Pieter Pauwels and Ana Roxin.
LOA seminar 2017 - Product and 3D geometry ontologies at action in constructi...Pieter Pauwels
Presentation given at the 2nd Workshop on Ontology and Engineering in Tandem, at LOA in Trento, Italy: Product and 3D geometry ontologies at action in construction industry: from manufacturer to demolition.
BuildingSMART Standards Summit 2015 - JBeetz - Product Room - Use Cases for i...Pieter Pauwels
Presentation held by Jakob Beetz at the BuildingSMART Standards Summit 2015 in Singapore. The presentation was made in the Product Room and aimed at investigating and discussing the relation between the Linked Data Working Group (LDWG) and the buildingSMART Data Dictionary (bSDD) Working Group.
Presentation about the current status of IFC2RDF tools for the Accelerating BIM workshop, held on October 2015 in Eindhoven (NL), collocated with the CIB W78 2015 conference.
ECPPM2016 - SemCat: Publishing and Accessing Building Product Information as ...Pieter Pauwels
Presentation at the 11th European Conference on Product and Process Modelling (2016), in Limassol, Cyprus. Presentation and article are authored by Gudni Gundason and Pieter Pauwels.
BuildingSMART Standards Summit 2015 - Technical Room - Linked Data for Constr...Pieter Pauwels
Presentation at the Technical Room of the BuildingSMART Standards Summit October 2015 in Singapore. The presentation was done together with Jakob Beetz, TUEindhoven, with strong support by Walter Terkaj, ITIA-CNR, and Kris McGlinn, TCDublin. It is part of the SWIMing H2020 project, run by Kris McGlinn (http://swiming-project.eu/).
SWIMing VoCamp 2016 - ifcOWL overview and current statePieter Pauwels
Presentation at the 2016 SWIMing VoCamp on 22-23 March 2016 in Dublin (http://phaedrus.scss.tcd.ie/buildviz/workshop/vocamp/march2016/): "ifcOWL overview and current state".
CAA NLFL 2015 - Semantics in the documentation of architectural heritage: BIM...Pieter Pauwels
Presentation held at the CAA Netherlands-Flanders chapter meeting 2015 in Amsterdam - Computer Applications & Quantitative Methods in Archaeology.
More information: http://www.caanlfl.nl/
Google Cloud Platform (GCP) is one of the leaders among cloud APIs. It has gained notable expansion due to its suite of public cloud services that it based on a huge, solid infrastructure. GCP allows developers to use these services by accessing GCP RESTful API that is described through HTML pages on its website. However, the documentation of GCP API is written in natural language (English prose) and therefore shows several drawbacks, such as Informal Heterogeneous Documentation, Imprecise Types, Implicit Attribute Metadata, Hidden Links, Redundancy and Lack of Visual Support. To avoid confusion and misunderstandings, the cloud developers obviously need a precise specification of the knowledge and activities in GCP. Therefore, this paper introduces GCP MODEL, an inferred formal model-driven specification of GCP which describes without ambiguity the resources offered by GCP.
MoDMaCAO: Model-Driven Configuration Management of Cloud Applications with OC...Stéphanie Challita
To tackle the cloud-provider lock-in, the Open Grid Forum (OGF) is developing the Open Cloud Computing Interface (OCCI), a standardized interface for managing any kind of cloud resources. Besides the OCCI Core model, which defines the basic modeling elements for cloud resources, the OGF also defines extensions that reflect the requirements of different cloud service levels, such as IaaS and PaaS. However, so far the OCCI PaaS extension is very coarse grained and lacks of supporting use cases and implementations. Especially, it does not define how the components of the application itself can be managed. In this paper, we present a model-driven framework that extends the OCCI PaaS extension and is able to use different configuration management tools to manage the whole lifecycle of cloud applications. We demonstrate the feasibility of the approach by presenting four different use cases and prototypical implementations for three different configuration management tools.
HDF5 (with Nexus) is becoming the de facto standard in most X-ray facilities. However, it is not always easy to navigate such files to get quick feedback on the data, due to the peculiar structure of Nexus files. HDF5 file viewers are one way to solve this issue. They allow for the browsing and inspecting of the hierarchical structure of HDF5 files, as well as visualising the datasets they contain as basic plots (1D, 2D, 3D).
This presentation will focus on h5web, the open-source web-based viewer being developed at the European Synchrotron Radiation Facility. The intent is to provide synchrotron users with an easy-to-use application and to make open-source components available for other similar web applications. `h5web` is built with React, a front-end web development library. It supports the exploration of HDF5 files, requested from a separate back-end (e.g. HSDS) for modularity, and the visualisation of datasets using performant WebGL-based visualisations.
Overview of possible applications and benefits of virtual reality and augmented reality applications in logistics, created by the Virtual Dimension Center (VDC) in Fellbach.
Today, Google Cloud Platform (GCP) is one of the leaders among cloud APIs. Although it was established only five years ago, GCP has gained notable expansion due to its suite of public cloud services that it based on a huge, solid infrastructure. GCP allows developers to use these services by accessing GCP RESTful API that is described through HTML pages on its website. However, the documentation of GCP API is written in natural language (English prose) and therefore shows several drawbacks, such as Informal Heterogeneous Documentation, Imprecise Types, Implicit Attribute Metadata, Hidden Links, Redundancy and Lack of Visual Support. To avoid confusion and misunderstandings, the cloud developers obviously need a precise specification of the knowledge and activities in GCP. Therefore, this paper introduces GCP MODEL, an inferred formal model-driven specification of GCP which describes without ambiguity the resources offered by GCP. GCP MODEL conforms to the Open Cloud Computing Interface (OCCI) metamodel and is implemented based on the open source model-driven Eclipse-based OCCIWARE tool chain. Thanks to our GCP MODEL, we offer corrections to the drawbacks we identified.
A talk presented at PGCon 2015.
This talk presents principles of designing performance evaluations and shows how you can put them into practice by introducing the speaker's experiences of performance evaluations with database and storage systems.
See also: http://www.pgcon.org/2015/schedule/events/821.en.html
ECPPM2016 - SemCat: Publishing and Accessing Building Product Information as ...Pieter Pauwels
Presentation at the 11th European Conference on Product and Process Modelling (2016), in Limassol, Cyprus. Presentation and article are authored by Gudni Gundason and Pieter Pauwels.
BuildingSMART Standards Summit 2015 - Technical Room - Linked Data for Constr...Pieter Pauwels
Presentation at the Technical Room of the BuildingSMART Standards Summit October 2015 in Singapore. The presentation was done together with Jakob Beetz, TUEindhoven, with strong support by Walter Terkaj, ITIA-CNR, and Kris McGlinn, TCDublin. It is part of the SWIMing H2020 project, run by Kris McGlinn (http://swiming-project.eu/).
SWIMing VoCamp 2016 - ifcOWL overview and current statePieter Pauwels
Presentation at the 2016 SWIMing VoCamp on 22-23 March 2016 in Dublin (http://phaedrus.scss.tcd.ie/buildviz/workshop/vocamp/march2016/): "ifcOWL overview and current state".
CAA NLFL 2015 - Semantics in the documentation of architectural heritage: BIM...Pieter Pauwels
Presentation held at the CAA Netherlands-Flanders chapter meeting 2015 in Amsterdam - Computer Applications & Quantitative Methods in Archaeology.
More information: http://www.caanlfl.nl/
Google Cloud Platform (GCP) is one of the leaders among cloud APIs. It has gained notable expansion due to its suite of public cloud services that it based on a huge, solid infrastructure. GCP allows developers to use these services by accessing GCP RESTful API that is described through HTML pages on its website. However, the documentation of GCP API is written in natural language (English prose) and therefore shows several drawbacks, such as Informal Heterogeneous Documentation, Imprecise Types, Implicit Attribute Metadata, Hidden Links, Redundancy and Lack of Visual Support. To avoid confusion and misunderstandings, the cloud developers obviously need a precise specification of the knowledge and activities in GCP. Therefore, this paper introduces GCP MODEL, an inferred formal model-driven specification of GCP which describes without ambiguity the resources offered by GCP.
MoDMaCAO: Model-Driven Configuration Management of Cloud Applications with OC...Stéphanie Challita
To tackle the cloud-provider lock-in, the Open Grid Forum (OGF) is developing the Open Cloud Computing Interface (OCCI), a standardized interface for managing any kind of cloud resources. Besides the OCCI Core model, which defines the basic modeling elements for cloud resources, the OGF also defines extensions that reflect the requirements of different cloud service levels, such as IaaS and PaaS. However, so far the OCCI PaaS extension is very coarse grained and lacks of supporting use cases and implementations. Especially, it does not define how the components of the application itself can be managed. In this paper, we present a model-driven framework that extends the OCCI PaaS extension and is able to use different configuration management tools to manage the whole lifecycle of cloud applications. We demonstrate the feasibility of the approach by presenting four different use cases and prototypical implementations for three different configuration management tools.
HDF5 (with Nexus) is becoming the de facto standard in most X-ray facilities. However, it is not always easy to navigate such files to get quick feedback on the data, due to the peculiar structure of Nexus files. HDF5 file viewers are one way to solve this issue. They allow for the browsing and inspecting of the hierarchical structure of HDF5 files, as well as visualising the datasets they contain as basic plots (1D, 2D, 3D).
This presentation will focus on h5web, the open-source web-based viewer being developed at the European Synchrotron Radiation Facility. The intent is to provide synchrotron users with an easy-to-use application and to make open-source components available for other similar web applications. `h5web` is built with React, a front-end web development library. It supports the exploration of HDF5 files, requested from a separate back-end (e.g. HSDS) for modularity, and the visualisation of datasets using performant WebGL-based visualisations.
Overview of possible applications and benefits of virtual reality and augmented reality applications in logistics, created by the Virtual Dimension Center (VDC) in Fellbach.
Today, Google Cloud Platform (GCP) is one of the leaders among cloud APIs. Although it was established only five years ago, GCP has gained notable expansion due to its suite of public cloud services that it based on a huge, solid infrastructure. GCP allows developers to use these services by accessing GCP RESTful API that is described through HTML pages on its website. However, the documentation of GCP API is written in natural language (English prose) and therefore shows several drawbacks, such as Informal Heterogeneous Documentation, Imprecise Types, Implicit Attribute Metadata, Hidden Links, Redundancy and Lack of Visual Support. To avoid confusion and misunderstandings, the cloud developers obviously need a precise specification of the knowledge and activities in GCP. Therefore, this paper introduces GCP MODEL, an inferred formal model-driven specification of GCP which describes without ambiguity the resources offered by GCP. GCP MODEL conforms to the Open Cloud Computing Interface (OCCI) metamodel and is implemented based on the open source model-driven Eclipse-based OCCIWARE tool chain. Thanks to our GCP MODEL, we offer corrections to the drawbacks we identified.
A talk presented at PGCon 2015.
This talk presents principles of designing performance evaluations and shows how you can put them into practice by introducing the speaker's experiences of performance evaluations with database and storage systems.
See also: http://www.pgcon.org/2015/schedule/events/821.en.html
CIB W78 2015 - Keynote "The Web of Construction Data:Pathways and Opportunities"Pieter Pauwels
Keynote presentation for the 32nd CIB W78 conference in Eindhoven (2015): "The Web of Construction Data:Pathways and Opportunities". With many thanks to the researchers who are referenced throughout the presentation.
http://cib-w78-2015.bwk.tue.nl/
LDAC 2015 - Towards an industry-wide ifcOWL: choices and issuesPieter Pauwels
Presentation at LDAC 2015 (http://ldac-2015.bwk.tue.nl/) in Eindhoven, together with Maria Poveda-Villalon (UPMadrid): Towards an industry-wide ifcOWL: choices and issues.
LDAC 2015 - Selection of IFC subsets using ifcOWL and rewrite rulesPieter Pauwels
Presentation at LDAC2015 Eindhoven (http://ldac-2015.bwk.tue.nl), together with Matthias Weise (AEC3): Selection of IFC subsets using ifcOWL and rewrite rules.
Querying and reasoning over large scale building datasets: an outline of a pe...Ana Roxin
Presented at the International Workshop on Semantic Big Data (SBD 2016), held in conjunction with the 2016 ACM SIGMOD Conference
July 1st, 2016, San Francisco, USA
Tiny Batches, in the wine: Shiny New Bits in Spark StreamingPaco Nathan
London Spark Meetup 2014-11-11 @Skimlinks
http://www.meetup.com/Spark-London/events/217362972/
To paraphrase the immortal crooner Don Ho: "Tiny Batches, in the wine, make me happy, make me feel fine." http://youtu.be/mlCiDEXuxxA
Apache Spark provides support for streaming use cases, such as real-time analytics on log files, by leveraging a model called discretized streams (D-Streams). These "micro batch" computations operated on small time intervals, generally from 500 milliseconds up. One major innovation of Spark Streaming is that it leverages a unified engine. In other words, the same business logic can be used across multiple uses cases: streaming, but also interactive, iterative, machine learning, etc.
This talk will compare case studies for production deployments of Spark Streaming, emerging design patterns for integration with popular complementary OSS frameworks, plus some of the more advanced features such as approximation algorithms, and take a look at what's ahead — including the new Python support for Spark Streaming that will be in the upcoming 1.2 release.
Also, let's chat a bit about the new Databricks + O'Reilly developer certification for Apache Spark…
ifcWOD (Web Of Data) - Semantically Adapting IFC Model Relations into OWL Pro...Ana Roxin
Presented at the Technical Room, at the buildingSMART Summit
12th April 2016, Rotterdam, The Netherlands
Describes the semi-automatical conception of the ifcWOD ontology, based on the IFC EXPRESS model, ifcOWL and IFC Property Set Definitions (PSD)
Ontology-based data access: why it is so cool!Josef Hardi
A brief introduction about ontology-based data access (shortly OBDA) and its core implementation. I presented too a recent simple benchmark between -ontop- and Semantika---two most available software for OBDA framework---in term of query performance (including details in the appendix section). The slides were presented for Friday Research Meeting in Stanford Center for Biomedical Informatics Research (BMIR).
License: Creative Commons by Attribution 3.0
WSO2 Machine Learner takes data one step further, pairing data gathering and analytics with predictive intelligence: this helps you understand not just the present, but to predict scenarios and generate solutions for the future.
Telefonica: Automatización de la gestión de redes mediante grafosNeo4j
David Blanco, Global OSS Architecture, Telefonica
La complejidad de las redes de comunicaciones se ha incrementado de forma exponencial en los últimos años con la aparición de nuevas tecnologías (5G, IoT, Virtualización, AI/ML …) que permiten ofrecer nuevos productos y servicios a los consumidores. Para una operación eficiente de esta complejidad es necesario disponer de sistemas que automaticen la gestión de su Ciclo de Vida. Los sistemas basados en grafos facilitan esta automatización.
In this talk, we’ll discuss technical designs of support of HBase as a “native” data source to Spark SQL to achieve both query and load performance and scalability: near-precise execution locality of query and loading, fine-tuned partition pruning, predicate pushdown, plan execution through coprocessor, and optimized and fully parallelized bulk loader. Point and range queries on dimensional attributes will benefit particularly well from the techniques. Preliminary test results vs. established SQL-on-HBase technologies will be provided. The speaker will also share the future plan and real-world use cases, particularly in the telecom industry.
Testistanbul 2016 - Keynote: "Performance Testing of Big Data" by Roland LeusdenTurkish Testing Board
Agile, Continous Intergration, DevOps, Big data are not longer buzzwords but part of the day today process of everyone working in software development and delivery. To cope with applications that need to be deployed in production almost the same moment they were created, software development has changed, impacting the way of working for everyone in the team. In this talk, Roland will discuss the challenges performance testers face with Big Data applications and how Architecture, Agile, Continous Intergration and DevOps come together to create solutions.
Similar to ACM SIGMOD SBD2016 - Querying and reasoning over large scale building datasets: an outline of a performance benchmark (20)
CAADFutures 2015 - Shape grammars for architectural design: the need for refr...Pieter Pauwels
Presentation at CAADFutures 2015, in Sao Paulo: http://caadfutures2015.fec.unicamp.br/. The paper is available at http://link.springer.com/chapter/10.1007/978-3-662-47386-3_28.
Summer School LD4SC 2015 - ifcOWL introductionPieter Pauwels
Presentation about ifcOWL at the Summer School on Linked Data 4 Smart Cities, in Cercedilla (2015): http://smartcity.linkeddata.es/LD4SC/, organised by the Ontology Engineering Group of Universidad Politécnica de Madrid.
Summer School LD4SC 2015 - RDF(S) and SPARQLPieter Pauwels
Presentation about RDF(S) and SPARQL at the Summer School on Linked Data 4 Smart Cities, in Cercedilla (2015): http://smartcity.linkeddata.es/LD4SC/, organised by the Ontology Engineering Group of Universidad Politécnica de Madrid.
EuropIA 2014 - Analysing the impact of constraints on decision-making by arch...Pieter Pauwels
Architectural design projects are characterised by a high level of complexity. This level of complexity may be attributed to the high number of constraints that apply to architectural design projects. Along with planning, energy performance and fire safety regulations, current designers have to face constraining factors related to budget, acoustics, orientation, wind turbulence, accessibility for the disabled, and so forth. It thus appears that all sorts of restrictions and regulations steer the design process implicitly and explicitly in certain directions as soon as architectural designers aim at satisfying design briefs.
In this research, we aim at analysing the impact of parameters and constraints on the design process. We wish to investigate how designers in practice deal with parameters and constraints. How do they interpret incoming parameters or constraints? Are constraints considered to be limitative (constraining), or are they key reference points in a variety of parametric possibilities? Are constraints omnipresent during the design process or are they considered only until they have been 'resolved'? To make an analysis of the role of constraints and parameters in the design process, we have studied four design sessions in a particular design use case, which will be presented briefly in this paper. In each of these design sessions, the design was not only re-evaluated, but it was also redirected in response to certain constraints that were not met (yet). In analysing these four sessions, we used linkography as a method, because this appeared to be one of the better options to obtain a more quantitative assessment of the design process. The linkography method was combined with an interview of the student design team, in order to check the correctness of our conclusions.
NordDesign2014 - Reasoning processes involved in ICT-mediated design communic...Pieter Pauwels
Conversational interaction is central to architectural design practice. New information and communication technologies (ICT) change the designer’s traditional way of communicating and interacting. In this paper we investigate how communication in the design process might be supported using ICT. With this aim, we study a text-based Skype conversation between a design teacher and a design student. We consider this conversation as part of an architectural design process and analyse it using linkography. From the linkograph analysis, specific features are identified that apply specifically to text-based Skype interactions. We conclude that online text-based Skype interaction can be one of the many possible interactions by means of communication media (sketching, conversation, modelling, and so forth) during the design process, and provides a distinct set of characteristics that might be considered by the designer.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
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/
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
ACM SIGMOD SBD2016 - Querying and reasoning over large scale building datasets: an outline of a performance benchmark
1. AnaROXIN–ana-maria.roxin@u-bourgogne.fr
PieterPAUWELS–Pieter.pauwels@ugent.be
Querying and reasoning over
large scale building datasets: an outline of
a performance benchmark
Pieter Pauwels, Tarcisio Mendes deFarias, ChiZhang, Ana Roxin, Jakob Beetz, Jos De Roo,
Christophe Nicolle
International Workshop on Semantic Big Data (SBD 2016)
in conjunction with the 2016 ACM SIGMOD Conference in San Francisco, USA
3. AnaROXIN–ana-maria.roxin@u-bourgogne.fr
PieterPAUWELS–Pieter.pauwels@ugent.be
Context description
◼ The architecturaldesign andconstructiondomainsworkonadailybasis withmassiveamountsof
data.
◼ In the contextofBIM, aneutral,interoperablerepresentationofinformationconsistsin the Industry
FoundationClasses(IFC) standard
Difficult to handlethe EXPRESS format
◼ SemanticWebtechnologies havebeen identifiedas apossible solution
Semantic data enrichment
Schema and data transformations
◼ A semanticapproachinvolves 3 maincomponents:
Schema (Tbox)
• OWL ontology
• Informationstructure
Instances (ABox)
• Assertions
• Respectsschema definition
Rules(RBox)
• If-Thenstatements
• Involving elementsfrom the
ABoxandtheTBox
Queryingand reasoningover large scale buildingdatasets: anoutline of a performancebenchmark
3
July1st, 2016
4. AnaROXIN–ana-maria.roxin@u-bourgogne.fr
PieterPAUWELS–Pieter.pauwels@ugent.be
Problem identified
◼ Differentimplementationsexist forthecomponents(TBox,ABox,RBox)ofsuch Semanticapproach
Diverse reasoning engines
Diverse queryprocessing techniques
Diverse queryhandling
Diverse dataset size
Diverse dataset complexity
◼ Missing anappropriaterule andqueryexecutionperformancebenchmark
Expressiveness vs.
performance
Queryingand reasoningover large scale buildingdatasets: anoutline of a performancebenchmark
4
July1st, 2016
5. AnaROXIN–ana-maria.roxin@u-bourgogne.fr
PieterPAUWELS–Pieter.pauwels@ugent.be
Performance benchmark variables
◼ Main components
◼ Theseelements areimplemented into3differentsystems
SPIN(SPARQL InferenceNotation) and Jena
EYE
Stardog
◼ An ensemble ofqueries isaddressedtotheso-createdsystems
Schema
(TBox)
• ifcOWL
Instances(ABox)
• 369ifcOWL-
compliantbuilding
models
Rules
(RBox)
• 68 data
transformationrules
Queryingand reasoningover large scale buildingdatasets: anoutline of a performancebenchmark
5
July1st, 2016
6. AnaROXIN–ana-maria.roxin@u-bourgogne.fr
PieterPAUWELS–Pieter.pauwels@ugent.be
TBox - the ifcOWL ontology
◼ All building modelsareencoded usingtheifcOWLontology
Built up underthe impulse of numerousinitiatives during the last 10years
◼ The ontologyused isthe onethatis madepublicly availablebythe buildingSMARTLinked Data
Working Group(LDWG)
http://ifcowl.openbimstandards.org/IFC4#
http://ifcowl.openbimstandards.org/IFC4_ADD1#
http://ifcowl.openbimstandards.org/IFC2X3_TC1#
http://ifcowl.openbimstandards.org/IFC2X3_Final#
Queryingand reasoningover large scale buildingdatasets: anoutline of a performancebenchmark
6
July1st, 2016
7. AnaROXIN–ana-maria.roxin@u-bourgogne.fr
PieterPAUWELS–Pieter.pauwels@ugent.be
ifcOWL Stats
July1st, 2016 Queryingand reasoningover large scale buildingdatasets: anoutline of a performancebenchmark
7
Axioms 21306
Logical Axioms 13649
Classes 1230
Object properties 1578
Data properties 5
Individuals 1627
DL expressivity SROIQ(D)
SubClassOf axioms 4622
EquivalentClasses axioms 266
DisjointClasses axioms 2429
SubObjectPropertyOf axioms 1
InverseObjectProperties axioms 94
FunctionalObjectProperty axioms 1441
TransitiveObjectProperty axioms 1
ObjectPropertyDomain axioms 1577
ObjectPropertyRange axioms 1576
FunctionalDataProperty axioms 5
DataPropertyDomain axioms 5
DataPropertyRange axioms 5
Pieter Pauwels and Walter Terkaj, EXPRESS to OWL for
construction industry: towards a recommendable and usable
ifcOWL ontology. Automation in Construction 63: 100-133 (2016).
8. AnaROXIN–ana-maria.roxin@u-bourgogne.fr
PieterPAUWELS–Pieter.pauwels@ugent.be
Call for papers – special issue in SWJ
◼ SemanticWebJournal– Interoperability,Usability,Applicability
http://www.semantic-web-journal.net
◼ Specialissue on"SemanticTechnologies andInteroperability intheBuilt Environment"
◼ Importantdates
March, 1st 2017– paper submission deadline
May 1st 2017– notification of acceptance
OntologiesforAEC/FM
LinkingBIM modelsto
externaldatasources
Multiplescaleintegration
throughsemanitc
interoperability
Multilingualdataaccess
andannotation
Queryprocessing,query
performance
Semantic-basedbuilding
monitoringsystems
Reasoningwithbuilding
data
Buildingdatapublication
strategies
BigLinkedDatafor
buildinginformation
Queryingand reasoningover large scale buildingdatasets: anoutline of a performancebenchmark
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July1st, 2016
12. AnaROXIN–ana-maria.roxin@u-bourgogne.fr
PieterPAUWELS–Pieter.pauwels@ugent.be
Implementation
• Implementedbased ontheopen source APIs
of Topbraid SPIN(SPIN API 1.4.0)and Apache
Jena (Jena Core 2.11.0,Jena ARQ2.11.0,Jena
TDB 1.0.0)
• Rulesare writtenwith TopbraidComposer
Freeversion,and theyare exportedas RDF
Turtlefiles.
• A smallJava program isimplementedto read
RDF models,schema,rulesfrom the TDB store
and query data.
• AlltheSPARQLqueriesareconfigured using
theJena org.apache.jena.sparql.algebra
package
• To avoid unnecessaryreasoningprocesses,in
thistestenvironment onlythe RDFS
vocabulary issupported.
SPIN+ JenaTDB
• Version‘EYE-Winter16.0302.1557’(‘SWI-
Prolog 7.2.3 (amd64):Aug 252015,
12:24:59’).
• EYE isa semi-backwardreasonerenhanced
with Eulerpath detection.
• Asour rulesetcurrently containsonly rules
using=>, forward reasoningwilltake place.
• Each command is executed5 times
• Each command includesthefullontology, the
fullsetof rulesand theRDFS vocabulary, as
wellasone of the 369buildingmodel filesand
one of the3 query files.
• Notriplestoreisused:triplesare processed
directlyfrom theconsideredfiles.
EYE
• 4.0.2Stardogsemanticgraphdatabase(Java 8,
RDF 1.1graph datamodel, OWL2profiles,
SPARQL1.1)
• OWL reasoner+rule engine.
• Support of SWRLrules,backward-chaining
reasoning
• Reasoningis performedby applyinga query
rewritingapproach (SWRLrulesare taken into
account during thequery rewritingprocess).
• Stardogallowsattaininga DL-expressivity
levelof SROIQ(D).
• Inthisapproach, SWRLrulesare taken into
account during thequery rewritingprocess.
Stardog
Queryingand reasoningover large scale buildingdatasets: anoutline of a performancebenchmark
12
July1st, 2016
13. AnaROXIN–ana-maria.roxin@u-bourgogne.fr
PieterPAUWELS–Pieter.pauwels@ugent.be
Queries
◼ We have builta limited listof60 queries,eachofwhichtriggersatleast oneof theavailablerules.
◼ As we focushereon queryexecutionperformance,the consideredqueriesareentirelybasedon the
right-handsides ofthe consideredrules.
◼ 3 queries:
Q1 a simple querywith little results,
Q2 a simple querywith manyresults,
and Q3 a complex querythat triggers a considerable numberof rules
Query Query Contents
Q1 ?obj sbd:hasProperty ?p
Q2
?point sbd:hasCoordinateX ?x .
?point sbd:hasCoordinateY ?y .
?point sbd:hasCoordinateZ ?z
Q3 ?d rdf:type sbd:ExternalWall
Queryingand reasoningover large scale buildingdatasets: anoutline of a performancebenchmark
13
July1st, 2016
14. AnaROXIN–ana-maria.roxin@u-bourgogne.fr
PieterPAUWELS–Pieter.pauwels@ugent.be
Test environment
◼ In onecentralserver
Supplied by the Universityof Burgundy,researchgroup CheckSem,
Following specifications: UbuntuOS, Intel Xeon CPU E5-2430at 2.2GHz,6 coresand 16GB of DDR3
RAMmemory
◼ 3 VirtualMachines(VMs) wereset up in thiscentralserver
SPIN VM (Jena TDB), EYE VM(EYE inferenceengine), Stardog VM(Stardog triplestore)
◼ The VMsweremanagedas separatetestenvironments and
Each of these VMs had 2 coresout of 6 allocated
Each containedthe above resources (ontologies, data, rules, queries).
Queryingand reasoningover large scale buildingdatasets: anoutline of a performancebenchmark
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July1st, 2016
15. AnaROXIN–ana-maria.roxin@u-bourgogne.fr
PieterPAUWELS–Pieter.pauwels@ugent.be
Results
◼ Queriesappliedon 6hand-picked
building models ofvaryingsize
◼ In theSPINapproach
For Q1 and Q2, the execution time =
backward-chaininginference process +
actual query execution time
For Q3, execution time = queryexecution
time itself
◼ In the EYEapproach
Networktraffic time is ignored
◼ In the Stardogapproach
Execution time = backward-chaining
inference+ actual queryexecution time
Query
Building
Model
SPIN
(s)
EYE
(s)
Stardog(s)
Q1
(simple,little
results)
BM1 135,36 37,11 13,44
BM2 1,47 0,29 0,17
BM3 24,01 4,87 1,4
BM4 41,28 12,95 3,55
BM5 4,99 1,05 0,33
BM6 0,55 0,16 0,08
Q2
(simple,many
results)
BM1 46,17 2,10 6,82
BM2 92,03 4,20 15,83
BM3 82,68 4,12 15,28
BM4 19,93 1,04 2,81
BM5 3,69 0,21 1,36
BM6 0,74 0,045 1,00
Q3
(complex)
BM1 0,001 0,001 0,07
BM2 0,006 0,003 0,12
BM3 0,002 0,003 0,31
BM4 0,005 0,001 0,20
BM5 0,006 0,013 0,20
BM6 0,001 0,001 0,13
Queryingand reasoningover large scale buildingdatasets: anoutline of a performancebenchmark
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July1st, 2016
16. AnaROXIN–ana-maria.roxin@u-bourgogne.fr
PieterPAUWELS–Pieter.pauwels@ugent.be
Query time related to result count
For Q1 for each of the considered
approaches
(green = SPIN; blue = EYE; black = Stardog)
For Q2 for each of the considered
approaches
(green = SPIN; blue = EYE; black = Stardog)
Queryingand reasoningover large scale buildingdatasets: anoutline of a performancebenchmark
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July1st, 2016
17. AnaROXIN–ana-maria.roxin@u-bourgogne.fr
PieterPAUWELS–Pieter.pauwels@ugent.be
Additional findings
• The three considered procedures arequite farapartfrom each other, explaining the considerable performance differences, not only between the
procedures, but alsobetween diverse usages within one and the samesystem.
• Algorithms and optimization techniques used for each approach aren't entirely used: differences in indexation algorithms, query rewriting techniques
and rule handling strategies used.
Indexing algorithms, query rewriting techniques, and rule handling strategies
• The disadvantage of forward-chaining reasoning process is that millions of triples can bematerialized (EYE, SPIN forQ1 and Q2)
• Using backward-chaining reasoning allows avoiding triple materialization, thus saving query execution time (Stardog, SPIN forQ3).
Forward- versus backward-chaining
• Query Q3 triggers a rule that in turn triggers several other rules in the rule set. If the firstrule does not fire, however, the process stops early.
• Query Q2, however, fires relatively long rules. It takes more time to make these matches in all three approaches.
Typeof data in the building model
• Loading files in memory at query execution time leads to considerable delays.
Impact of the triple store
• Linear relation: the more results areavailable, the more triples need to bematched, leading to more assertions.
Impact of the number of output results
Queryingand reasoningover large scale buildingdatasets: anoutline of a performancebenchmark
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July1st, 2016
18. AnaROXIN–ana-maria.roxin@u-bourgogne.fr
PieterPAUWELS–Pieter.pauwels@ugent.be
Conclusion and future work
◼ Comparisonof3 differentapproaches
SPIN, EYE andStardog
◼ 3 queriesappliedover 6 differentbuilding models
◼ Futureworkconsistsin
Specifying morethis initial performancebenchmarkwith additional data and rules
Executing additional queries on the rest of the set of building models
Comparingresults ona wider scale:
―forthe individual approaches separately,
―as well as with other approaches not considered here.
Queryingand reasoningover large scale buildingdatasets: anoutline of a performancebenchmark
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July1st, 2016
Depending on the rules that are being triggered, one set of information then has the potential to be made available in a diverse number of forms,
bringing an entirely new form of interoperability for an industry
that has always relied heavily on the combination of an agreed standard with many intransparent import and export procedures that were implemented using procedural programming languages.