Enterprise knowledge graphs use semantic technologies like RDF, RDF Schema, and OWL to represent knowledge as a graph consisting of concepts, classes, properties, relationships, and entity descriptions. They address the "variety" aspect of big data by facilitating integration of heterogeneous data sources using a common data model. Key benefits include providing background knowledge for various applications and enabling intra-organizational data sharing through semantic integration. Challenges include ensuring data quality, coherence, and managing updates across the knowledge graph.
Linked data for Enterprise Data IntegrationSören Auer
The Web evolves into a Web of Data. In parallel Intranets of large companies will evolve into Data Intranets based on the Linked Data principles. Linked Data has the potential to complement the SOA paradigm with a light-weight, adaptive data integration approach.
Towards digitizing scholarly communicationSören Auer
Slides of the VIVO 2016 Conference keynote: Despite the availability of ubiquitous connectivity and information technology, scholarly communication has not changed much in the last hundred years: research findings are still encoded in and decoded from linear, static articles and the possibilities of digitization are rarely used. In this talk, we will discuss strategies for digitizing scholarly communication. This comprises in particular: the use of machine-readable, dynamic content; the description and interlinking of research artifacts using Linked Data; the crowd-sourcing of multilingual
educational and learning content. We discuss the relation of these developments to research information systems and how they could become part of an open ecosystem for scholarly communication.
Introduction to the Data Web, DBpedia and the Life-cycle of Linked DataSören Auer
Over the past 4 years, the Semantic Web activity has gained momentum with the widespread publishing of structured data as RDF. The Linked Data paradigm has therefore evolved from a practical research idea into
a very promising candidate for addressing one of the biggest challenges
of computer science: the exploitation of the Web as a platform for data
and information integration. To translate this initial success into a
world-scale reality, a number of research challenges need to be
addressed: the performance gap between relational and RDF data
management has to be closed, coherence and quality of data published on
the Web have to be improved, provenance and trust on the Linked Data Web
must be established and generally the entrance barrier for data
publishers and users has to be lowered. This tutorial will discuss
approaches for tackling these challenges. As an example of a successful
Linked Data project we will present DBpedia, which leverages Wikipedia
by extracting structured information and by making this information
freely accessible on the Web. The tutorial will also outline some recent advances in DBpedia, such as the mappings Wiki, DBpedia Live as well as
the recently launched DBpedia benchmark.
Towards an Open Research Knowledge GraphSören Auer
The document-oriented workflows in science have reached (or already exceeded) the limits of adequacy as highlighted for example by recent discussions on the increasing proliferation of scientific literature and the reproducibility crisis. Now it is possible to rethink this dominant paradigm of document-centered knowledge exchange and transform it into knowledge-based information flows by representing and expressing knowledge through semantically rich, interlinked knowledge graphs. The core of the establishment of knowledge-based information flows is the creation and evolution of information models for the establishment of a common understanding of data and information between the various stakeholders as well as the integration of these technologies into the infrastructure and processes of search and knowledge exchange in the research library of the future. By integrating these information models into existing and new research infrastructure services, the information structures that are currently still implicit and deeply hidden in documents can be made explicit and directly usable. This has the potential to revolutionize scientific work because information and research results can be seamlessly interlinked with each other and better mapped to complex information needs. Also research results become directly comparable and easier to reuse.
Slides of my talk at OSLCfest in Stockholm Nov 6, 2019
Video recording of the talk is available here:
https://www.facebook.com/oslcfest/videos/2261640397437958/
Linked data for Enterprise Data IntegrationSören Auer
The Web evolves into a Web of Data. In parallel Intranets of large companies will evolve into Data Intranets based on the Linked Data principles. Linked Data has the potential to complement the SOA paradigm with a light-weight, adaptive data integration approach.
Towards digitizing scholarly communicationSören Auer
Slides of the VIVO 2016 Conference keynote: Despite the availability of ubiquitous connectivity and information technology, scholarly communication has not changed much in the last hundred years: research findings are still encoded in and decoded from linear, static articles and the possibilities of digitization are rarely used. In this talk, we will discuss strategies for digitizing scholarly communication. This comprises in particular: the use of machine-readable, dynamic content; the description and interlinking of research artifacts using Linked Data; the crowd-sourcing of multilingual
educational and learning content. We discuss the relation of these developments to research information systems and how they could become part of an open ecosystem for scholarly communication.
Introduction to the Data Web, DBpedia and the Life-cycle of Linked DataSören Auer
Over the past 4 years, the Semantic Web activity has gained momentum with the widespread publishing of structured data as RDF. The Linked Data paradigm has therefore evolved from a practical research idea into
a very promising candidate for addressing one of the biggest challenges
of computer science: the exploitation of the Web as a platform for data
and information integration. To translate this initial success into a
world-scale reality, a number of research challenges need to be
addressed: the performance gap between relational and RDF data
management has to be closed, coherence and quality of data published on
the Web have to be improved, provenance and trust on the Linked Data Web
must be established and generally the entrance barrier for data
publishers and users has to be lowered. This tutorial will discuss
approaches for tackling these challenges. As an example of a successful
Linked Data project we will present DBpedia, which leverages Wikipedia
by extracting structured information and by making this information
freely accessible on the Web. The tutorial will also outline some recent advances in DBpedia, such as the mappings Wiki, DBpedia Live as well as
the recently launched DBpedia benchmark.
Towards an Open Research Knowledge GraphSören Auer
The document-oriented workflows in science have reached (or already exceeded) the limits of adequacy as highlighted for example by recent discussions on the increasing proliferation of scientific literature and the reproducibility crisis. Now it is possible to rethink this dominant paradigm of document-centered knowledge exchange and transform it into knowledge-based information flows by representing and expressing knowledge through semantically rich, interlinked knowledge graphs. The core of the establishment of knowledge-based information flows is the creation and evolution of information models for the establishment of a common understanding of data and information between the various stakeholders as well as the integration of these technologies into the infrastructure and processes of search and knowledge exchange in the research library of the future. By integrating these information models into existing and new research infrastructure services, the information structures that are currently still implicit and deeply hidden in documents can be made explicit and directly usable. This has the potential to revolutionize scientific work because information and research results can be seamlessly interlinked with each other and better mapped to complex information needs. Also research results become directly comparable and easier to reuse.
Slides of my talk at OSLCfest in Stockholm Nov 6, 2019
Video recording of the talk is available here:
https://www.facebook.com/oslcfest/videos/2261640397437958/
The Bounties of Semantic Data Integration for the Enterprise Ontotext
If you are looking for solutions that allow you not only to manage all of your data (structured, semi-structured and unstructured) but to also make the most out of them, using a common language is critical.
Adding Semantic Technology to data integration is the glue that holds together all your enterprise data and their relationships in a meaningful way.
Learn how you can quickly design data processing jobs and integrate massive amounts of data and see what semantic integration can do for your data and your business.
www.ontotext.com
Linking Open, Big Data Using Semantic Web Technologies - An IntroductionRonald Ashri
The Physics Department of the University of Cagliari and the Linkalab Group invited me to talk about the Semantic Web and Linked Data - this is simply an introduction to the technologies involved.
Using the Semantic Web Stack to Make Big Data SmarterMatheus Mota
This presentation will discuss how just a few parts of the Semantic Web Cake can already boost your analytics by making your (big) data smarter and even more connected.
This invited keynote at the Social Computing Track at WI-IAT21 gives an introduction to Knowledge Graphs and how they are built collaboratively by us. It gives also presents a brief analysis of the links in Wikidata.
Build Narratives, Connect Artifacts: Linked Open Data for Cultural HeritageOntotext
Many issues are faced by scholars, book researchers, museum directors who try to find the underlying connection between resources. Scholars in particular continuously emphasizes the role of digital humanities and the value of linked data in cultural heritage information systems.
Linked Data Experiences at Springer NatureMichele Pasin
An overview of how we're using semantic technologies at Springer Nature, and an introduction to our latest product: www.scigraph.com
(Keynote given at http://2016.semantics.cc/, Leipzig, Sept 2016)
The Power of Semantic Technologies to Explore Linked Open DataOntotext
Atanas Kiryakov's, Ontotext’s CEO, presentation at the first edition of Graphorum (http://graphorum2017.dataversity.net/) – a new forum that taps into the growing interest in Graph Databases and Technologies. Graphorum is co-located with the Smart Data Conference, organized by the digital publishing platform Dataversity.
The presentation demonstrates the capabilities of Ontotext’s own approach to contributing to the discipline of more intelligent information gathering and analysis by:
- graphically explorinh the connectivity patterns in big datasets;
- building new links between identical entities residing in different data silos;
- getting insights of what type of queries can be run against various linked data sets;
- reliably filtering information based on relationships, e.g., between people and organizations, in the news;
- demonstrating the conversion of tabular data into RDF.
Learn more at http://ontotext.com/.
First Steps in Semantic Data Modelling and Search & Analytics in the CloudOntotext
This webinar will break the roadblocks that prevent many from reaping the benefits of heavyweight Semantic Technology in small scale projects. We will show you how to build Semantic Search & Analytics proof of concepts by using managed services in the Cloud.
Analytics on Big Knowledge Graphs Deliver Entity Awareness and Help Data LinkingOntotext
A presentation of Ontotext’s CEO Atanas Kiryakov, given during Semantics 2018 - an annual conference that brings together researchers and professionals from all over the world to share knowledge and expertise on semantic computing.
DBPedia past, present and future - Dimitris Kontokostas. Reveals recent developments in the Linked Data and knowledge graphs field and how DBPedia progress with wikipedia data.
Towards Knowledge Graph based Representation, Augmentation and Exploration of...Sören Auer
Despite an improved digital access to scientific publications in the last decades, the fundamental principles of scholarly communication remain unchanged and continue to be largely document-based. The document-oriented workflows in science have reached the limits of adequacy as highlighted by recent discussions on the increasing proliferation of scientific literature, the deficiency of peer-review and the reproducibility crisis. We need to represent, analyse, augment and exploit scholarly communication in a knowledge-based way by expressing and linking scientific contributions and related artefacts through semantically rich, interlinked knowledge graphs. This should be based
on deep semantic representation of scientific contributions, their manual, crowd-sourced and automatic augmentation and finally the intuitive exploration and interaction employing question answering on the resulting scientific knowledge base. We need to synergistically combine automated extraction and augmentation techniques, with large-scale collaboration to reach an unprecedented level of knowledge graph breadth and depth. As a result, knowledge-based information flows can facilitate completely new ways of search and exploration. The efficiency and effectiveness of scholarly communication will significant increase, since ambiguities are reduced, reproducibility is facilitated, redundancy is avoided, provenance and contributions can be better traced and the interconnections of research contributions are made more explicit and transparent. In this talk we will present first steps in this direction in the context of our Open Research Knowledge Graph initiative and the ScienceGRAPH project.
The Bounties of Semantic Data Integration for the Enterprise Ontotext
If you are looking for solutions that allow you not only to manage all of your data (structured, semi-structured and unstructured) but to also make the most out of them, using a common language is critical.
Adding Semantic Technology to data integration is the glue that holds together all your enterprise data and their relationships in a meaningful way.
Learn how you can quickly design data processing jobs and integrate massive amounts of data and see what semantic integration can do for your data and your business.
www.ontotext.com
Linking Open, Big Data Using Semantic Web Technologies - An IntroductionRonald Ashri
The Physics Department of the University of Cagliari and the Linkalab Group invited me to talk about the Semantic Web and Linked Data - this is simply an introduction to the technologies involved.
Using the Semantic Web Stack to Make Big Data SmarterMatheus Mota
This presentation will discuss how just a few parts of the Semantic Web Cake can already boost your analytics by making your (big) data smarter and even more connected.
This invited keynote at the Social Computing Track at WI-IAT21 gives an introduction to Knowledge Graphs and how they are built collaboratively by us. It gives also presents a brief analysis of the links in Wikidata.
Build Narratives, Connect Artifacts: Linked Open Data for Cultural HeritageOntotext
Many issues are faced by scholars, book researchers, museum directors who try to find the underlying connection between resources. Scholars in particular continuously emphasizes the role of digital humanities and the value of linked data in cultural heritage information systems.
Linked Data Experiences at Springer NatureMichele Pasin
An overview of how we're using semantic technologies at Springer Nature, and an introduction to our latest product: www.scigraph.com
(Keynote given at http://2016.semantics.cc/, Leipzig, Sept 2016)
The Power of Semantic Technologies to Explore Linked Open DataOntotext
Atanas Kiryakov's, Ontotext’s CEO, presentation at the first edition of Graphorum (http://graphorum2017.dataversity.net/) – a new forum that taps into the growing interest in Graph Databases and Technologies. Graphorum is co-located with the Smart Data Conference, organized by the digital publishing platform Dataversity.
The presentation demonstrates the capabilities of Ontotext’s own approach to contributing to the discipline of more intelligent information gathering and analysis by:
- graphically explorinh the connectivity patterns in big datasets;
- building new links between identical entities residing in different data silos;
- getting insights of what type of queries can be run against various linked data sets;
- reliably filtering information based on relationships, e.g., between people and organizations, in the news;
- demonstrating the conversion of tabular data into RDF.
Learn more at http://ontotext.com/.
First Steps in Semantic Data Modelling and Search & Analytics in the CloudOntotext
This webinar will break the roadblocks that prevent many from reaping the benefits of heavyweight Semantic Technology in small scale projects. We will show you how to build Semantic Search & Analytics proof of concepts by using managed services in the Cloud.
Analytics on Big Knowledge Graphs Deliver Entity Awareness and Help Data LinkingOntotext
A presentation of Ontotext’s CEO Atanas Kiryakov, given during Semantics 2018 - an annual conference that brings together researchers and professionals from all over the world to share knowledge and expertise on semantic computing.
DBPedia past, present and future - Dimitris Kontokostas. Reveals recent developments in the Linked Data and knowledge graphs field and how DBPedia progress with wikipedia data.
Towards Knowledge Graph based Representation, Augmentation and Exploration of...Sören Auer
Despite an improved digital access to scientific publications in the last decades, the fundamental principles of scholarly communication remain unchanged and continue to be largely document-based. The document-oriented workflows in science have reached the limits of adequacy as highlighted by recent discussions on the increasing proliferation of scientific literature, the deficiency of peer-review and the reproducibility crisis. We need to represent, analyse, augment and exploit scholarly communication in a knowledge-based way by expressing and linking scientific contributions and related artefacts through semantically rich, interlinked knowledge graphs. This should be based
on deep semantic representation of scientific contributions, their manual, crowd-sourced and automatic augmentation and finally the intuitive exploration and interaction employing question answering on the resulting scientific knowledge base. We need to synergistically combine automated extraction and augmentation techniques, with large-scale collaboration to reach an unprecedented level of knowledge graph breadth and depth. As a result, knowledge-based information flows can facilitate completely new ways of search and exploration. The efficiency and effectiveness of scholarly communication will significant increase, since ambiguities are reduced, reproducibility is facilitated, redundancy is avoided, provenance and contributions can be better traced and the interconnections of research contributions are made more explicit and transparent. In this talk we will present first steps in this direction in the context of our Open Research Knowledge Graph initiative and the ScienceGRAPH project.
Dec'2013 webinar from the EUCLID project on managing large volumes of Linked Data
webinar recording at https://vimeo.com/84126769 and https://vimeo.com/84126770
more info on EUCLID: http://euclid-project.eu/
Structured Dynamics provides 'ontology-driven applications'. Our product stack is geared to enable the semantic enterprise. The products are premised on preserving and leveraging existing information assets in an incremental, low-risk way. SD's products span from converters to authoring environments to Web services middleware and to eventual ontologies and user interfaces and applications.
This tutorial explains the Data Web vision, some preliminary standards and technologies as well as some tools and technological building blocks developed by AKSW research group from Universität Leipzig.
This presentation addresses the main issues of Linked Data and scalability. In particular, it provides gives details on approaches and technologies for clustering, distributing, sharing, and caching data. Furthermore, it addresses the means for publishing data trough could deployment and the relationship between Big Data and Linked Data, exploring how some of the solutions can be transferred in the context of Linked Data.
morning session talk at the second Keystone Training School "Keyword search in Big Linked Data" held in Santiago de Compostela.
https://eventos.citius.usc.es/keystone.school/
Usage of Linked Data: Introduction and Application ScenariosEUCLID project
This presentation introduces the main principles of Linked Data, the underlying technologies and background standards. It provides basic knowledge for how data can be published over the Web, how it can be queried, and what are the possible use cases and benefits. As an example, we use the development of a music portal (based on the MusicBrainz dataset), which facilitates access to a wide range of information and multimedia resources relating to music.
Video: https://www.youtube.com/watch?v=Rt2oHibJT4k
Technologies such as Hadoop have addressed the "Volume" problem of Big Data, and technologies such as Spark have recently addressed the "Velocity" problem – but the "Variety" problem is largely unaddressed – there is a lot of manual "data wrangling" to mange data models.
These manual processes do not scale well. Not only is the variety of data increasing, also the rate of change in the data definitions is increasing. We can’t keep up. NoSQL data repositories can handle storage, but we need effective models of the data to fully utilize it.
This talk will present tools and a methodology to manage Big Data Models in a rapidly changing world. This talk covers:
Creating Semantic Metadata Models of Big Data Resources
Graphical UI Tools for Big Data Models
Tools to synchronize Big Data Models and Application Code
Using NoSQL Databases, such as Amazon DynamoDB, with Big Data Models
Using Big Data Models with Hadoop, Storm, Spark, Giraph, and Inference
Using Big Data Models with Machine Learning to generate Predictive Models
Developer Collaborative/Coordination processes using Big Data Models and Git
Managing change – Big Data Models with rapidly changing Data Resources
This talk introduces the concepts of web 3.0 technology and how they relate to related technologies such as Internet of Things (IoT), Grid Computing and the Semantic Web:
• A short history of web technologies:
o Web 1.0: Publishing static information with links for human consumption.
o Web 2.0: Publishing dynamic information created by users, for human consumption.
o Web 3.0: Publishing all kinds of information with links between data items, for machine consumption.
• Standardization of protocols for description of any type of data (RDF, N3, Turtle).
• Standardization of protocols for the consumption of data in “the grid” (SPARQL).
• Standardization of protocols for rules (RIF).
• Comparison with the evolution of technologies related to data bases.
• Comparison of IoT solutions based on web 2.0 and web 3.0 technologies.
• Distributed solutions vs centralized solutions..
• Security
• Extensions of Peer-to-peer protocols (XMPP).
• Advantages of solutions based on web 3.0 and standards (IETF, XSF).
Duration of talk: 1-2 hours with questions.
Knowledge Graph Research and Innovation ChallengesSören Auer
Gives an overview on some challenges regarding the combination of machine-learning and knowledge graph technologies and the vision of devising a concept of Cognitive Knowledge Graphs consisting of graphlets instead of mere entity descriptions.
This presentation gives a brief overview on achievements and challenges of the Data Web and describes different aspects of using the Semantic Data Wiki OntoWiki for Linked Data management.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
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/
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
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.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
2. The three Big Data „V“ – Variety is often neglected
Quelle: Gesellschaft für Informatik
Sören Auer 2
3. Linked Data Principles
Addressing the neglected third V (Variety)
1. Use URIs to identify the “things” in your data
2. Use http:// URIs so people (and machines) can
look them up on the web
3. When a URI is looked up, return a description of
the thing (in RDF format)
4. Include links to related things
http://www.w3.org/DesignIssues/LinkedData.html
3
[1] Auer, Lehmann, Ngomo, Zaveri: Introduction to Linked Data and Its Lifecycle on the Web. Reasoning Web 2013
4. Linked (Open) Data: The RDF Data Model
4
RDF = Resource Description Framework
located in
label
industry
headquarters
full nameDHL
Post Tower
162.5 m
Bonn
Logistics Logistik
DHL International GmbH
height
物流
label
Sören Auer
5. RDF Data Model (a bit more technical)
– Graph consists of:
• Resources (identified via URIs)
• Literals: data values with data type (URI) or language (multilinguality integrated)
• Attributes of resources are also URI-identified (from vocabularies)
– Various data sources and vocabularies can be arbitrarily mixed and meshed
– URIs can be shortened with namespace prefixes; e.g. dbp: → http://dbpedia.org/resource/
gn:locatedIn
rdfs:label
dbo:industry
ex:headquarters
foaf:namedbp:DHL_International_GmbH
dbp:Post_Tower
"162.5"^^xsd:decimal
dbp:Bonn
dbp:Logistics
"Logistik"@de
"DHL International GmbH"^^xsd:string
ex:height
"物流"@zh
rdfs:label
rdf:value
unit:Meter
ex:unit
6. RDF mediates between different Data Models &
bridges between Conceptual and Operational Layers
Id Title Screen
5624 SmartTV 104cm
5627 Tablet 21cm
Prod:5624 rdf:type Electronics
Prod:5624 rdfs:label “SmartTV”
Prod:5624 hasScreenSize “104”^^unit:cm
...
Electronics
Vehicle
Car Bus Truck
Vehicle rdf:type owl:Thing
Car rdfs:subClassOf Vehicle
Bus rdfs:subClassOf Vehicle
...
Tabular/Relational Data
Taxonomic/Tree Data
Logical Axioms / Schema
Male rdfs:subClassOf Human
Female rdfs:subClassOf Human
Male owl:disjointWith Female
...
Sören Auer 6
20. 1. Either resulting RDF knowledge base is materialized in a triple store &
2. subsequently queried using SPARQL
3. or the materialization step is avoided by dynamically mapping an input SPAQRL query
into a corresponding SQL query, which renders exactly the same results as the SPARQL
query being executed against the materialized RDF dump
SPARQLMap – Mapping RDB 2 RDF
21. Example: Sparqlify
• Rationale: Exploit existing formalisms
(SQL, SPARQL Construct) as much as
possible
• flexible & versatile mapping language
• translating one SPARQL query into
exactly one efficiently executable SQL
query
• Solid theoretical formalization based
on SPARQL-relational algebra
transformations
• Extremely scalable through elaborated
view candidate selection mechanism
• Used to publish 20B triples for
LinkedGeoData
[1] Stadler, Unbehauen, Auer, Lehmann: Sparqlify – Very Large Scale Linked Data Publication from Relational Databases.
[2] Unbehauen, Stadler, Auer: Optimizing SPARQL-to-SQL Rewriting. iiWAS 2013
[3] Auer, et al.: Triplify: light-weight linked data publication from relational databases. WWW 2009
SPARQL
Construct
SQL
View
Bridge
22. Semantified Big Data Architecture Blueprint
Sören Auer 22
[1] Mami, Scerri, Auer, Vidal: Towards the Semantification of Big Data Technology. DEXA 2016
Datasources Ingestion Storage
Semantic Lifting
with Mappings
Querys
Storing of semantic and semantified data
in Apache Parquet files on HDFS
24. SEBIDA Evaluation Results
• Loads data faster
• Has quite different query
performance
characteristics –
faster in 5 out of 12
queries,
similar performance in 2,
slower in 5
Sören Auer 24
48. Big Data is not Just Volume and Velocity
Variety (& Varacity) are key challenges
Linked Data helps dealing with both
• Linked Data life-cycle requires to integrate
and adapt results from a number of
disciplines
– NLP,
– Machine Learning,
– Knowledge Representation,
– Data Management,
– User Interaction
– …
• Applications in a number of domains
– cultural heritage,
– life sciences,
– industry 4.0 / cyber-physical systems,
– smart cities,
– mobility,
– …
Sören Auer 48
Linked Data links not only data but also:
• Various disciplines
• Applications and Use cases
49. Creating Knowledge
out of Interlinked Data
Thanks for your attention!
Sören Auer
http://www.iai.uni-bonn.de/~auer | http://eis.iai.uni-bonn.de
auer@cs.uni-bonn.de
https://www.eccenca.com
Data Lake is a storage repository for big data scale raw data in original data formats.
late binding approach to schema: “Let us decide, when we need it.”
scale out architecture on commodity infrastructure, mostly with HFS/Hadoop/Spark, which gives a huge cost advantage – about factor 10 compared to data warehouses.
Semantic Data Lake = Data Lake + Knowledge Graph
management of structure (vocabularies/schemas, KPIs trees, metadata, …) on top of the Data Lake is performed in a knowledge graph - a complex data fabric representing all kinds of things and how they relate to each other.
A knowledge graph is unique regarding flexibility, multiple views and metadata capabilities.
Based on the Resource Description Framework (RDF) standard and Linked Data principles.
Die Plattform bietet einen sicheren Raum zur Vernetzung
Daten bleiben bei den Enterprise und werden nur bei Bedarf vernetzt
Marktorientiertes Modell ohne Abhängigkeiten von einzelnen Anbietern
Wertschöpfung und Servicee bleiben beim Enterprise
Finanzierung über Servicee, nicht über Werbung oder Datenverkauf
Keine zentrale Datenkrake wie Google, sondern Kontrolle über Daten bleibt bei den Daten-Ownern
Kunde (Endnutzer) ist nicht Produkt, sondern Souverän über seine Daten
Das Ganze ist mehr als die Summe der einzelnen Teile (Ende-zu-Ende-Servicee auf Basis der Daten von mehreren bieten überproportional höheren Mehrwert)
Kein zentraler Datentopf, sondern ein Netz gesunder, sicherer Daten
Governance nicht monopolistisch, sondern föderal
Linked Data approach can help to establish data value chains
Linked Data life-cycle requires to integrate and adapt results from a number of disciplines (NLP, Machine Learning, Knowledge Representation, Data Management)
Applications in a number of domains (cultural heritage, life sciences, industry 4.0 / cyber-physical systems, smart cities, mobility,…)