The document discusses the need for ontologies that can better support linking and mapping between large, distributed databases on the semantic web. While OWL has been successful in some domains, it lacks expressivity for tasks like representing part-whole relations, temporal reasoning, and procedural knowledge. A new generation of ontology languages may need to relax requirements like decidability in order to more powerfully represent relationships that are important for data integration and discovery across multiple knowledge sources.
Exploring the Boundaries of Artificial Intelligence (or "Modern AI")James Hendler
A discussion of the strengths and limitations of some current AI systems including chatGPT and DALL-E. Originally presented at University of Leicester Feb 2023.
The original abstract, title and bio were generated by chatGPT -- the first three slides show corrections -- original talk announcement included:
"Please note: The title, abstract and Hendler’s bio above were written by “GPT3,” a modern AI system. It contains information which is both correct and incorrect. That will be the topic of this talk."
ABOUT US 3E MAKİNA entrepreneur, who provides services and products for the needs of business partners, increases the production qualities and constantly develops himself, was founded in 2011 with an innovative and responsible visionary spirit. With its principles and values that it has started its activities in the machinery industry, it has become a demanded company in a short time. 3E MAKİNA has successfully represented the Turkish machinery industry with its high quality and after-sales services, which it has presented in the country and abroad in the last years. This rapid growth in a short period of time has become stable and has been among the esteemed and reliable establishments of 3E MAKİNA MAKİNA SANAYII.
Exploring the Boundaries of Artificial Intelligence (or "Modern AI")James Hendler
A discussion of the strengths and limitations of some current AI systems including chatGPT and DALL-E. Originally presented at University of Leicester Feb 2023.
The original abstract, title and bio were generated by chatGPT -- the first three slides show corrections -- original talk announcement included:
"Please note: The title, abstract and Hendler’s bio above were written by “GPT3,” a modern AI system. It contains information which is both correct and incorrect. That will be the topic of this talk."
ABOUT US 3E MAKİNA entrepreneur, who provides services and products for the needs of business partners, increases the production qualities and constantly develops himself, was founded in 2011 with an innovative and responsible visionary spirit. With its principles and values that it has started its activities in the machinery industry, it has become a demanded company in a short time. 3E MAKİNA has successfully represented the Turkish machinery industry with its high quality and after-sales services, which it has presented in the country and abroad in the last years. This rapid growth in a short period of time has become stable and has been among the esteemed and reliable establishments of 3E MAKİNA MAKİNA SANAYII.
Knowledge Representation in the Age of Deep Learning, Watson, and the Semanti...James Hendler
IJCAI 16 keynote on the need to bring modern AI accomplishments of recent years into connection with the more traditional goals of symbolic AI (and vice versa).
Social Machines - 2017 Update (University of Iowa)James Hendler
This is an update to the talk entitled "Social Machines: the coming collision of artificial intelligence, social networks and humanity." It was presented as an ACM Distinguished Speaker lecture at the "University of Iowa Computing Conference" 2017-02-24
Social Machines: The coming collision of Artificial Intelligence, Social Netw...James Hendler
Will your next doctor be a human being—or a machine? Will you have a choice? If you do, what should you know before making it?This book introduces the reader to the pitfalls and promises of artificial intelligence (AI) in its modern incarnation and the growing trend of systems to "reach off the Web" into the real world. The convergence of AI, social networking, and modern computing is creating an historic inflection point in the partnership between human beings and machines with potentially profound impacts on the future not only of computing but of our world and species.AI experts and researchers James Hendler—co-originator of the Semantic Web (Web 3.0)—and Alice Mulvehill—developer of AI-based operational systems for DARPA, the Air Force, and NASA—explore the social implications of AI systems in the context of a close examination of the technologies that make them possible. The authors critically evaluate the utopian claims and dystopian counterclaims of AI prognosticators. Social Machines: The Coming Collision of Artificial Intelligence, Social Networking, and Humanity is your richly illustrated field guide to the future of your machine-mediated relationships with other human beings and with increasingly intelligent machines.
On Beyond OWL: challenges for ontologies on the WebJames Hendler
The need for ontologies in the real world is manifest and increasing. On the Web, ontologies are everywhere — but OWL isn’t. In this talk, I look at some of the things that are not in OWL, but which are needed for the use of OWL in many Web domains. This talk explores some of the needs for ontologies on the Web in data integration, emerging technologies, and linked data applications – and asks where the features needed for these are in OWL. The talk ends with some challenges to the OWL, and greater ontology, community needed to see more eventual use of standard ontologies on the Web.
A 1015 update to the 2012 "Data Big and Broad" talk - http://www.slideshare.net/jahendler/data-big-and-broad-oxford-2012 - extends coverage, brings more in context of recent "big data" work.
A talk presented at IBM's "Academy of Technology" exploring, in brief, what the research community has to learn from Watson (and the techniques derived therefrom) and some new research ideas that can be explored therefrom. All known proprietary information from either IBM or RPI has been removed from the original talk.
ABSTAT: Ontology-driven Linked Data Summaries with Pattern MinimalizationBlerina Spahiu
An increasing number of research and industrial initiatives
have focused on publishing Linked Open Data, but little attention has been provided to help consumers to better understand existing data sets. In this paper we discuss how an ontology-driven data abstraction model supports the extraction and the representation of summaries of linked data sets. The proposed summarization model is the backbone of the ABSTAT framework, that aims at helping users understanding big and complex linked data sets. Our framework is evaluated by showing that
it is capable of unveiling information that is not explicitly represented in underspecified ontologies and that is valuable to users, e.g., helping them in the formulation of SPARQL queries.
The General Ontology Evaluation Framework (GOEF) & the I-Choose Use CaseA ...Joanne Luciano
Example of the application of General Ontology Evaluation Framework (GOEF) to uses cases from I-Choose, a transnational project (NSF (USA) and CONACYT (Mexico)). to build an interoperable data architecture to support ethical consumption, with a focus on sustainable coffee products produced in Mexico and consumed and distributed in Canada and in the US.
Components of I-Choose System: A set of data standards to share information across sustainable supply-chain and a governance system.
National Institute of Standards and Technology
NIST Grant No.: 60NANB12D201
PI: Joanne S. Luciano
(Download slideshow to see slide builds)
The term ontology is used a lot in our profession but rarely do we define what ontology is or what it is supposed to accomplish. Ontology is actually a very effective method to describe things and their relationships. Come to the Ontology Dojo to:
Find out that ontology really is not that scary.
Learn skills to help understand large information and data problems.
Supercharge your deliverables (especially concept maps).
No ontology skills are needed, but you will leave fully armed to take on any ontology problem!
Video version of the presentation from 2016 IA Summit: http://bit.ly/29bTrqE
The OWL Web Ontology Language enables software engineers to define ontologies of domain knowledge which can be queried and reasoned over by software agents. OWL facilitates greater machine interpretability of content than that supported by XML, RDF, and RDF Schema by providing additional vocabulary along with formal semantics.
In this talk I review some of the early visions of the Semantic Web, some of the different views, and I follow through on a thread of how Semantic Web technology has been adopted in search engines (and other companies). I end with a challenge to the research community to keep pursuing this research, rather than letting industry take over the "low end" and keep new work from flourishing.
VOLT: A Provenance-Producing, Transparent SPARQL Proxy for the On-Demand Computation of Linked Data & its Applications to Spatiotemporally Dependent Data
Human-Aware Sensor Network Ontology: Semantic Support for Empirical Data Coll...Paulo Pinheiro
Overall description of the Human-Aware Sensor Network Ontology (HASNetO), explaining how it was derived as an integration of concepts provided by the OBOE, VSTO and W3C PROV ontologies.
ESWC 2016 Tutorial on RDF Benchmarks
(This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688227.)
Presented at The 6th Workshop on Semantics for Smarter Cities (S4SC 2015) co-located with The 14th International Semantic Web Conference (ISWC 2015).
Full paper at: http://tw.rpi.edu/web/doc/santos-s4sc-2015
This talks summarizes some of the main trends on the Semantic Web in the past year. It includes discussion of recent industrial trends, government data, and some Web 3.0 thoughts. This particular version was presented at a Korean Workshop (http://wsms2010.kaist.ac.kr/) in 2010.
An updated "what is happening on the Semantic Web" presentation for 2010 - includes business use, government use, and some speculation on the current areas of excitement and development. A very accessible talk, not aimed solely at a technical audience.
Knowledge Representation in the Age of Deep Learning, Watson, and the Semanti...James Hendler
IJCAI 16 keynote on the need to bring modern AI accomplishments of recent years into connection with the more traditional goals of symbolic AI (and vice versa).
Social Machines - 2017 Update (University of Iowa)James Hendler
This is an update to the talk entitled "Social Machines: the coming collision of artificial intelligence, social networks and humanity." It was presented as an ACM Distinguished Speaker lecture at the "University of Iowa Computing Conference" 2017-02-24
Social Machines: The coming collision of Artificial Intelligence, Social Netw...James Hendler
Will your next doctor be a human being—or a machine? Will you have a choice? If you do, what should you know before making it?This book introduces the reader to the pitfalls and promises of artificial intelligence (AI) in its modern incarnation and the growing trend of systems to "reach off the Web" into the real world. The convergence of AI, social networking, and modern computing is creating an historic inflection point in the partnership between human beings and machines with potentially profound impacts on the future not only of computing but of our world and species.AI experts and researchers James Hendler—co-originator of the Semantic Web (Web 3.0)—and Alice Mulvehill—developer of AI-based operational systems for DARPA, the Air Force, and NASA—explore the social implications of AI systems in the context of a close examination of the technologies that make them possible. The authors critically evaluate the utopian claims and dystopian counterclaims of AI prognosticators. Social Machines: The Coming Collision of Artificial Intelligence, Social Networking, and Humanity is your richly illustrated field guide to the future of your machine-mediated relationships with other human beings and with increasingly intelligent machines.
On Beyond OWL: challenges for ontologies on the WebJames Hendler
The need for ontologies in the real world is manifest and increasing. On the Web, ontologies are everywhere — but OWL isn’t. In this talk, I look at some of the things that are not in OWL, but which are needed for the use of OWL in many Web domains. This talk explores some of the needs for ontologies on the Web in data integration, emerging technologies, and linked data applications – and asks where the features needed for these are in OWL. The talk ends with some challenges to the OWL, and greater ontology, community needed to see more eventual use of standard ontologies on the Web.
A 1015 update to the 2012 "Data Big and Broad" talk - http://www.slideshare.net/jahendler/data-big-and-broad-oxford-2012 - extends coverage, brings more in context of recent "big data" work.
A talk presented at IBM's "Academy of Technology" exploring, in brief, what the research community has to learn from Watson (and the techniques derived therefrom) and some new research ideas that can be explored therefrom. All known proprietary information from either IBM or RPI has been removed from the original talk.
ABSTAT: Ontology-driven Linked Data Summaries with Pattern MinimalizationBlerina Spahiu
An increasing number of research and industrial initiatives
have focused on publishing Linked Open Data, but little attention has been provided to help consumers to better understand existing data sets. In this paper we discuss how an ontology-driven data abstraction model supports the extraction and the representation of summaries of linked data sets. The proposed summarization model is the backbone of the ABSTAT framework, that aims at helping users understanding big and complex linked data sets. Our framework is evaluated by showing that
it is capable of unveiling information that is not explicitly represented in underspecified ontologies and that is valuable to users, e.g., helping them in the formulation of SPARQL queries.
The General Ontology Evaluation Framework (GOEF) & the I-Choose Use CaseA ...Joanne Luciano
Example of the application of General Ontology Evaluation Framework (GOEF) to uses cases from I-Choose, a transnational project (NSF (USA) and CONACYT (Mexico)). to build an interoperable data architecture to support ethical consumption, with a focus on sustainable coffee products produced in Mexico and consumed and distributed in Canada and in the US.
Components of I-Choose System: A set of data standards to share information across sustainable supply-chain and a governance system.
National Institute of Standards and Technology
NIST Grant No.: 60NANB12D201
PI: Joanne S. Luciano
(Download slideshow to see slide builds)
The term ontology is used a lot in our profession but rarely do we define what ontology is or what it is supposed to accomplish. Ontology is actually a very effective method to describe things and their relationships. Come to the Ontology Dojo to:
Find out that ontology really is not that scary.
Learn skills to help understand large information and data problems.
Supercharge your deliverables (especially concept maps).
No ontology skills are needed, but you will leave fully armed to take on any ontology problem!
Video version of the presentation from 2016 IA Summit: http://bit.ly/29bTrqE
The OWL Web Ontology Language enables software engineers to define ontologies of domain knowledge which can be queried and reasoned over by software agents. OWL facilitates greater machine interpretability of content than that supported by XML, RDF, and RDF Schema by providing additional vocabulary along with formal semantics.
In this talk I review some of the early visions of the Semantic Web, some of the different views, and I follow through on a thread of how Semantic Web technology has been adopted in search engines (and other companies). I end with a challenge to the research community to keep pursuing this research, rather than letting industry take over the "low end" and keep new work from flourishing.
VOLT: A Provenance-Producing, Transparent SPARQL Proxy for the On-Demand Computation of Linked Data & its Applications to Spatiotemporally Dependent Data
Human-Aware Sensor Network Ontology: Semantic Support for Empirical Data Coll...Paulo Pinheiro
Overall description of the Human-Aware Sensor Network Ontology (HASNetO), explaining how it was derived as an integration of concepts provided by the OBOE, VSTO and W3C PROV ontologies.
ESWC 2016 Tutorial on RDF Benchmarks
(This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688227.)
Presented at The 6th Workshop on Semantics for Smarter Cities (S4SC 2015) co-located with The 14th International Semantic Web Conference (ISWC 2015).
Full paper at: http://tw.rpi.edu/web/doc/santos-s4sc-2015
This talks summarizes some of the main trends on the Semantic Web in the past year. It includes discussion of recent industrial trends, government data, and some Web 3.0 thoughts. This particular version was presented at a Korean Workshop (http://wsms2010.kaist.ac.kr/) in 2010.
An updated "what is happening on the Semantic Web" presentation for 2010 - includes business use, government use, and some speculation on the current areas of excitement and development. A very accessible talk, not aimed solely at a technical audience.
The Unreasonable Effectiveness of MetadataJames Hendler
Invited talk at VIVO 2017 conference - explores the view of the semantic web as enriched metadata, and how that kind of information can be used in new and interesting ways.
Digital Archiving, The Semantic Web, and Modern AIJames Hendler
This was my keynote talk on accepted the "Spotlight Award" from the association of moving image archivists. The talk relates needs of archiving, use of semantic (web) metadata, and deep learning for archiving.
A lecture/conversation focusing on the first 12 years of Semantic Web - delivered on February 21, 2012.
See http://j.mp/SWIntro for more details. More detailed course material is at http://knoesis.org/courses/web3/
Effective Semantics for Engineering NLP SystemsAndre Freitas
Provide a synthesis of the emerging representation trends behind NLP systems.
Shift in perspective:
Effective engineering (task driven, scalable) instead of sound formalism.
Best-effort representation.
Knowledge Graphs (Frege revisited)
Information Extraction & Text Classification
Distributional Semantic Models
Knowledge Graphs & Distributional Semantics
(Distributional-Relational Models)
Applications of DRMs
KG Completion
Semantic Parsing
Natural Language Inference
Knowing what AI Systems Don't know and Why it mattersJames Hendler
A discussion of chatGPT and some other examples with respect to accuracy and other issues - a general background talk for those interested in the subject
Presentation at "International knowledge graph workshop" at KDD 2020. The short overview talk shows how we have moved from Semantic Web to Linked Data to Knowledge Graphs. We argue that the same "a little semantics goes a long way" principle from the early days of the Semantic Web still is needed today -- some lessons learned and steps ahead are outlined.
Keynote talk presented at WebScience 2020 conference. Looks at roots of Web/Web Science and explores two possible futures and what web scientists and others can do about it. Even starts with a quote from Charles Dickins.
The Future of AI: Going BeyondDeep Learning, Watson, and the Semantic WebJames Hendler
These slides, based on a presentation at distinguished lecture at IBM Almaden in March, 2017 explore some of the challenges to machine learning and some recent work. It is a newer version of the slides originally presented at IJCAI 2016.
Capacity Building: Data Science in the University At Rensselaer Polytechnic ...James Hendler
In this short talk, presented at the ITU's Capacity Building Symposium, I review some of the pedagogical innovation in data science happening at Rensselaer (RPI) and some aspects of teaching data science that are crucial to larger success.
Enhancing Precision Wellness with Knowledge Graphs and Semantic Analytics: O...James Hendler
Talk presented at Bio-IT 2018 (machine learning track) - explores some approaches to overcoming challenges of using machine learning systems in healthcare applications.
This talk presents areas of investigation underway at the Rensselaer Institute for Data Exploration and Applications. First presented at Flipkart, Bangalore India, 3/2015.
Facilitating Web Science Collaboration through Semantic MarkupJames Hendler
These are the slides that accompanied the paper "Dominic DiFranzo, John S. Erickson, Marie Joan Kristine T. Gloria, Joanne S. Luciano, Deborah McGuinness, & James Hendler, The Web Observatory Extension: Facilitating Web Science Collaboration through Semantic Markup, Proc. WWW 2014 (Web Science Track), Seoul, Korea, 2014." They describe an extension to schema.org that can be used for sharing Web-related datasets and projects.
Why Watson Won: A cognitive perspectiveJames Hendler
In this talk, we present how the Watson program, IBM's famous Jeopardy playing computer, works (based on papers published by IBM), we look at some aspects of potential scoring approaches, and we examine how Watson compares to several well known systems and some preliminary thoughts on using it in future artificial intelligence and cognitive science approaches.
The Rensselaer Institute for Data Exploration and Applications is addressing new modes of data exploration and integration to enhance the work of campus researchers (and beyond). This talk outlines the "data exploration" technologies being explored
Presented to a webinar hosted by Nuance Inc, under the title "The Semantic Web: What it is and Why you should care" on 2/29/2012.
This talk presents a fast overview of the Semantic Web and recent application deployment in the space.
The death of the Web has been prematurely reported -- the best is yet to come! In this talk, from the Kshitij at IIT Kharagpur 2012, I talk about what Web 3.0 will feature, and some thoughts on key technology trends on the Web.
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/
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/
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
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
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
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
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.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
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.
PHP Frameworks: I want to break free (IPC Berlin 2024)
Wither OWL
1. Tetherless World Constellation
Wither OWL
Jim Hendler
@jahendler
Tetherless World Professor of Computer, Web and Cognitive Science
Director, Rensselaer Institute for Data Exploration and Applications
Rensselaer Polytechnic Institute
2. Tetherless World Constellation
About the title
• Whither:
– To what place or state
• Wither:
1.Become dry and shriveled
2.To lose the freshness of youth, as from
age
12. Tetherless World Constellation
All cool, but…
• Which of these use OWL in any
significant way?
(This part of the slide intentionally left blank)
13. Tetherless World Constellation
Why not OWL?
• This is NOT to say OWL isn’t being used
– but it’s not much by comparison
– but it’s not much on the Web
• with the possible exception of the misuse of
owl:sameAs, but let’s not go there…
• Semantic markup on the Web exceeds
anything we predicted in 2001…
– … but OWL use on the Web as a proportion of
this lags behind the expectations many of us
had
• The rest of this talk is speculation as to why…
15. Ontology: the OWL DL view
• Ontology as Barad-
Dur (Sauron's
tower):
– Extremely powerful!
– Patrolled by Orcs
• Let one little hobbit
in, and the whole
thing could come
crashing down
inconsistency
Decidable Logic basis
16. ontology: the RDFS view
• ontology and the
tower of Babel
– We will build a tower
to reach the sky
– We only need a little
ontological
agreement
• Who cares if we all
speak different
languages?
Genesis 11:7 Let us go down, and there confound their
language, that they may not understand one another's speech.
So the Lord scattered them abroad from thence upon the face
of all the earth: and they left off to build the city.
17. ROI: Reasoning over
(Enterprise) data
• This "big O" Ontology finds use cases in
verticals and enterprises
– Where the vocabulary can be controlled
– Where finding things in the data is important
• Example
– Drug discovery from data
• Model the molecule (site, chemical properties, etc) as
faithfully and expressively as possible
• Use "Realization" to categorize data assets against the
ontology
– Bad or missed answers are money down the drain
BUT VERY EXPENSIVE
18. ROI: Web 3.0
• The "small o" ontology finds use cases in
Web Applications (at Web scales)
– A lot of data, a little semantics
– Finding anything in the mess can be a win!
• Example
– Declare simple inferable relationships and apply,
at scale, to large, heterogeneous data collections
• These are "heuristics" not every answer must be
right (qua Google)
– But remember time = money!
WHAT I USED TO BELIEVE
19. ROI: Web 3.0
• The "small o" ontology finds use cases in
Web Applications (at Web scales)
– A lot of data, a little semantics
– Finding anything in the mess can be a win!
• Example
– Declare simple inferable relationships and apply,
at scale, to large, heterogeneous data collections
• These are "heuristics" not every answer must be
right (qua Google)
– But remember time = money!
WHAT I NOW BELIEVE
20. Tetherless World Constellation
BUT, not quite the same way
• That explains why the uptake of
RDFS/SPARQL is going on
– But primarthings like schema.org
• But still doesn’t explain why OWL
isn’t used as much as it should be
– especially on the Web
– especially when the need for ontologies
is growing rapidly and many kinds of
“ontology like things” are being used
heavily
21. Tetherless World Constellation
What I am coming to believe
• My previous view was blaming OWL’s
problems on too much expressivity
– as opposed to RDFS (or really RDFS+)
• I now believe the problem is lack of
expressivity (in an interoperable
way)
– for tasks where people really need Web
semantics
22. Tetherless World Constellation
We were right:
The Web is increasingly about LINKING DATA
http://linkeddata.org/ cloud is a tiny fraction of what is out there
23. Tetherless World Constellation
Current linked data approaches are also broken!
• Data is converted into RDF and SPARQL’ed
– creates huge graph DBs less efficient than the
original DB
• Data is converted from DB into SPARQL
return on demand
– much better, but you must know the mapping
• owl:sameAs is (ab)used to map data to
data
– but that only lets you map equals – which is an
easy mapping to express in many ways
• defining equality right in a model theory is much
harder, and thus the abuse, but let’s leave that for
another talk
24. Tetherless World Constellation
DataData
MetaData
What we need
Linked Semantic Web “metadata” documents that can be used to link very large databases in
distributed data systems. This could lead to orders of magnitude reduction in information flow
for large-scale distributed data problems.
25. Tetherless World Constellation
What’s the problem
• We want a knowledge representation
that can do things like:
– help us find the right data for a problem
• The “Date” field in some DB could be lots of
different things
– consider “Database of 1957 NYC births” vs
“Database of 1957 NYC deaths”
– help us map between different
databases
• The problem isn’t primarily translating
ontologies to each other, it is tying the
ontologies to the data (for the mappings)
26. Tetherless World Constellation
Example: Mereology (and meronymy)
• OWL doesn’t have a part-whole relation
– left out of design because we couldn’t reach
consensus (and there’s 2000 yrs of argument behind
that)
• but also because most require transitive closure of
parts in many cases and that had complexity
issues
– but one of the most
used relations in
the gene ontology
and many medical
ontologies is
part of
27. Tetherless World Constellation
But, what? Wait!
Example: We use the fact that the brain has 5 lobes as
a driving example for qualified cardinality
- but to say that in OWL, you need to INVENT the
“hasdirectpart” relation (i.e. no interoperability on the
important part for the data!)
28. Tetherless World Constellation
Database mapping
• Many things in database schemas
also map to parts/wholes
– Who is in what organization?
– What components comprise an
assembly?
– Where did something occur (that was
part of another event)?
– When…
29. Tetherless World Constellation
When?
• Temporal reasoning is missing from
OWL
– Knowing [this talk occurred during
“ESWC 2016” AND “ESWC 2016”
occurred in May of 2016, THEREFORE
this talk occurred in May of 2016] would
be huge
• Whole books of temporal logics out there
– picking is hard
– but it is also what OWL has to do to be a standard
for this kind of mapping
30. Tetherless World Constellation
Geophysical reasoning
• Add math to part-wholes
– OY!
– but GDBs are widely used for mappings
of information in big databases
• especially in science (more OWL use cases)
• Talking about “math”
– lots of discussion of adding probability
to OWL
• and someone should some day
– but what about
31. Tetherless World Constellation
SIMPLE relationship reasoning
• Discovery Informatics and data mining
– Huge industries, and growing
– Web data, Internet of things, data
interoperability (the startup holy grails)
• Example: supposing some scientific theory
“implies” that if X increases then Y should
also increase
– Which databases would help confirm my
theory? Which would argue against it?
– Easy to check in many new database systems
– How do we express that aspect of the theory in
OWL?
32. Tetherless World Constellation
Digression…
(and shameless self promotion)
• That will be the topic of my keynote
at IJCAI 2016 entitled “Knowledge
Representation in the Era of Deep
Learning, Watson and the Semantic
Web”
– I’d welcome your thoughts and good
ideas I next couple of days!
33. Tetherless World Constellation
Back to our regularly scheduled talk:
Procedural Attachment?
• In fact, what about procedural
attachment?
– lots of literature on preserving
completeness w/respect to procedures
• used in prolog, etc.
– Why isn’t this in OWL?
• patent issues w/respect to standard
• general concern about whether procedural
attachment was possible in OWL DL
framework
35. 35
Exploring knowledge graphs
• Agent reasons about a network of connected entities and chooses the
best next one to discuss based on a combination of factors
– Consistency, Novelty and Ontological relationships
36. 36
Integrating
• Automate Agent Creation combining:
Information Extraction: Using anew
"living information extraction" technique, we
will be able to create a "never-ending
extractor" which will be pulling from web
documents information about entities and
events, and the relationships between
them.
The new system can work in a dynamic
node, and does not need human annotated
samples for training, but it works best if
there are a number of known relationships
between pages to build off of.
info extraction uses ontologies
37. 37
Integrate
• Automate Agent Creation combining:
Information Extraction: Using anew
"living information extraction" technique, we
will be able to create a "never-ending
extractor" which will be pulling from web
documents information about entities and
events, and the relationships between
them.
The new system can work in a dynamic
node, and does not need human annotated
samples for training, but it works best if
there are a number of known relationships
between pages to build off of.
Semantic Web: The Semantic Web
provides a number of known relationships
between pages on the Web in a number of
domains. Using general knowledge
sources, like dbpedia and Yago, and
specialized knowledge sources, like the
data from musicbrainz, the reviews from
Yelp (which have semantic annotations)
and even the Open Graph of Facebook
(which is available in a semantic web
format), provides a jumpstart for the
language extraction.
However, the Semantic Web relates pages,
but doesn't have any sort of
"understanding" of what is on the pages.
ontologies
again!
38. 38
Our Approach
• Automate Agent Creation combining:
Information Extraction: Using anew
"living information extraction" technique, we
will be able to create a "never-ending
extractor" which will be pulling from web
documents information about entities and
events, and the relationships between
them.
The new system can work in a dynamic
node, and does not need human annotated
samples for training, but it works best if
there are a number of known relationships
between pages to build off of.
Semantic Web: The Semantic Web
provides a number of known relationships
between pages on the Web in a number of
domains. Using general knowledge
sources, like dbpedia and Yago, and
specialized knowledge sources, like the
data from musicbrainz, the reviews from
Yelp (which have semantic annotations)
and even the Open Graph of Facebook
(which is available in a semantic web
format), provides a jumpstart for the
language extraction.
However, the Semantic Web relates pages,
but doesn't have any sort of
"understanding" of what is on the pages.
Cognitive Computing : Cognitive
Computing, can allow us to have a better
way of accessing information about the
entities found on the Web and finding other
information about the same entities using
various kinds of search and language
heuristics. This allows us to have more
organized information, rapidly generated,
about the entities being explored.
However, given a large graph of entities
(even the organized linked-open data cloud
has information about billions of things),
how do we choose what to display next? If
the best we can do is provide links, all of
the above isn't much better than choosing
a page and clicking from there.
and here!
39. 39
Our Approach
• Automate Agent Creation combining:
Information Extraction: Using anew
"living information extraction" technique, we
will be able to create a "never-ending
extractor" which will be pulling from web
documents information about entities and
events, and the relationships between
them.
The new system can work in a dynamic
node, and does not need human annotated
samples for training, but it works best if
there are a number of known relationships
between pages to build off of.
Semantic Web: The Semantic Web
provides a number of known relationships
between pages on the Web in a number of
domains. Using general knowledge
sources, like dbpedia and Yago, and
specialized knowledge sources, like the
data from musicbrainz, the reviews from
Yelp (which have semantic annotations)
and even the Open Graph of Facebook
(which is available in a semantic web
format), provides a jumpstart for the
language extraction.
However, the Semantic Web relates pages,
but doesn't have any sort of
"understanding" of what is on the pages.
Cognitive Story-telling Technology: Interactive
storytelling techniques are being explored
to take information in the kind of
"knowledge graph" resulting from the
above, and tailoring the presentation to a
user using storytelling techniques. It is
aimed at presenting the information as an
interesting and meaningful story by taking
into consideration a combination of factors
ranging from topic consistency and novelty,
to learned user interests and even a user’s
emotional reactions. The system can
essentially determine "where to go next"
and what to do there in the organized
information as processed above..
“User models” (which we are encoding using an ontology)
40. Tetherless World Constellation
I could go on
• There are many other such examples
– Describing how data in one set could be joined
to data in another is incredibly powerful,
timely, and important
• it’s just not really what people have typically used
traditional reasoners for
– Providing the ontological glue among different
AI technologies: Priceless
• Why aren’t we doing more to understand
these issues and bring into the OWL
“family?”
– de facto standardization leads to adoption
41. Tetherless World Constellation
My challenge
• Is the problem that we cannot have
these powerful things in a decidable
(sound and complete) language?
– then maybe we have to give up
decidability?
• or even better, define new maths of
expressivity that have different kinds of
“sound and complete” behavior
– i.e. approximately sound and complete
» (is modern computational theory weakened by
“within epsilon” optimality?)
– i.e. “anytime” algorithms for reasoners
» (conjecture) sound and complete at infinity
43. Tetherless World Constellation
I’m not “anti-formalism”
• A sufficient formalism for Semantic Web
applications must
– Provide a model that accounts for linked data
• What is the equivalent of a DB calculus?
– Provide a means for evaluating different kinds
of completeness for reasoners
• In practice we must be able to model A-box effects
as formally as T-box technologies
– example Weaver 2012 showed what restrictions were needed
to maximize parallelism of some OWL subsets
– Think about other processors than formal
reasoners that will use the ontologies
• ontologies used in many other ways
– i.e. why does an IE system w/F1=.84 need a DL reasoner?
44. Tetherless World Constellation
Summary
• The growing world of (semantic web,
linked) data needs ontologies more than
ever
– OWL has some of the important things
– But is missing many of the really important
things
• The problem isn’t (formal) expressivity
– it’s the need to express other things (esp
relationships between properties, events, etc.)
– We need more research into how to formalize
these kinds of relations
45. Tetherless World Constellation
Acknowledgments
• I get funded by lots of folks – this talk may or
may not represent anything anyone there
believes:
– ARL, DARPA, Microsoft, Mitre, Optum Laboratories
• The Rensselaer Institute for Data Exploration and
Application pays my salary
– Thanks!!
• Many of my best ideas, including a lot in this talk
come from listening to smart people
– Frank van Harmelen and Peter Mika have influenced my
thinking about many of the ideas in this talk
• The students and my colleagues at the RPI
Tetherless World Constellation (tw.rpi.edu)