This document discusses when to use documents versus triples in a database. It describes the pros and cons of relational databases, document databases, graph databases, and triple stores. It advocates using a hybrid approach that combines documents and triples for the benefits of both. Documents are well-suited for storing heterogeneous data while triples enable modeling relationships and inferring new information. The combination provides a unified platform for querying rich data through semantics.
This presentation, hold during Semantcs conference, introduce Ontos' current achievement towards a Streaming-based Text Mining solution by using Deep Learning and Semantic Web technologies.
Knowledge graphs - it’s what all businesses now are on the lookout for. But what exactly is a knowledge graph and, more importantly, how do you get one? Do you get it as an out-of-the-box solution or do you have to build it (or have someone else build it for you)? With the help of our knowledge graph technology experts, we have created a step-by-step list of how to build a knowledge graph. It will properly expose and enforce the semantics of the semantic data model via inference, consistency checking and validation and thus offer organizations many more opportunities to transform and interlink data into coherent knowledge.
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
Smarter content with a Dynamic Semantic Publishing PlatformOntotext
Personalized content recommendation systems enable users to overcome the information overload associated with rapidly changing deep and wide content streams such as news. This webinar discusses Ontotext’s latest improvements to its Dynamic Semantic Publishing (DSP) platform NOW (News on the Web). The Platform includes social data mining, web usage mining, behavioral and contextual semantic fingerprinting, content typing and rich relationship search.
This presentation, hold during Semantcs conference, introduce Ontos' current achievement towards a Streaming-based Text Mining solution by using Deep Learning and Semantic Web technologies.
Knowledge graphs - it’s what all businesses now are on the lookout for. But what exactly is a knowledge graph and, more importantly, how do you get one? Do you get it as an out-of-the-box solution or do you have to build it (or have someone else build it for you)? With the help of our knowledge graph technology experts, we have created a step-by-step list of how to build a knowledge graph. It will properly expose and enforce the semantics of the semantic data model via inference, consistency checking and validation and thus offer organizations many more opportunities to transform and interlink data into coherent knowledge.
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
Smarter content with a Dynamic Semantic Publishing PlatformOntotext
Personalized content recommendation systems enable users to overcome the information overload associated with rapidly changing deep and wide content streams such as news. This webinar discusses Ontotext’s latest improvements to its Dynamic Semantic Publishing (DSP) platform NOW (News on the Web). The Platform includes social data mining, web usage mining, behavioral and contextual semantic fingerprinting, content typing and rich relationship search.
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.
The Business Case for Semantic Web Ontology & Knowledge GraphCambridge Semantics
In this webinar Mark Wallace, Ontologist & Developer, Semantic Arts, and Thomas Cook, Director of Sales AnzoGraph DB, Cambridge Semantics, explore the benefits of building a Semantic Knowledge Graph with RDF*, wrapping up with an airline data demo that illustrates the value of schema, inference and reasoning in it.
What is Connected Data as a concept? Who is interested in Connected Data? What problems does Connected Data solve? What skills are used in Connected Data?
Connected Data as of July 2017 has been running for over a year with very successful conference and 9 meetups held to date on a range of topics. These have included Knowledge Representation, Semantics, Linked Data, Graph Databases, Ontology development and use cases and industry verticals including recommendations, telecoms and finance. Yet the group has never had a particularly formal terms of reference or description defining what Connected Data actually means. Some would say this is something of a irony for a group so focused on semantics, schemas, definitions & structure!
This is an attempt (with some humour and something of journey included in it) to achieve something resembling a definition and terms of reference for the group.
Sigma EE: Reaping low-hanging fruits in RDF-based data integrationRichard Cyganiak
A presentation I gave at I-Semantics 2010 on Sigma EE, an RDF-based data integration front-end.
Sigma EE is now available for download here: http://sig.ma/?page=help
Large corporations have to master vast amounts of heterogeneous data in order to stay competitive. While existing approaches have attempted to consolidate and manage the data by forcing it into a single shared data model, data lakes recently emerged that instead provide a central storage point for holding all data sets in their original form.
In this talk, we present eccenca CorporateMemory, which extends the data lake paradigm with a semantic integration layer for managing diverse, but semantically enriched data. eccenca CorporateMemory builds an extensible knowledge graph that employs RDF vocabularies for transforming and linking multiple datasets in order to generate an integrated semantic understanding of the data.
Robert Isele | Head of Data Integration Unit at eccenca GmbH
Presentation at Semantics 2016 in Leipzig in the context with the results of the LEDS project
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.
Open Data and News Analytics Demo from the 4th Sofia Open Data & Linked Data meetup
http://www.meetup.com/Sofia-Open-Data-Linked-Data-Meetup/events/228747999/
Mar'2016, Sofia | BG
GraphDB Cloud: Enterprise Ready RDF Database on DemandOntotext
GraphDB Cloud is an enterprise grade RDF graph database providing high-performance querying over large volumes of RDF data. On this webinar, Ontotext demonstrates how to instantly create and deploy a fully managed Graph Database, then import & query data with the (OpenRDF) GraphDB Workbench, and finally explore and visualize data with the build in visualization tools.
When we set out to build a knowledge graph at Zalando, most people did not know how to build one, or considered machine learning as the better solution. However, endorsement from upper management led to the current project, where we use ontologies to improve the customer search and browsing experience.
There are many unique things about the way we built our ontology for Enterprise purposes. Our ontology is peer-reviewed, use case-driven, and we apply special techniques to keep the graph and our APIs and data in sync.
Communicating the graph to different professionals also has its challenges. Backend engineers and machine learning experts have a hard time understanding knowledge graph quirks. Product people accept it only if it creates a clear improvement for customers. How do you reconcile them all?
Enterprise architecture for big data projects
solution architecture,big data,hadoop,hive,hbase,impala,spark,apache,cassandra,SAP HANA,Cognos big insights
Find the answers to:
Why go semantic?
Should i use RDF or OWL?
What is the difference, what is the link?
Did you say smart data?
In this presentations you can check RDF Integration examples, learn about Ontologies and OWL
By Tara Raafat, (PhD) Chief Ontologist at Mphasis.
The first workshop of the series "Services to support FAIR data" took place in Prague during the EOSC-hub week (on April 12, 2019).
Speaker: Maajke the Jong
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.
The Business Case for Semantic Web Ontology & Knowledge GraphCambridge Semantics
In this webinar Mark Wallace, Ontologist & Developer, Semantic Arts, and Thomas Cook, Director of Sales AnzoGraph DB, Cambridge Semantics, explore the benefits of building a Semantic Knowledge Graph with RDF*, wrapping up with an airline data demo that illustrates the value of schema, inference and reasoning in it.
What is Connected Data as a concept? Who is interested in Connected Data? What problems does Connected Data solve? What skills are used in Connected Data?
Connected Data as of July 2017 has been running for over a year with very successful conference and 9 meetups held to date on a range of topics. These have included Knowledge Representation, Semantics, Linked Data, Graph Databases, Ontology development and use cases and industry verticals including recommendations, telecoms and finance. Yet the group has never had a particularly formal terms of reference or description defining what Connected Data actually means. Some would say this is something of a irony for a group so focused on semantics, schemas, definitions & structure!
This is an attempt (with some humour and something of journey included in it) to achieve something resembling a definition and terms of reference for the group.
Sigma EE: Reaping low-hanging fruits in RDF-based data integrationRichard Cyganiak
A presentation I gave at I-Semantics 2010 on Sigma EE, an RDF-based data integration front-end.
Sigma EE is now available for download here: http://sig.ma/?page=help
Large corporations have to master vast amounts of heterogeneous data in order to stay competitive. While existing approaches have attempted to consolidate and manage the data by forcing it into a single shared data model, data lakes recently emerged that instead provide a central storage point for holding all data sets in their original form.
In this talk, we present eccenca CorporateMemory, which extends the data lake paradigm with a semantic integration layer for managing diverse, but semantically enriched data. eccenca CorporateMemory builds an extensible knowledge graph that employs RDF vocabularies for transforming and linking multiple datasets in order to generate an integrated semantic understanding of the data.
Robert Isele | Head of Data Integration Unit at eccenca GmbH
Presentation at Semantics 2016 in Leipzig in the context with the results of the LEDS project
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.
Open Data and News Analytics Demo from the 4th Sofia Open Data & Linked Data meetup
http://www.meetup.com/Sofia-Open-Data-Linked-Data-Meetup/events/228747999/
Mar'2016, Sofia | BG
GraphDB Cloud: Enterprise Ready RDF Database on DemandOntotext
GraphDB Cloud is an enterprise grade RDF graph database providing high-performance querying over large volumes of RDF data. On this webinar, Ontotext demonstrates how to instantly create and deploy a fully managed Graph Database, then import & query data with the (OpenRDF) GraphDB Workbench, and finally explore and visualize data with the build in visualization tools.
When we set out to build a knowledge graph at Zalando, most people did not know how to build one, or considered machine learning as the better solution. However, endorsement from upper management led to the current project, where we use ontologies to improve the customer search and browsing experience.
There are many unique things about the way we built our ontology for Enterprise purposes. Our ontology is peer-reviewed, use case-driven, and we apply special techniques to keep the graph and our APIs and data in sync.
Communicating the graph to different professionals also has its challenges. Backend engineers and machine learning experts have a hard time understanding knowledge graph quirks. Product people accept it only if it creates a clear improvement for customers. How do you reconcile them all?
Enterprise architecture for big data projects
solution architecture,big data,hadoop,hive,hbase,impala,spark,apache,cassandra,SAP HANA,Cognos big insights
Find the answers to:
Why go semantic?
Should i use RDF or OWL?
What is the difference, what is the link?
Did you say smart data?
In this presentations you can check RDF Integration examples, learn about Ontologies and OWL
By Tara Raafat, (PhD) Chief Ontologist at Mphasis.
The first workshop of the series "Services to support FAIR data" took place in Prague during the EOSC-hub week (on April 12, 2019).
Speaker: Maajke the Jong
Linked data the next 5 years - From Hype to ActionAndreas Blumauer
How can we shape the future of Linked Data and the Semantic Web, to make it even more widely spread in enterprises and other organizations? Which developments around linked data technologies should we expect, and how can we implement various use cases successfully?
Boost your data analytics with open data and public news contentOntotext
Get guidance through the gigantic sea of freely available Open Data and learn how it can empower you analysis of any kind of sources.
This webinar is a live demo of news and data analytics, based on rich links within big knowledge graphs. It will show you how to:
Build ranking reports (e.g for people and organisations)
View topics linked implicitly (e.g. daughter companies, key personnel, products …)
Draw trend lines
Extend your analytics with additional data sources
Evidence suggests that the track record of MDM (Master Data Management) initiatives is not very good. Traditional MDM is often a costly, time-consuming, IT-driven activity that is disconnected from business goals and stakeholders. Even MDM projects that initially meet their goals often suffer during sustainment, or are limited to specific divisions and fail to provide value for the rest of the organization.
This webinar will:
- Review the technical and business challenges associated with the traditional MDM lifecycle
- Explain why the technologies and conventional wisdom associated with MDM do not seem to be working
- Discuss use cases of organizations who have achieved success by adopting a new, iterative approach called "streamlined MDM"
New Trends in Data Management in the Information Industries Matt Turner
Presentation from the Copyright Clearance Center Distinguished Speaker Series presentation February 26th, 2015.
As the publishing industry is transforming from form based, single purpose products to information providers focused on the curation of data and content tailoring its delivery to the role, action and location of the users, there has been a parallel transformation in the management of the data and content that are the raw materials for these products.
Matt Turner, MarkLogic’s CTO for Media and Publishing, will talk about the new generation of information management technology focusing on how they are helping transform the information industries and revolutionize how people think about managing data and content.
Topic that will be covered include NoSQL / new generation databases, search, and semantic technology and information product trends with example of innovative teams leveraging these new capabilities.
The following brief details the use of linked data to connect various high quality data sets produced by the U.S. Environmental Protection Agency. Linked data is an open standards way to publish and consume data. Using a linked data approach and the REST API, developers, scientists, and the public can more easily find, access and re-use authoritative data published by the EPA.
3 Round Stones Briefing to U.S. EPA's Chief Data Scientist on Open DataBernadette Hyland-Wood
The following is technical brief to U.S. EPA's Chief Data Scientist on open data information architecture, the use of Linked Data and the EPA Linked Data Management Service. The briefing was held in February 2016 and was educational in nature.
This presentation starts off by discussing powerful examples of The Power of Data and the benefits of Data Driven architectures. A Data Governance program is important for the success of Data Driven architectures. We then discuss the challenges of implementing a Data Governance framework on a Big Data Data Lake with open source software including DataPlane, Apache Atlas and Apache Ranger. And finally, we discuss the importance of the democratization of data and the switching to a speed of thought framework with Hive LLAP.
Transforming Data Management and Time to Insight with Anzo Smart Data Lake®Cambridge Semantics
This webinar is targeted to Federal Government CIOs and
staff that are researching enterprise data management and
mining tools to help them understand how Smart Data Lakes
enable a viable mechanism for addressing their top priorities.
Insight Platforms Accelerate Digital TransformationMapR Technologies
Many organizations have invested in big data technologies such as Hadoop and Spark. But these investments only address how to gain deeper insights from more diverse data. They do not address how to create action from those insights.
Forrester has identified an emerging class of software—insight platforms—that combine data, analytics, and insight execution to drive action using a big data fabric.
In this presentation, our guest, Forrester Research VP and Principal Analyst, Brian Hopkins, will:
o Present Forrester's recent research on insight platforms and big data fabrics.
o Provide strategies for getting more value from your big data investments.
MapR will share:
o Examples of leading companies and best practices for creating modern applications.
o How to combine analytics and operations to accelerate digital transformation and create competitive advantage.
This talk was given at SEMANTiCS 2014 in Leipzig. It gives an overview how to develop an enterprise linked data strategy around controlled vocabularies based on SKOS. It discusses how knowledge graphs based on SKOS can extended step by step due to the needs of the organization.
What’s the problem? The data is in silos. Business and IT are both demanding a unified view of data to help provide solutions to today’s business challenges, but you can’t use the tools and technologies that created the problem to solve the problem. Enter the Multi-Model database. In this session John Biedebach introduces a trusted and secure approach to data integration using Multi-Model databases. The data we want to integrate has already been modeled, so we’ll discuss how to load information as-is into a Multi-Model database to leverage the models that already exist in the data. We’ll then apply our own models to our data in place to rapidly deliver answers to business questions while providing value from harmonized information directly to consumers. We’ll also discuss the characteristics of a Multi-Model database and the benefits of a Multi-Model approach, including:
How to get unified views across disparate data models and formats within a single database
The benefits of a single product vs multi-product Multi-Model approach to data integration
The importance of agility in data access and delivery through APIs, interfaces, and indexes
How to scale a multi-model database while still providing ACID capabilities and security
How to determine where a multi-model database fits in your existing architecture
Transforming your application with ElasticsearchBrian Ritchie
Have an existing application that needs search super powers? Or are ad hoc searches melting your SQL Server? Either way, this is the talk for you. We will explore search enabling an existing application - from data modeling to retrieval. In this talk, we will cover data modeling for search, connecting ElasticSearch to your data pipeline, building a search API and connecting to an Angular web site. Presented at Code on the Beach 2018
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/
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.
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.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
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
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
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.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
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.
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.
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.
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.
?How do semantic partners differ from ML?
^^^add analytic animation here
ML triple stores enable & complement many diff analytics
Mach learn + NLP > entity extract > store in ML
Triples & inferencing > create knowledge graphs & support data mining & analytics
Let’s talk just a bit more about terminology as the semantics of semantics can get messy…
From our perspective, MarkLogic is a document oriented database. It also has a built-in triple store. It also serves as a precursor to other capabilities.
A triple store can serve as a knowledge graph with facts and relationships about billions of things.
You can also mine data in MarkLogic to do predictive analytics.
MarkLogic also works with partners such as SmartLogic to do entity extraction. When you take free text and extract facts about people, places, and things, the unstructured data becomes machine readable.
This is the basis for natural language processing, or NLP.
NLP, machine learning, and pattern recognition fall into the realm of cognitive computing, and all of this is encroaching into the territory of AI.
You guys recognize these logos?
OF COURSE! Everybody knows “ENTERTAINMENT COMPANY”
Actually, the entertainment companies that are our customers, and those we hope will honor us by becoming customers,
…are doing or looking to do similar things with semantics, albeit in their own way…so we talk about them as a group in this presentation.
As David Gorbet said in his keynote, we’re helping enterprises
See their entire product and customers through intelligence search
Understand their production and distribution processes through a Semantic Metadata Hub
Deliver customized, targeted content and user experience through Dynamic Semantic Publishing
Maintain a valuable engagement with customers through semantically driven Recommendations
AND assess business risks by leveraging semantics for Compliance
The goal of this first session is to de-mystify "Semantics".
Some people are put off by the notion that semantics is somehow magical, or at least enormously complicated.
Semantic technologies can be very powerful, but there's no magic here – just science.
By a show of fingers – where 0 is "I don’t know what a triple is" and 10 is "I have a PhD in Ontologies" – how much do you know about Semantic technologies?
I see some 7s and 8s – OK, I'll go through this section quite quickly.
For the 1s and 2s, I'll define some basic terms and give you a general idea of what we mean by Semantics in this context.
BBC – DSP
BSI – Semantic Search
InfoBox
There’s a lot you can do with JUST triples, but the real magic of semantics comes when you use triples alongside documents.
Here, you can see a document as Marklogic sees it. A document is stored as XML or JSON, which is a hierarchical tree format.
Documents are schema-agnostic, human-readable, and don’t carry all of the entity integrity constraints that you had with a relational model.
You can do a lot with documents, but even documents can fall short when it comes to optimizing for facts and relationships, which are best stored in a graph model as triples.
Here, you can see a graph formed by triples about a particular video title.
In this graph we know that a title not only has this metadata, but the title has characters, etc.
With a single query, you can bring back the document, parts of the graph, or both and have it all materialize at runtime.
This “multi-model” view of data provides more flexibility and agility than any other model.
If you want to go into more detail about how semantics helps with classification
Mix'n'Match documents and triples
There’s a lot you can do with JUST triples, but the real magic of semantics comes when you use triples alongside documents.
Here, you can see a document as Marklogic sees it. A document is stored as XML or JSON, which is a hierarchical tree format.
Documents are schema-agnostic, human-readable, and don’t carry all of the entity integrity constraints that you had with a relational model.
You can do a lot with documents, but even documents can fall short when it comes to optimizing for facts and relationships, which are best stored in a graph model as triples.
Here, you can see a graph formed by triples about a particular video title.
In this graph we know that a title not only has this metadata, but the title has characters, etc.
With a single query, you can bring back the document, parts of the graph, or both and have it all materialize at runtime.
This “multi-model” view of data provides more flexibility and agility than any other model.
If you want to go into more detail about how semantics helps with classification
There’s a lot you can do with JUST triples, but the real magic of semantics comes when you use triples alongside documents.
Here, you can see a document as Marklogic sees it. A document is stored as XML or JSON, which is a hierarchical tree format.
Documents are schema-agnostic, human-readable, and don’t carry all of the entity integrity constraints that you had with a relational model.
You can do a lot with documents, but even documents can fall short when it comes to optimizing for facts and relationships, which are best stored in a graph model as triples.
Here, you can see a graph formed by triples about a particular video title.
In this graph we know that a title not only has this metadata, but the title has characters, etc.
With a single query, you can bring back the document, parts of the graph, or both and have it all materialize at runtime.
This “multi-model” view of data provides more flexibility and agility than any other model.
If you want to go into more detail about how semantics helps with classification
There’s a lot you can do with JUST triples, but the real magic of semantics comes when you use triples alongside documents.
Here, you can see a document as Marklogic sees it. A document is stored as XML or JSON, which is a hierarchical tree format.
Documents are schema-agnostic, human-readable, and don’t carry all of the entity integrity constraints that you had with a relational model.
You can do a lot with documents, but even documents can fall short when it comes to optimizing for facts and relationships, which are best stored in a graph model as triples.
Here, you can see a graph formed by triples about a particular video title.
In this graph we know that a title not only has this metadata, but the title has characters, etc.
With a single query, you can bring back the document, parts of the graph, or both and have it all materialize at runtime.
This “multi-model” view of data provides more flexibility and agility than any other model.
If you want to go into more detail about how semantics helps with classification
There’s a lot you can do with JUST triples, but the real magic of semantics comes when you use triples alongside documents.
Here, you can see a document as Marklogic sees it. A document is stored as XML or JSON, which is a hierarchical tree format.
Documents are schema-agnostic, human-readable, and don’t carry all of the entity integrity constraints that you had with a relational model.
You can do a lot with documents, but even documents can fall short when it comes to optimizing for facts and relationships, which are best stored in a graph model as triples.
Here, you can see a graph formed by triples about a particular video title.
In this graph we know that a title not only has this metadata, but the title has characters, etc.
With a single query, you can bring back the document, parts of the graph, or both and have it all materialize at runtime.
This “multi-model” view of data provides more flexibility and agility than any other model.
If you want to go into more detail about how semantics helps with classification
We can think of "Order", "Order associated with App1" as metadata; "extended" because we can extend the link from App1 to "application that requires TopSecret".
International Classification of Diseases, a set of codes used by physicians, hospitals, and allied health workers to indicate diagnosis for all patient encounters.
International Classification of Diseases, a set of codes used by physicians, hospitals, and allied health workers to indicate diagnosis for all patient encounters.
The goal of this first session is to de-mystify "Semantics".
Some people are put off by the notion that semantics is somehow magical, or at least enormously complicated.
Semantic technologies can be very powerful, but there's no magic here – just science.
By a show of fingers – where 0 is "I don’t know what a triple is" and 10 is "I have a PhD in Ontologies" – how much do you know about Semantic technologies?
I see some 7s and 8s – OK, I'll go through this section quite quickly.
For the 1s and 2s, I'll define some basic terms and give you a general idea of what we mean by Semantics in this context.