SlideShare una empresa de Scribd logo
1 de 68
THERE IS MORE THAN PAGES,
CONTENT AND RECORDS IN THE
WORLD.
SEMANTIC DATA IN TYPO3
SEBASTIAN HELZLE - T3CON 2018
SEMANTIC DATA IN TYPO3 - INTRODUCTION
ABOUT ME
▸Consultant for web development & agile
▸Many years of TYPO3, Neos CMS, Scrum experience
▸Neos core team member
▸@home in
Karlsruhe & Cambodia
▸Hiker & baker
▸@sebobo
SEMANTIC DATA IN TYPO3 - INTRODUCTION
AGENDA
▸Target audience for this talk
▸Why do I talk about this
▸A look into the past & present
▸What you can do now
▸Wishlist for the future
▸Summary
▸Time for questions
TARGET
AUDIENCE FOR
THIS TALK
SEMANTIC DATA IN TYPO3 - TARGET AUDIENCE FOR THIS TALK
DEVS & INTEGRATORS
SEMANTIC DATA IN TYPO3 - TARGET AUDIENCE FOR THIS TALK
EDITORS
SEMANTIC DATA IN TYPO3 - TARGET AUDIENCE FOR THIS TALK
PROJECT MANAGERS
WHY DO I
TALK ABOUT
THIS
FIRST: WHAT IS
SEMANTIC
DATA?
SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC
„It is a conceptual data model in which
semantic information is included. This
means that the model describes the
meaning of its instances.“
https://en.wikipedia.org/wiki/Semantic_data_model
SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC
https://en.wikipedia.org/wiki/Semantic_data_model
„It is a conceptual data model that
includes the capability to express
information that enables other parties to
interpret meaning (semantics) from the
instances, without the need to know the
meta-model.“
MY
EXPERIENCE
SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC
Supporting editors feels good* and you
earn money but it doesn’t create value.
SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC
Editors say TYPO3 is hard to use.
SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC
Onboarding of new editors and team
members takes a lot of time.
SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC
Future extensions of existing features
was sometimes too hard.
SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC
Customer means „X“
→ PO understands „Y“
→ Dev understands „Z“
SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC
Transferred ideas from Neos CMS to
TYPO3 with good results.
SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC
Added semantic data became the basis
for new features which were initially
never defined.
SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC
Goal is to minimize work to create
content and maximize it’s use.
A LOOK INTO
THE PAST
SEMANTIC DATA IN TYPO3 - LOOK INTO THE PAST
This page is a product page because it
uses backend layout “P“.
SEMANTIC DATA IN TYPO3 - LOOK INTO THE PAST
The record is a page because a plugin
renders it based on the url parameters.
SEMANTIC DATA IN TYPO3 - LOOK INTO THE PAST
Events are news.
SEMANTIC DATA IN TYPO3 - LOOK INTO THE PAST
The text & image element is actually a
slide of a banner because its in the top
backend column.
SEMANTIC DATA IN TYPO3 - LOOK INTO THE PAST
Different record types are rendered with
the same plugin and lots of conditions
in the code.
SEMANTIC DATA IN TYPO3 - LOOK INTO THE PAST
You inherit a project and only the
webmaster knows where which record
type actually works.
WHAT YOU
CAN DO NOW
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Create a content architecture.
Text & Image
Employee
Quote
Banner
Form
Blogpost
Productpage
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Optimize overlapping
definitions and connections.
A
B
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Define a user specific
vocabulary with the customer.
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
USER SPECIFIC VOCABULARY EXAMPLES
▸„Banner“ OR „Carousel“ OR „Slider“
▸„Teaser“ OR „Related Content“
▸„Landingpage“ OR „Subhomepage“ OR „Divison Homepage“
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Adapt labels according to
the projects vocabulary:
„Header“ OR „Title“ OR „Leadtext“?
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Create the content elements you need
and disable the rest.
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Use schema.org when thinking about
internal field names and their necessity.
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Example:
Quotation content
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Render microdata and make search
engines happy:
https://developers.google.com/search/docs/guides/search-gallery
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Reuse microdata in Javascript to create
interactivity.
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
If something
behaves like a page,
it should be a page.
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Pages get URLs for
free and appear
in sitemaps.
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Pages are part
of the page tree
and can be
easily found.
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Pages can be
edited like a page!
🤯
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
But also in
list mode.
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Page types (or Doctypes)
can be customized
according to the
projects needs.
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Page types can be
easily identified in
the database and
loaded via
repositories.
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Pages can be
rendered without
plugins.
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Permissions can be
fine tuned for
different page types.
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Search results for
pages can be rendered
depending on the
their type.
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Pages can have
meaningful icons.
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Use category folders
instead of long lists.
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Disable
everything that’s
not necessary.
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Adapt the position and grouping of properties
according to the desired workflow.
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Example:
Combine fields that are needed 95%
of the time into one tab.
SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW
Example:
Editor uses copy & paste from word
→ order fields according to their documents
WISHLIST
FOR THE
FUTURE
SEMANTIC DATA IN TYPO3 - WISHLIST FOR THE FUTURE
No need for extensions to simplify
creation of custom content
and page types.
SEMANTIC DATA IN TYPO3 - WISHLIST FOR THE FUTURE
One easier way to implement Doctypes
in TYPO3
SEMANTIC DATA IN TYPO3 - WISHLIST FOR THE FUTURE
Ability to easily
override all labels
in the editor
SEMANTIC DATA IN TYPO3 - WISHLIST FOR THE FUTURE
Better concepts for grouping related
content.
SEMANTIC DATA IN TYPO3 - WISHLIST FOR THE FUTURE
Example:
Cutting a text in multiple columns & elements still
makes it the same text.
SUMMARY
SEMANTIC DATA IN TYPO3 - SUMMARY
Give all your data meaning.
SEMANTIC DATA IN TYPO3 - SUMMARY
TYPO3 already has lots of capabilities
to do this.
SEMANTIC DATA IN TYPO3 - SUMMARY
It gets easier with every release.
SEMANTIC DATA IN TYPO3 - SUMMARY
Reuse and optimize what you have.
SEMANTIC DATA IN TYPO3 - SUMMARY
Less is more.
ANY
QUESTIONS?
THANKS!
@SEBOBO
FEEL FREE TO CONTACT ME

Más contenido relacionado

Similar a Semantic data in TYPO3 - T3CON18EU

Toc08 Goldthwaite Digitizing Your Backlist
Toc08 Goldthwaite Digitizing Your BacklistToc08 Goldthwaite Digitizing Your Backlist
Toc08 Goldthwaite Digitizing Your Backlisttoc
 
Developing a typo3 template strategy
Developing a typo3 template strategyDeveloping a typo3 template strategy
Developing a typo3 template strategybusynoggin
 
Headless TYPO3 & PWA initiative | Web Camp Venlo 2020
 Headless TYPO3 & PWA initiative | Web Camp Venlo 2020 Headless TYPO3 & PWA initiative | Web Camp Venlo 2020
Headless TYPO3 & PWA initiative | Web Camp Venlo 2020Tomasz Grzemski
 
TYPO3 Headless & PWA - Webinar
TYPO3 Headless & PWA - WebinarTYPO3 Headless & PWA - Webinar
TYPO3 Headless & PWA - WebinarMacopedia
 
Digital Practices - introductions
Digital Practices - introductionsDigital Practices - introductions
Digital Practices - introductionsprisca schmarsow
 
Rank | Analyse | Lead | Search
Rank | Analyse | Lead | SearchRank | Analyse | Lead | Search
Rank | Analyse | Lead | Searchsopekmir
 
Dimensional Fact Model @ BI Academy - 2016
Dimensional Fact Model @ BI Academy - 2016Dimensional Fact Model @ BI Academy - 2016
Dimensional Fact Model @ BI Academy - 2016caccio
 
ITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data Lake
ITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data LakeITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data Lake
ITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data LakeITCamp
 
Datalayer Best Practices with Observepoint
Datalayer Best Practices with ObservepointDatalayer Best Practices with Observepoint
Datalayer Best Practices with ObservepointMike Plant
 
Cato: Magnolia for the OFBiz ERP
Cato: Magnolia for the OFBiz ERPCato: Magnolia for the OFBiz ERP
Cato: Magnolia for the OFBiz ERPMagnolia
 
Continuous delivery for machine learning
Continuous delivery for machine learningContinuous delivery for machine learning
Continuous delivery for machine learningRajesh Muppalla
 
A possible future role of schema.org for business reporting
A possible future role of schema.org for business reportingA possible future role of schema.org for business reporting
A possible future role of schema.org for business reportingsopekmir
 
Business Intelligence Solution Using Search Engine
Business Intelligence Solution Using Search EngineBusiness Intelligence Solution Using Search Engine
Business Intelligence Solution Using Search Engineankur881120
 
Provenance in Production-Grade Machine Learning
Provenance in Production-Grade Machine LearningProvenance in Production-Grade Machine Learning
Provenance in Production-Grade Machine LearningAnand Sampat
 
Adobe Ask the AEM Community Expert Session Oct 2016
Adobe Ask the AEM Community Expert Session Oct 2016Adobe Ask the AEM Community Expert Session Oct 2016
Adobe Ask the AEM Community Expert Session Oct 2016AdobeMarketingCloud
 
WordPress North East (Jan 2021) ~ SEO Fundamentals For WordPress
WordPress North East (Jan 2021) ~ SEO Fundamentals For WordPressWordPress North East (Jan 2021) ~ SEO Fundamentals For WordPress
WordPress North East (Jan 2021) ~ SEO Fundamentals For WordPressDan Taylor
 
Mark logic text analytics
Mark logic text analyticsMark logic text analytics
Mark logic text analyticsFernando Mesa
 

Similar a Semantic data in TYPO3 - T3CON18EU (20)

Toc08 Goldthwaite Digitizing Your Backlist
Toc08 Goldthwaite Digitizing Your BacklistToc08 Goldthwaite Digitizing Your Backlist
Toc08 Goldthwaite Digitizing Your Backlist
 
Developing a typo3 template strategy
Developing a typo3 template strategyDeveloping a typo3 template strategy
Developing a typo3 template strategy
 
Headless TYPO3 & PWA initiative | Web Camp Venlo 2020
 Headless TYPO3 & PWA initiative | Web Camp Venlo 2020 Headless TYPO3 & PWA initiative | Web Camp Venlo 2020
Headless TYPO3 & PWA initiative | Web Camp Venlo 2020
 
TYPO3 Headless & PWA - Webinar
TYPO3 Headless & PWA - WebinarTYPO3 Headless & PWA - Webinar
TYPO3 Headless & PWA - Webinar
 
Digital Practices - introductions
Digital Practices - introductionsDigital Practices - introductions
Digital Practices - introductions
 
Rank | Analyse | Lead | Search
Rank | Analyse | Lead | SearchRank | Analyse | Lead | Search
Rank | Analyse | Lead | Search
 
Dimensional Fact Model @ BI Academy - 2016
Dimensional Fact Model @ BI Academy - 2016Dimensional Fact Model @ BI Academy - 2016
Dimensional Fact Model @ BI Academy - 2016
 
ITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data Lake
ITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data LakeITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data Lake
ITCamp 2019 - Andy Cross - Machine Learning with ML.NET and Azure Data Lake
 
Datalayer Best Practices with Observepoint
Datalayer Best Practices with ObservepointDatalayer Best Practices with Observepoint
Datalayer Best Practices with Observepoint
 
Cato: Magnolia for the OFBiz ERP
Cato: Magnolia for the OFBiz ERPCato: Magnolia for the OFBiz ERP
Cato: Magnolia for the OFBiz ERP
 
Cloud Design Patterns
Cloud Design PatternsCloud Design Patterns
Cloud Design Patterns
 
Online Marketing Audit Example
Online Marketing Audit ExampleOnline Marketing Audit Example
Online Marketing Audit Example
 
Continuous delivery for machine learning
Continuous delivery for machine learningContinuous delivery for machine learning
Continuous delivery for machine learning
 
A possible future role of schema.org for business reporting
A possible future role of schema.org for business reportingA possible future role of schema.org for business reporting
A possible future role of schema.org for business reporting
 
Business Intelligence Solution Using Search Engine
Business Intelligence Solution Using Search EngineBusiness Intelligence Solution Using Search Engine
Business Intelligence Solution Using Search Engine
 
Provenance in Production-Grade Machine Learning
Provenance in Production-Grade Machine LearningProvenance in Production-Grade Machine Learning
Provenance in Production-Grade Machine Learning
 
Adobe Ask the AEM Community Expert Session Oct 2016
Adobe Ask the AEM Community Expert Session Oct 2016Adobe Ask the AEM Community Expert Session Oct 2016
Adobe Ask the AEM Community Expert Session Oct 2016
 
WordPress North East (Jan 2021) ~ SEO Fundamentals For WordPress
WordPress North East (Jan 2021) ~ SEO Fundamentals For WordPressWordPress North East (Jan 2021) ~ SEO Fundamentals For WordPress
WordPress North East (Jan 2021) ~ SEO Fundamentals For WordPress
 
The coding portion of Data Science
The coding portion of Data ScienceThe coding portion of Data Science
The coding portion of Data Science
 
Mark logic text analytics
Mark logic text analyticsMark logic text analytics
Mark logic text analytics
 

Más de Sebastian Helzle

Neos CMS & SEO - The Next Level - NeosCon Dresden 2019
Neos CMS & SEO - The Next Level - NeosCon Dresden 2019Neos CMS & SEO - The Next Level - NeosCon Dresden 2019
Neos CMS & SEO - The Next Level - NeosCon Dresden 2019Sebastian Helzle
 
SEO with NeosCMS - Meet Neos Salzburg 2018
SEO with NeosCMS - Meet Neos Salzburg 2018SEO with NeosCMS - Meet Neos Salzburg 2018
SEO with NeosCMS - Meet Neos Salzburg 2018Sebastian Helzle
 
Continuous relaunch – die einzige konstante ist die Veränderung
Continuous relaunch – die einzige konstante ist die VeränderungContinuous relaunch – die einzige konstante ist die Veränderung
Continuous relaunch – die einzige konstante ist die VeränderungSebastian Helzle
 
Tasty Recipes for Every Day 2016 (Neos)
Tasty Recipes for Every Day 2016 (Neos)Tasty Recipes for Every Day 2016 (Neos)
Tasty Recipes for Every Day 2016 (Neos)Sebastian Helzle
 
Conceptual understanding in development
Conceptual understanding in developmentConceptual understanding in development
Conceptual understanding in developmentSebastian Helzle
 
Improving conceptual understanding in development
Improving conceptual understanding in developmentImproving conceptual understanding in development
Improving conceptual understanding in developmentSebastian Helzle
 
Improving editors' lives with Neos CMS
Improving editors' lives with Neos CMSImproving editors' lives with Neos CMS
Improving editors' lives with Neos CMSSebastian Helzle
 
Testen von TYPO3 CMS/Flow/Neos Anwendungen mit Behat und Dalek.js
Testen von TYPO3 CMS/Flow/Neos Anwendungen mit Behat und Dalek.jsTesten von TYPO3 CMS/Flow/Neos Anwendungen mit Behat und Dalek.js
Testen von TYPO3 CMS/Flow/Neos Anwendungen mit Behat und Dalek.jsSebastian Helzle
 
Continuous delivery with open source tools
Continuous delivery with open source toolsContinuous delivery with open source tools
Continuous delivery with open source toolsSebastian Helzle
 

Más de Sebastian Helzle (11)

Neos CMS & SEO - The Next Level - NeosCon Dresden 2019
Neos CMS & SEO - The Next Level - NeosCon Dresden 2019Neos CMS & SEO - The Next Level - NeosCon Dresden 2019
Neos CMS & SEO - The Next Level - NeosCon Dresden 2019
 
SEO with NeosCMS - Meet Neos Salzburg 2018
SEO with NeosCMS - Meet Neos Salzburg 2018SEO with NeosCMS - Meet Neos Salzburg 2018
SEO with NeosCMS - Meet Neos Salzburg 2018
 
Continuous relaunch – die einzige konstante ist die Veränderung
Continuous relaunch – die einzige konstante ist die VeränderungContinuous relaunch – die einzige konstante ist die Veränderung
Continuous relaunch – die einzige konstante ist die Veränderung
 
Neos CMS and SEO
Neos CMS and SEONeos CMS and SEO
Neos CMS and SEO
 
Ci & proServer
Ci & proServerCi & proServer
Ci & proServer
 
Tasty Recipes for Every Day 2016 (Neos)
Tasty Recipes for Every Day 2016 (Neos)Tasty Recipes for Every Day 2016 (Neos)
Tasty Recipes for Every Day 2016 (Neos)
 
Conceptual understanding in development
Conceptual understanding in developmentConceptual understanding in development
Conceptual understanding in development
 
Improving conceptual understanding in development
Improving conceptual understanding in developmentImproving conceptual understanding in development
Improving conceptual understanding in development
 
Improving editors' lives with Neos CMS
Improving editors' lives with Neos CMSImproving editors' lives with Neos CMS
Improving editors' lives with Neos CMS
 
Testen von TYPO3 CMS/Flow/Neos Anwendungen mit Behat und Dalek.js
Testen von TYPO3 CMS/Flow/Neos Anwendungen mit Behat und Dalek.jsTesten von TYPO3 CMS/Flow/Neos Anwendungen mit Behat und Dalek.js
Testen von TYPO3 CMS/Flow/Neos Anwendungen mit Behat und Dalek.js
 
Continuous delivery with open source tools
Continuous delivery with open source toolsContinuous delivery with open source tools
Continuous delivery with open source tools
 

Último

Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
Vertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsVertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsMiki Katsuragi
 
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdfHyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdfPrecisely
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Mark Simos
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr BaganFwdays
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024Lorenzo Miniero
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 3652toLead Limited
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationSlibray Presentation
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsMark Billinghurst
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024Lonnie McRorey
 
Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubUnleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubKalema Edgar
 
Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Mattias Andersson
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfAddepto
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfAlex Barbosa Coqueiro
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsSergiu Bodiu
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii SoldatenkoFwdays
 
Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Commit University
 
Search Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfSearch Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfRankYa
 
Advanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionAdvanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionDilum Bandara
 

Último (20)

Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
Vertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsVertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering Tips
 
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdfHyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
Hyperautomation and AI/ML: A Strategy for Digital Transformation Success.pdf
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
 
"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan"ML in Production",Oleksandr Bagan
"ML in Production",Oleksandr Bagan
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck Presentation
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR Systems
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024
 
Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubUnleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding Club
 
Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdf
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdf
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platforms
 
DMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special EditionDMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special Edition
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko
 
Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!
 
Search Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfSearch Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdf
 
Advanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionAdvanced Computer Architecture – An Introduction
Advanced Computer Architecture – An Introduction
 

Semantic data in TYPO3 - T3CON18EU

  • 1. THERE IS MORE THAN PAGES, CONTENT AND RECORDS IN THE WORLD. SEMANTIC DATA IN TYPO3 SEBASTIAN HELZLE - T3CON 2018
  • 2. SEMANTIC DATA IN TYPO3 - INTRODUCTION ABOUT ME ▸Consultant for web development & agile ▸Many years of TYPO3, Neos CMS, Scrum experience ▸Neos core team member ▸@home in Karlsruhe & Cambodia ▸Hiker & baker ▸@sebobo
  • 3. SEMANTIC DATA IN TYPO3 - INTRODUCTION AGENDA ▸Target audience for this talk ▸Why do I talk about this ▸A look into the past & present ▸What you can do now ▸Wishlist for the future ▸Summary ▸Time for questions
  • 5. SEMANTIC DATA IN TYPO3 - TARGET AUDIENCE FOR THIS TALK DEVS & INTEGRATORS
  • 6. SEMANTIC DATA IN TYPO3 - TARGET AUDIENCE FOR THIS TALK EDITORS
  • 7. SEMANTIC DATA IN TYPO3 - TARGET AUDIENCE FOR THIS TALK PROJECT MANAGERS
  • 8. WHY DO I TALK ABOUT THIS
  • 10. SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC „It is a conceptual data model in which semantic information is included. This means that the model describes the meaning of its instances.“ https://en.wikipedia.org/wiki/Semantic_data_model
  • 11. SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC https://en.wikipedia.org/wiki/Semantic_data_model „It is a conceptual data model that includes the capability to express information that enables other parties to interpret meaning (semantics) from the instances, without the need to know the meta-model.“
  • 13. SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC Supporting editors feels good* and you earn money but it doesn’t create value.
  • 14. SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC Editors say TYPO3 is hard to use.
  • 15. SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC Onboarding of new editors and team members takes a lot of time.
  • 16. SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC Future extensions of existing features was sometimes too hard.
  • 17. SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC Customer means „X“ → PO understands „Y“ → Dev understands „Z“
  • 18. SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC Transferred ideas from Neos CMS to TYPO3 with good results.
  • 19. SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC Added semantic data became the basis for new features which were initially never defined.
  • 20. SEMANTIC DATA IN TYPO3 - WHY DO I TALK ABOUT THIS TOPIC Goal is to minimize work to create content and maximize it’s use.
  • 22. SEMANTIC DATA IN TYPO3 - LOOK INTO THE PAST This page is a product page because it uses backend layout “P“.
  • 23. SEMANTIC DATA IN TYPO3 - LOOK INTO THE PAST The record is a page because a plugin renders it based on the url parameters.
  • 24. SEMANTIC DATA IN TYPO3 - LOOK INTO THE PAST Events are news.
  • 25. SEMANTIC DATA IN TYPO3 - LOOK INTO THE PAST The text & image element is actually a slide of a banner because its in the top backend column.
  • 26. SEMANTIC DATA IN TYPO3 - LOOK INTO THE PAST Different record types are rendered with the same plugin and lots of conditions in the code.
  • 27. SEMANTIC DATA IN TYPO3 - LOOK INTO THE PAST You inherit a project and only the webmaster knows where which record type actually works.
  • 29. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Create a content architecture. Text & Image Employee Quote Banner Form Blogpost Productpage
  • 30. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Optimize overlapping definitions and connections. A B
  • 31. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Define a user specific vocabulary with the customer.
  • 32. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW USER SPECIFIC VOCABULARY EXAMPLES ▸„Banner“ OR „Carousel“ OR „Slider“ ▸„Teaser“ OR „Related Content“ ▸„Landingpage“ OR „Subhomepage“ OR „Divison Homepage“
  • 33. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Adapt labels according to the projects vocabulary: „Header“ OR „Title“ OR „Leadtext“?
  • 34. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Create the content elements you need and disable the rest.
  • 35. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Use schema.org when thinking about internal field names and their necessity.
  • 36. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Example: Quotation content
  • 37. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Render microdata and make search engines happy: https://developers.google.com/search/docs/guides/search-gallery
  • 38. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Reuse microdata in Javascript to create interactivity.
  • 39. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW If something behaves like a page, it should be a page.
  • 40. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Pages get URLs for free and appear in sitemaps.
  • 41. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Pages are part of the page tree and can be easily found.
  • 42. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Pages can be edited like a page! 🤯
  • 43. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW But also in list mode.
  • 44. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Page types (or Doctypes) can be customized according to the projects needs.
  • 45. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Page types can be easily identified in the database and loaded via repositories.
  • 46. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Pages can be rendered without plugins.
  • 47. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Permissions can be fine tuned for different page types.
  • 48. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Search results for pages can be rendered depending on the their type.
  • 49. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Pages can have meaningful icons.
  • 50. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Use category folders instead of long lists.
  • 51. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Disable everything that’s not necessary.
  • 52. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Adapt the position and grouping of properties according to the desired workflow.
  • 53. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Example: Combine fields that are needed 95% of the time into one tab.
  • 54. SEMANTIC DATA IN TYPO3 - WHAT YOU CAN DO NOW Example: Editor uses copy & paste from word → order fields according to their documents
  • 56. SEMANTIC DATA IN TYPO3 - WISHLIST FOR THE FUTURE No need for extensions to simplify creation of custom content and page types.
  • 57. SEMANTIC DATA IN TYPO3 - WISHLIST FOR THE FUTURE One easier way to implement Doctypes in TYPO3
  • 58. SEMANTIC DATA IN TYPO3 - WISHLIST FOR THE FUTURE Ability to easily override all labels in the editor
  • 59. SEMANTIC DATA IN TYPO3 - WISHLIST FOR THE FUTURE Better concepts for grouping related content.
  • 60. SEMANTIC DATA IN TYPO3 - WISHLIST FOR THE FUTURE Example: Cutting a text in multiple columns & elements still makes it the same text.
  • 62. SEMANTIC DATA IN TYPO3 - SUMMARY Give all your data meaning.
  • 63. SEMANTIC DATA IN TYPO3 - SUMMARY TYPO3 already has lots of capabilities to do this.
  • 64. SEMANTIC DATA IN TYPO3 - SUMMARY It gets easier with every release.
  • 65. SEMANTIC DATA IN TYPO3 - SUMMARY Reuse and optimize what you have.
  • 66. SEMANTIC DATA IN TYPO3 - SUMMARY Less is more.
  • 68. @SEBOBO FEEL FREE TO CONTACT ME

Notas del editor

  1. * Do long-term support for a project * simplify their own future work * easier onboarding for other devs * Help editors
  2. Who wonder if their work in TYPO3 could be easier Who work in teams and have to onboard others Who enjoy better usability
  3. Who are unhappy with the technical debts of older projects Who want to learn more about the capabilities of TYPO3 Who want to create customer centric solutions with great usability
  4. * Depends
  5. Low overall satisfaction Might cost you the next project Bad for community
  6. Great customer feedback Less support needed Developers appreciated advantages of those ideas after initial doubts
  7. And the editors didn’t have to change anything
  8. Not possible to easily see for an editor Hard to debug
  9. * Not much fun with SEO adjustments, caching, search, url generation -> needs lot of glue code
  10. First it’s fast and then it’s a pain 7 years ago it felt smart, now it’s hard to separate it again with thousands of records
  11. * More like a coincidence than semantics
  12. This will break apart
  13. Wouldn’t it be nice if the structure, naming & meaning already give you enough hints?
  14. Each type of content is defined with the customer and the team Focus on the minimum Discuss & document use cases
  15. If two similar types of author elements come up, maybe only one is needed.
  16. When in doubt -> still remove or disable Create glossary if needed Also for localization! Prevent multiple meanings! Enforce vocabulary in ticket system too!
  17. Reduces onboarding time for new editors Reduces confusion during discussions
  18. Technical: prefer flexforms to using real fields -> more flexibility, database doesn’t care, support in TS getting better, not as good for querying No need for many default elements
  19. It’s reusable later
  20. List views, selectors, etc…
  21. Simplifies SEO, Metadata, Backend handling,
  22. No matter whether from Realurl or TYPO3 9 LTS
  23. Simple records can not be edited like a page Customers want to customize their record based articles -> sorry complicated
  24. Much easier to understand what your looking at and find wrong documents
  25. Gives additional semantic data later on for category selectors etc… Could have even more levels depending on amount of pages and subcategories like year or month Categories can be hidden in the url or behave as aggregations or redirect to a filter page with a preset
  26. When in doubt -> still remove or disable Regularly check with the customer in a workshop or via screen sharing what is used and in which way
  27. Reduces onboarding time for new editors Reduces number of clicks and time needed for new content
  28. * Often content types are reused with different meanings because of high cost of implementation
  29. No adding to multiple array to support SOLR etc… No defining of numbered IDs in range of 255 -> makes it hard to create extensions with doctypes
  30. Hard to identify as one entity via the database or other methods Combine the text into one semantic container and give it meaning