Fluid Topics - Breaking the silos
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Breaking the silos BUILDING YOUR KNOWLEDGE GRAPH LAVACON – PORTLAND 2014/10
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! Data Management
enrichment integration search
! Our mission is to help organizations create value with their data
ANTIDOT
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2 products
AIF – Antidot Information Factory Data integration: cleanse, transform, enrich and link data and documents to create business information.
AFS – Antidot Finder Suite The semantic search engine for creating rich, relevant applications and power your sites.
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Augmented Customer Support
Fluid Topics is a complete solution to deliver your documentation and technical content online ! A turnkey portal for searching,
browsing and reading
! Offering value added features: comments, bookmarks, alerts, feedbacks, personal books creation…
! Designed for PCs and tablets
! With a full-featured back-office to manage and analyze
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KNOWLEDGE GRAPHS
THE CONCEPTUAL FRAMEWORK
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Knowledge Object
EINSTEIN
Born in: Ulm, Germany
Awards: Nobel Prize in P…
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Graph
EINSTEIN
ULM POP
ULM
ULM UNIV
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KG
Knowledge
+ Links -----------------------------
= Knowledge Graph
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LINKED DATA
THE TECHNICAL FRAMEWORK
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Linked Data is • a method of publishing structured data so that it can be
interlinked • in order to create a decentralized knowledge base across
the Web • in which the interest of each piece is made more useful by
additional data.
ULM
located Baden-Württemberg
123 672
popula+on
www.ulm.de Web site
Sources on the Web
place of birth
born
March 14th 1879
ULM
Einstein
Source B
Nobel Prize in Physics
Theory of relativity invented
awarded
Source A
Einstein
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! Semantic Web / Linked Data § Designed by W3C for over 12 years § Open, sustainable § Scalable, reversible
! Ecosystem of protocols and tools
Web 3.0
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The Semantic Web Stack
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Linked Data on the Web
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WRITING DOCUMENTATION
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Why
Why do we write documentation?
Because…
! We must! Everybody does
! Regulatory or legal constraints
! We love that! A nice doc is so cool
! To serve users: clients, support agents... (they can use the product, reduce support costs)
! To formalize and convey knowledge
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When
Produc=on
Marke=ng
Tech Doc
Sales R&D
Idea Proto
Technical documentation is:
! Formal
! Pre conceived (at the same time the product is designed)
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Your Product Informa/on Corpus
Product Information
R&D Prod Sales Support
PLM Exper=se
Training, Docs, KB, Wikis, Q&A, Forums, Tickets
PIM/ERP, Catalog, Tech Doc
Marke=ng, CRM, WP, fact sheets
+ Analy=cs: usage, sen=ment analysis, hot topics, weak signals…
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The Challenge
Your Product Informa/on Corpus
How can we take advantage of this wealth of information?
Create Knowledge and make it accessible:
! Support agents, Partners, End-users
! Self-service portal, within your helpdesk soft
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Let’s build a
Knowledge Graph
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LINKING PRODUCT INFORMATION
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What we need to do
Break the silos: create links between data
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What we need to do
Link selected product and support related data in order to create a comprehensive knowledge graph
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What we need to do
Break the silos: create links between data
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How?
When data is structured
! Look for “join” attributes § Identifiers: code, reference, email address, UID, …
§ Names: people, organization, product, …
XYZ
XYZ
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How?
When data is structured
! Need for data normalization § Leverage existing reference materials
§ Automatically create some based on content (eg: create taxonomy of products from the ERP)
XYZ
#XY-Z
XT
XY XY.U XY.Z
…
…
XY.Z XY.Z
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How?
When content is un-structured, we need to enrich it and create metadata
! Text-mining, entity extraction
! Classification
! Clusterization
Taxonomies and existing vocabularies are important.
XYZ
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How?
Build the graph ! Run inferences
! Machine learning will help refine
Create and extract knowledge objects from that graph
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How?
! Behind the conceptual graph, a real graph of data
Data graph leveraging ontologies such as DC, foaf, sioc, baetle, doap, goodrela=ons, …
Conceptual graph
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How?
! Behind the conceptual graph, a real graph of data
! It requires advanced technologies and a little bit of black magic
! You need to understand what you do and to master the technologies
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KG and Tech Doc
What is the role of technical documentation in all this Knowledge Graph and Linked Data approach?
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KG and Tech Doc
Technical Documentation and reference metadata provide a skeleton to build the KG
Tech Doc is controlled, certified, up to date, versioned, … TRUSTABLE
Metadata are key(s) - Tech Doc has plenty of them
• Product names, ranges, versions
• Taxonomies for classification
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CONCLUSION
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CONCLUSION
Because Tech Writers are information professionals, they have a huge opportunity to lead the innovation.
Advice: invest in your metadata, they are the foundation of your future knowledge graph.
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ANTIDOT
Contact: [email protected] http://www.antidot.net @AntidotNet http://www.fluidtopics.com @FluidTopics
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