Download - Fluid Topics - Breaking the silos

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Breaking the silos BUILDING YOUR KNOWLEDGE GRAPH LAVACON – PORTLAND 2014/10


!   Data Management

enrichment integration search

!   Our mission is to help organizations create value with their data

ANTIDOT


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.


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


KNOWLEDGE GRAPHS

THE CONCEPTUAL FRAMEWORK


Knowledge Object

EINSTEIN

Born in: Ulm, Germany

Awards: Nobel Prize in P…


Graph

EINSTEIN

ULM POP

ULM

ULM UNIV


KG

Knowledge

+ Links -----------------------------

= Knowledge Graph


LINKED DATA

THE TECHNICAL FRAMEWORK


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


!   Semantic Web / Linked Data § Designed by W3C for over 12 years § Open, sustainable §  Scalable, reversible

!   Ecosystem of protocols and tools

Web 3.0


The Semantic Web Stack


Linked Data on the Web


WRITING DOCUMENTATION


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


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)


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…


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


Let’s build a

Knowledge Graph


LINKING PRODUCT INFORMATION


What we need to do

Break the silos: create links between data


What we need to do

Link selected product and support related data in order to create a comprehensive knowledge graph


What we need to do

Break the silos: create links between data


How?

When data is structured

!   Look for “join” attributes §  Identifiers: code, reference, email address, UID, …

§  Names: people, organization, product, …

XYZ

XYZ


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


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


How?

Build the graph !   Run inferences

!   Machine learning will help refine

Create and extract knowledge objects from that graph


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


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


KG and Tech Doc

What is the role of technical documentation in all this Knowledge Graph and Linked Data approach?


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


CONCLUSION


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.


ANTIDOT

Contact: [email protected] http://www.antidot.net @AntidotNet http://www.fluidtopics.com @FluidTopics

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Download - Fluid Topics - Breaking the silos

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