The value of                               Structured Data                               in Content Management Systems    ...
The key goals of your website  1. Capture new customers  2. Engage your customers  3. Retain visitors and inspire loyalty
«Structured Data»?
John works lives in the UK. He is an engineer and works for Nike. He was 42 years old in 2011.Margareth works in Spain. Sh...
John       Engineer     42 years     Cycling    US          NikeMargaret   Analyst      Born 1969    Rowing     Spain     ...
Name       Position     Age          Interest   Country     CompanyJohn       Engineer     42 years     Cycling    US     ...
Name       Position     Birth        Interest   Country     CompanyJohn       Engineer     01.02.1969   Cycling    US     ...
Name       Position     Birth        Interest   Country     CompanyJohn       Engineer     01.02.1969   Cycling    US     ...
PEOPLE                                             COUNTRYName           Position   Birth            Company   Interest   ...
«Structured data» in CMS systems?
TAG                                  TAG                                  TAG                                        TAG  ...
How can Structured Data  improve your CMS?
Topics                                     •   Navigation                                     •   Multichannel publishing ...
Tree-based navigation               Region     City     Activity                 West                Rafting             R...
Relation based navigation                            DEMO
Multichannel publication      CMS                      Different                               HTML Layouts               ...
DEMO
Social collaboration• Social data is a  network of relations.• If your Data Model  support relations,  you can model socia...
Social collaboration                 Communicate, Collaborate, Connect• Collaboration platform for   – 2 500 schools + 4 m...
Search Engine Optimization
Without semantic tags  [H1]                              [Blue]  text                               text                  ...
With semantic tagsProduct                         Phone Name                           Color                              ...
www.schema.orgDEMO
Engage you customersTREND 1: Customers land directly on one of your productpages after searching for it in one of the sear...
Web Applications• Business processes moves to the web• Websites are becoming Web Applications• Increased need for data int...
web av data
Integration and Data Sharing  through Data endpoints
«A protocol for sharing and updatingstructured data between applications.»
Ecobox project database                NORWEGIAN STATE HOUSING BANK      OData     Endpoint                               ...
Topics                                        Navigation                                        Multichannel publishing ...
Capture                                SEO / Rich snippets / Data sharing                                        Engage   ...
The value of structured data
The value of structured data
The value of structured data
The value of structured data
The value of structured data
The value of structured data
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The value of structured data

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Our slides from the presentation I held at the Gilbane Boston Conference 2012. Topic: The value of structured data in Content Management Systems.

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  • Ok, so why do I want to talk about Structured Data.I want to talk about Structured Data because it is directly linked to the key goals of most websites:
  • Unstructured data in this context, is just plain text.Computers are not good at understanding text and language. They are super fast, but has little value use as long as they do not understand the data.To help them we add structure.
  • We organize data into columns
  • Tables where each column containing specific data
  • We introduce datatypes and rules for the dataformat
  • We normalize the data to ensure consitency and avoid repeating the same data over and over again, like the company name for instands
  • We split the data into tables and introduce entity types and link them with releations. All in the purpose of making the computer understand the data, so it can use the data effectively, analyse, manipulate it, and generate real value from contents of data.
  • So, what about structured data in CMS systems?
  • DocumentsHiererchyDocument typesDocument fieldsMeta Tags Tags provide additional meta data, and can be used to indirectly relate content by tagging both witn the same tag.But tags do not give the relation a specific meaning. It does not specify that the relation between a person and a company is employment.To to that you need to introduce direct and typed relations, where each type of relation has a spesific meaning.
  • Men du harogså data om de besøkende. Sådeterikkenok å bare bringedataenetiloverflaten. Du måpersonaliseredetogtilpassedet den individuellebrukeren. Systemetmåkunnebrukebrukrensprofilogpreferansertil å presentereinnholdet I riktigcontekst. Ogdetspennerfra å tilpassesegtilbrukrensspesifikkebrukerenhet, entendetermobil, tablet ellertvogsettesammeninnholdsomer relevant for deresprofil. There is also data about the user. So it is notenough to just bring it to the surface. You need to personalize it and adapt it to the user. Your systems must be able react on the identity of the user, adapt to the users preferences and present content for the right context. It ranges from adapting to the specific device she or he is using, to composing data that is relevant to their profile.
  • We among the first to implement this auto
  • I
  • The value of structured data

    1. 1. The value of Structured Data in Content Management Systems Ole Gulbrandsen CTO Webnodes ole@webnodes.comGILBANE CONFERENCE Boston - 2012 www.webnodes.com
    2. 2. The key goals of your website 1. Capture new customers 2. Engage your customers 3. Retain visitors and inspire loyalty
    3. 3. «Structured Data»?
    4. 4. John works lives in the UK. He is an engineer and works for Nike. He was 42 years old in 2011.Margareth works in Spain. She likes rowing. She works for Nike too and is a financial analyst.Ronald works for Nike too, but i Norway. He is a shop assistant. His hobby is cycling. Bert is acleaner from United Kingdom. He loves painting, and works in Hewlet Packard. Sofie likesantiques and lives in Australia where she works for the same company as Bert. Margareth is fiveyears older than John. Ronald is 30 and 3 years older than Bert. John works lives in the UK. He isan engineer and works for Nike. He was 42 years old in 2011. Margareth works in Spain. Shelikes rowing. She works for Nike too and is a financial analyst. Ronald works for Nike too, but iNorway. He is a shop assistant. His hobby is cycling. Bert is a cleaner from United Kingdom. Heloves painting, and works in Hewlet Packard. Sofie likes antiques and lives in Australia where sheworks for the same company as Bert. Margareth is five years older than John. Ronald is 30 and 3years older than Bert. John works lives in the UK. He is an engineer and works for Nike. He was42 years old in 2011. Margareth works in Spain. She likes rowing. She works for Nike too and is afinancial analyst. Ronald works for Nike too, but i Norway. He is a shop assistant. His hobby iscycling. Bert is a cleaner from United Kingdom. He loves painting, and works in Hewlet Packard.Sofie likes antiques and lives in Australia where she works for the same company as Bert.Margareth is five years older than John. Ronald is 30 and 3 years older than Bert. John workslives in the UK. He is an engineer and works for Nike. He was 42 years old in 2011. Margarethworks in Spain. She likes rowing. She works for Nike too and is a financial analyst. Ronald worksfor Nike too, but i Norway. He is a shop assistant. His hobby is cycling. Bert is a cleaner fromUnited Kingdom. He loves painting, and works in Hewlet Packard. Sofie likes antiques and livesin Australia where she works for the same company as Bert. Margareth is five years older thanJohn. Ronald is 30 and 3 years older than Bert. John works lives in the UK. He is an engineer andworks for Nike. He was 42 years old in 2011. Margareth works in Spain. She likes rowing. Sheworks for Nike too and is a financial analyst. Ronald works for Nike too, but i Norway. He is a
    5. 5. John Engineer 42 years Cycling US NikeMargaret Analyst Born 1969 Rowing Spain NikeRonald Engineer 34 years Cycling UK HPBert Cleaner 28 years Painting Australia HPSofia Accountant Born 12/79 Antiques US NikeJohn Engineer 42 years Cycling US NikeMargaret Analyst Born 1969 Rowing Spain NikeRonald Engineer 34 years Cycling UK HPBert Cleaner 28 years Painting Australia HPSofia Accountant Born 12/79 Antiques US NikeJohn Engineer 42 years Cycling US NikeMargaret Analyst Born 1969 Rowing Spain NikeRonald Engineer 34 years Cycling UK HPBert Cleaner 28 years Painting Australia HPSofia Accountant Born 12/79 Antiques US Nike
    6. 6. Name Position Age Interest Country CompanyJohn Engineer 42 years Cycling US NikeMargaret Analyst Born 1969 Rowing Spain NikeRonald Engineer 34 years Cycling UK HPBert Cleaner 28 years Painting Australia HPSofia Accountant Born 12/79 Antiques US NikeJohn Engineer 42 years Cycling US NikeMargaret Analyst Born 1969 Rowing Spain NikeRonald Engineer 34 years Cycling UK HPBert Cleaner 28 years Painting Australia HPSofia Accountant Born 12/79 Antiques US NikeJohn Engineer 42 years Cycling US NikeMargaret Analyst Born 1969 Rowing Spain NikeRonald Engineer 34 years Cycling UK HP
    7. 7. Name Position Birth Interest Country CompanyJohn Engineer 01.02.1969 Cycling US NikeMargaret Analyst 03.02.1969 Rowing Spain NikeRonald Engineer 02.12.1975 Cycling UK HPBert Cleaner 02.12.1971 Painting Australia HPSofia Accountant 02.12.1979 Antiques US NikeJohn Engineer 01.02.1969 Cycling US NikeMargaret Analyst 03.02.1969 Rowing Spain NikeRonald Engineer 02.12.1975 Cycling UK HPBert Cleaner 02.12.1971 Painting Australia HPSofia Accountant 02.12.1979 Antiques US NikeJohn Engineer 01.02.1969 Cycling US NikeMargaret Analyst 03.02.1969 Rowing Spain NikeRonald Engineer 02.12.1975 Cycling UK HP
    8. 8. Name Position Birth Interest Country CompanyJohn Engineer 01.02.1969 Cycling US NikeMargaret Analyst 03.02.1969 Rowing Spain NikeRonald Engineer 02.12.1975 Cycling UK HPBert Cleaner 02.12.1971 Painting Australia HPSofia Accountant 02.12.1979 Antiques US NikeJohn Engineer 01.02.1969 Cycling US NikeMargaret Analyst 03.02.1969 Rowing Spain NikeRonald Engineer 02.12.1975 Cycling UK HPBert Cleaner 02.12.1971 Painting Australia HPSofia Accountant 02.12.1979 Antiques US NikeJohn Engineer 01.02.1969 Cycling US NikeMargaret Analyst 03.02.1969 Rowing Spain NikeRonald Engineer 02.12.1975 Cycling UK HP
    9. 9. PEOPLE COUNTRYName Position Birth Company Interest Country ID NameJohn 1 01.02.1969 1 2 2 1 AustraliaMargaret 2 01.02.1969 1 2 3 2 UKRonald 2 01.02.1969 2 4 4 3 USBert 4 01.02.1969 2 3 2 4 PaintingSofia 3 01.02.1969 1 1 1 POSITION COMPANY INTERESTID Name ID Name ID Name Sport1 Engineering 1 Hewlett Packard Cycling True 12 Analytics 2 Nike 2 Antiques False3 Accounting 3 Rowing True4 Cleaning 4 Painting False
    10. 10. «Structured data» in CMS systems?
    11. 11. TAG TAG TAG TAG TAG TAGPages are Generated Views of the content“Manage content, not pages”
    12. 12. How can Structured Data improve your CMS?
    13. 13. Topics • Navigation • Multichannel publishing • Social collaboration • E-commerce & BI • Personalized content • Web Applications • SEO & Schema.org • Integration and data sharing • Semantic WebOle Gulbrandsen – ole@webnodes.com www.webnodes.com
    14. 14. Tree-based navigation Region City Activity West Rafting Rafting Oslo West East Skiing Skiing Oslo Explore Hamar EastNorway.com North Biking Biking Hamar Biking in Hamar North South Hiking Hiking South
    15. 15. Relation based navigation DEMO
    16. 16. Multichannel publication CMS Different HTML Layouts for devices«One system» &«One data source»for all devices Differentand all formats Data Formats for App frameworks in tablets & mobiles
    17. 17. DEMO
    18. 18. Social collaboration• Social data is a network of relations.• If your Data Model support relations, you can model social graphs directly in your CMS and integrate it with your content.
    19. 19. Social collaboration Communicate, Collaborate, Connect• Collaboration platform for – 2 500 schools + 4 mill users• All data and functionality in one CMS• Seamless integration of content and social data• E-Commerce• Unified access system on all content• Multiple devices, Multiple formats
    20. 20. Search Engine Optimization
    21. 21. Without semantic tags [H1] [Blue] text text [Red] text [Image]240x130px [Black] text [Bold] text
    22. 22. With semantic tagsProduct Phone Name Color PriceProduct Image Currency Stock Status
    23. 23. www.schema.orgDEMO
    24. 24. Engage you customersTREND 1: Customers land directly on one of your productpages after searching for it in one of the search enginesTREND 2: Customers use your search for navigating,not your menus and linksConsequence for your website: • Relation-based navigation • Product recommendations • Accurate and faceted search • Seamless transition between menus and searching
    25. 25. Web Applications• Business processes moves to the web• Websites are becoming Web Applications• Increased need for data integration and sharing-> All points to the need for Structured Data
    26. 26. web av data
    27. 27. Integration and Data Sharing through Data endpoints
    28. 28. «A protocol for sharing and updatingstructured data between applications.»
    29. 29. Ecobox project database NORWEGIAN STATE HOUSING BANK OData Endpoint FURTHER CONNECTING TO 13 OTHER WEBSITES GOVERMENTAL INITIATIVE ABOUT ENERGY EFFICIENT HEATING
    30. 30. Topics  Navigation  Multichannel publishing  Social collaboration  E-commerce & BI  Personalized content  Web Applications  SEO & Schema.org  Integration and data sharing  Semantic WebOle Gulbrandsen – ole@webnodes.com www.webnodes.com
    31. 31. Capture SEO / Rich snippets / Data sharing Engage Navigation / Richer clients / Search Retain Social collaboration / Personalized content / BIOle Gulbrandsen – ole@webnodes.com www.webnodes.com

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