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Structured Data for the Financial Industry

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Structured Data for the Financial Industry
The extensions to schema.org and their benefits for:
Ranking | Analytics | Search | Reporting

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Structured Data for the Financial Industry

  1. 1. Ranking | Analytics | Search | Reporting Structured Data for the Financial Industry The extensions to schema.org and their benefits for: Trusted Open Data Ecosystem, September 28, 2017, Madrid, Spain Dr. Mirek Sopek, Dr. Robert Trypuz
  2. 2. 2TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 THE WORKSHOP AGENDA • A Quest for Meaning • On the open web • In the business world • The principle of least power • The rise of schema.org • Intro to schema.org • Under the hood of schema.org • Extending schema.org • Applications of schema.org • Rank • Analytics • Search PART I – THE PRESENT
  3. 3. 3TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 THE WORKSHOP AGENDA • The reporting horizon • The goal – to test the idea of the further simplification of the reporting • The relevant development: • Semantics for XBRL • The movement from within • What we have done so far? • MakoLab POCs & exercises • A vision for the future steps • Discussion PART II – THE FUTURE
  4. 4. The PresentSCHEMA.ORG and its existing applications
  5. 5. 5TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 INTRO A QUEST FOR MEANING ON THE WEB • The Web is (mostly) a Mess • Metadata becomes (very often) Meta-Crap (after: Cory Doctorow*) • There is no such thing as Esperanto of the Web (despite its importance, English is not a lingua franca) • The trust is lost – people of the Web (often) live in echo- chambers THE WEB WAS IN THE DEEP NEED OF A PRAGMATIC APPROACH SHORTLY AFTER THE WEB WAS INVENTED WE NOTICED THAT: * https://www.well.com/~doctorow/metacrap.htm
  6. 6. 6TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 INTRO WEB FULL OF MEANING INVENTION • The “Web Full of Meaning” was invented (a.k.a. the “Semantic Web” or Web 3.0) • Web gurus borrowed a fundamental term from philosophy – ONTOLOGY - to name their Vocabularies. • Using Ontologies (aka Vocabularies) they started to create and promote new models for Data (Linked Data, Graph Data, Smart Data) TO COUNTERBALANCE THE MESS …
  7. 7. 7TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 INTRO DISSATISFACTION • Most of the results were (so far) only good for academic research • Almost none of our ontologies enjoyed wide adoption • Promises to build Web 3.0 quickly turned out to be failed THE WEB WAS IN THE DEEP NEED OF A PRAGMATIC APPROACH HOWEVER…
  8. 8. 8TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 MEANWHILE IN THE BUSINESS WORLD … • ISO20022, FpML, FIX, MISMO, XBRL, DPM, RIXML, IFX, OFX, BPM6, SDMX, SDDS, MDDL, ACORD • FIBO, ACTUS, DPM2ISO, SMCube MULTIPLICITY of STANDARDS and PROJECTS From: Michał Piechocki: „Trusted Open Data Ecosystems” Data Amplified 2016
  9. 9. 9TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 SIR TIM BERNERS LEE • Principle: Powerful languages inhibit information reuse. • Good Practice: Use the least powerful language suitable for expressing information, constraints or programs on the World Wide Web. • Tradeoff: Choosing between languages that can solve a broad range of problems and languages in which programs and data are easily analyzed PRINCIPLE OF LEAST POWER - 1998
  10. 10. 10TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 …EARLY ATTEMPTS TO ACT WITH LESS POWER .. • MCF (Meta Content Framework) – R. Guha 1995-1997 https://en.wikipedia.org/wiki/Meta_Content_Framework • SHOE - Simple HTML Ontology Extensions – Sean Luke, Lee Spector, James Hendler, Jeff Heflin, and David Rager, 1996 https://en.wikipedia.org/wiki/Simple_HTML_Ontology_Extensions • RSS - RDF Site Summary – Dan Libby and Ramanathan V. Guha, 1999 • MICROFORMATS (μF) – a grassroots movement, 2005 https://en.wikipedia.org/wiki/Microformat NONE OF THEM RECEIVED WIDESPREAD ADOPTION !!!!
  11. 11. 11TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 …SO THE SCHEMA.ORG WAS INVENTED ! • Schema.org (2011), sponsored by the most important search engines: Google, Microsoft, Yahoo and Yandex, is a large scale collaborative activity with a mission to create, maintain, and promote schemas for structured data on the WEB pages and beyond. • It contains more than 2000 terms: 753 types, 1207 properties and 220 enumerations. • Schema.org covers entities, relationships between entities and actions. • Today, about 15 million sites use schema.org. Random yet representative crawls (Web Data Commons) show that about 30% of URLs on the web return some form of triples from schema.org. • Many applications from Google (Knowledge Graph), Microsoft (like Cortana), Pinterest, Yandex and others already use schema.org to power rich experiences. • Think of schema.org as a global Vocabulary for the web transcending domain and language barriers. • The principal authors of the schema.org conceptual framework are R. Guha, D. Brickley and P. Mika
  12. 12. 12TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 http://bl.ocks.org/danbri/raw/1c121ea8bd2189cf411c/ WHAT IS SCHEMA.ORG? http://schema.org
  13. 13. 13TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 SCHEMA.ORG USE SIMPLICITY – AN ILLUSTRATION http://finances.makolab.com/HTML/LoanStudents/LoanStudents.html
  14. 14. Under the hoodOF SCHEMA.ORG
  15. 15. 15TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 UNDER THE HOOD OF SCHEMA.ORG • „The driving factor in the design of Schema.org was to make it easy for webmasters to publish their data. In general, the design decisions place more of the burden on consumers of the markup.” R.V. GUHA, D. DAN BRICKLEY, S. MACBETH – „Schema.org - Evolution of Structured Data on the Web” DESIGN DECISIONS • Derived from RDFS (RDF Schema) • Multiple inheritance hierarchy • POLYMORPHIC PROPERTIES - Each property may have one or more types as its domain and its range („domainincludes” and „rangeincludes”) DATA MODEL
  16. 16. 16TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 UNDER THE HOOD OF SCHEMA.ORG USAGE MODELS • Under full control of site/messages/data publishers • Data EMBEDDED into page, data representation or into message markup (HTML, XML) • Harvested during standard crawling, message or data processing SERIALIZATIONS • RDFa - CANONICAL • Microdata (native to HTML5) • JSON-LD
  17. 17. 17TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 UNDER THE HOOD OF SCHEMA.ORG CORE http://schema.org/<term> http://schema.org/<term> HOSTED EXT. http://<ext>.schema.org/<term> http://schema.org/<term> External EXT. http://<ext.domain>/<term> http://<ext.domain>/<term> CORE http://schema.org/Car http://schema.org/Car HOSTED EXT. http://auto.schema.org/Motorcycle http://schema.org/Motorcycle External EXT. http://fibo.org/voc/BusinessEntity http://fibo.org/voc/BusinessEntity EXTENSION MECHANISM: RULES FOR URIs Documentation URI: Canonical URI: Examples: Rules:
  18. 18. 18TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 UNDER THE HOOD OF SCHEMA.ORG <div itemscope itemtype="http://schema.org/BankTransfer"> <h1>If you want to donate</h1> Send <span itemprop="amount" itemscope itemtype="http://schema.org/MonetaryAmount"> <span itemprop="amount">30</span> <span itemprop="currency" content="USD">$</span> </span> via bank transfer to the <span itemprop="beneficiaryBank">European ExampleBank, London</span> Put "<i itemprop="name">Donate wikimedia.org</i>" in the transfer title. </div> EXAMPLES - MICRODATA
  19. 19. 19TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 UNDER THE HOOD OF SCHEMA.ORG <div vocab="http://schema.org" typeof="BankTransfer"> <h1>If you want to donate</h1> Send <span property="amount" typeof="MonetaryAmount"> <span property="amount">30</span> <span property="currency" content="USD">$</span> </span> via bank transfer to the <span property="beneficiaryBank"> European ExampleBank,London</span> Put "<i property=’name’>Donate wikimedia.org</i>" in the transfer title. </div> EXAMPLES - RDFa
  20. 20. 20TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 UNDER THE HOOD OF SCHEMA.ORG <script type="application/ld+json"> {"@context": "http://schema.org/", "@type": "BankTransfer", "name": "Donate wikimedia.org", "amount": { "@type": "MonetaryAmount", "amount": "30", "currency": "USD" }, "beneficiaryBank": "European ExampleBank, London"} </script> EXAMPLES – JSON-LD
  21. 21. 21TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 SCHEMA.ORG VS. ONTOLOGIES AND LINKED DATA • Common elements: a graph data model of typed entities with named properties • Schema.org uses RDFS schema language and JSON-LD and RDFa syntaxes • Schema.org shares (with Linked Data and Ontologies) many of the same goals • Linked data and ontologies have brought to the Web a much smaller number of data sources than Schema.org, but their quality is (often) very high. This opens up many opportunities for combining the two approaches—for example, professionally published ontologies can often authoritatively describe the entities mentioned in Schema.org descriptions from the wider mainstream Web. SIMILARITIES DIFFERENCES • Schema.org's approach can be seen as less noisy and decentralized than Linked Data • Schema.org promotes syntaxes (microdata, RDFa) that are a tradeoff between machine-friendly and human-friendly formats • Linked RDF data publication practices have not been adopted in the Web at large • Schema.org shares the Linked-Data community's skepticism toward the premature ontologies (rule systems, description logics, etc.) found in much of the academic work that is carried out under the Semantic Web banner. • Schema.org avoids assuming that rule-based processing will be commonplace • Schema.org’s approach, in contrast to the methodologies of building Linked Data and ontologies, does not assume that various kinds of cleanup, reconciliation, and post-processing will usually be needed before structured data from the Web can be exploited in applications. • Many frame-based knowledge representation systems, including RDF Schema and OWL have a single domain and range for each relation. Schema.org assumes polymorphism. • Schema.org allows for multiple inheritance.
  22. 22. ExtensionsOF SCHEMA.ORG
  23. 23. 23TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 UNDER THE HOOD OF SCHEMA.ORG CORE  HOSTED EXTENSIONS  EXTERNAL EXTENSIONS • CORE – „Core, basic vocabulary for describing the kind of entities the most common web applications need”* • HOSTED/REVIEWED EXTENSIONS – Domain specific basic vocabularies. • EXTERNAL EXTENSIONS – More specialized, fully independent domain specific vocabularies. Built by a third party. • Today: autos, finance, bibliography, health & life-sciences, iot EXTENSION MECHANISM: SEQUENCE OF SPECIFICITY * http://schema.org/docs/extension.html
  24. 24. 24TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 CREATING EXTENSIONS TO SCHEMA.ORG • Extension URI: auto.schema.org • Designed as the first phase of the GAO project (Generic Automotive Ontology - http://automotive-ontology.org) • First step: extending core vocabulary by a minimal set of new terms (May 2015) • Second step: creating auto.schema.org hosted extension (May 2016) • Third step: creating POC of the external extension (March 2017) • Extension URI: fibo.schema.org • Inspiration from FIBO project (Financial Industry Business Ontology – http://fibo.org ) • Going through BOC (Bag-Of-Concept) phase and using an „Occam Razor” approach. • First step: extending core vocabulary by a minimal set of new terms (May 2016) • Second step: creating fibo.schema.org hosted extension (published in pending.schema.org (March 2017)) • Third step: creating POC of the external extension (March 2017) AUTOMOTIVE EXTENSION FINANCIAL EXTENSION
  25. 25. 25TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 AUTO.SCHEMA.ORG May 13, 2015 – official introduction of the Automotive extension to schema.org Collaborative project of Hepp Research GmbH, MakoLab SA and many other individuals.
  26. 26. 26TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 FIBO.SCHEMA.ORG Extension of the core vocabulary by a minimal set of new terms (May 2016) The hosted extension (published March 2017) as pending.schema.org Collaborative project of an international group of individuals lead by MakoLab SA. Described in: http://schema.org/docs/financial.html
  27. 27. 27TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 The financial extension of schema.org refers to the most important real world objects related to banks and financial institutions: • A bank and its identification mechanism • A financial product • An offer to the client • Described in: http://schema.org/docs/financial.html Thing CLASSES Action TransferAction MoneyTransfer Intangible Service FinancialProduct BankAccount DepositAccount CurrencyConversionService InvestmentOrDeposit BrokerageAccount DepositAccount InvestmentFund LoanOrCredit CreditCard MortgageLoan PaymentCard + PaymentService StructuredValue ExchangeRateSpecification MonetaryAmount RepaymentSpecification FIBO.SCHEMA.ORG
  28. 28. 28TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 FIBO.SCHEMA.ORG The financial extension of schema.org refers to the most important real world objects related to banks and financial institutions: • A bank and its identification mechanism • A financial product • An offer to the client • Described in: http://schema.org/docs/financial.html
  29. 29. 29TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 A BANK A DEPOSIT ACCOUNT A PAYMENT CARD THE BASIC MODELS OF THE FINANCIAL OBJECTS FIBO.SCHEMA.ORG
  30. 30. 30TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 CREATING EXTENSIONS – THE ART OF HARD CHOICES • All additions to schema.org, to its core and to a „hosted” extension must meet extremely strict conditions: • Their number must be minimal compared to the size of the vocabulary of the domain the extension represents. The making of an extension is an endless trade-off between the need for the expressive vocabulary of the domain and the requirement for its minimalism. • They must represent the CUSTOMER NEEDS and adopt down „bottom-up” design rules – not the demands of the domain specialists and practitioners. • The bottom-up approach assumes the „BOC” (Bag Of Concepts) approach, where the elements of the bag stem from the public „discourse” (the search on the web, social media) • The extensions must reuse the existing schema.org terms wherever possible, even if the current meaning of them may differ from the expected meaning. Why is the creation of schema.org extension the Art of Hard Choices?
  31. 31. The Applications. I. RankWEB SEARCH REDEFINED
  32. 32. 32TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 FUNDAMENTAL TRENDS IN WEB SEARCH 1. BIGGER SHARE ON THE TRANSACTION 2. RICHER INTERACTION This slide is based on the work of M. Hepp & M. Sopek "Web Search and Beyond: Digital Marketing for Automotive"
  33. 33. 33TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 4. DYNAMICS AND VOLATILITY 3. STRONGER INDIVIDUALIZATION FUNDAMENTAL TRENDS IN WEB SEARCH This slide is based on the work of M. Hepp & M. Sopek "Web Search and Beyond: Digital Marketing for Automotive"
  34. 34. 34TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 RICH SNIPPETS KNOWLEDGE PANEL VISUAL FEATURES IN SEARCH ENGINES This slide is based on the work of M. Hepp & M. Sopek "Web Search and Beyond: Digital Marketing for Automotive"
  35. 35. 35TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 FACTUAL ANSWERS And more … TABULAR RESULTS VISUAL FEATURES IN SEARCH ENGINES This slide is based on the work of M. Hepp & M. Sopek "Web Search and Beyond: Digital Marketing for Automotive"
  36. 36. 36TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 CONCRETE BENEFITS Rich snippet results on 2nd position received higher CTR than standard snippet on 1st position CTR INCREASE EXAMPLE
  37. 37. 37TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 What you measure in a traditional way may not reflect your actual performance Solutions: • Use KPIs with care • New metrics based on external resources • Add granular event handlers MEASURE WITH CARE NEW METRICS NEEDED
  38. 38. 38TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 SUMMARY OF “RANK” BENEFITS OF SCHEMA.ORG • CTR increase (Rich Snippets effect) • Better Brand visibility (Knowledge Panels and Factual Answers) • Better Product positioning (Rich snippets & Tabular results) • Faster way to reach searched content (more sitelinks) • Better mobile device experience of search 11.09.2015 – Google: „Over time, I think it [structured markup] is something that might go into the rankings as well. If we can recognize someone is looking for a car, we can say oh well, we have these pages that are marked up with structured data for a car, so probably they are pretty useful in that regard. We don’t have to guess if this page is about a car.” John Mueller / Webmaster Trends Analyst @Google
  39. 39. 39TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 WHAT ELSE CAN WE DO WITH SCHEMA? • While schema.org was invented to help search engines in their job and to help site owners to be more reliably discovered and ranked on the Search Engine Results Pages – its benefits are much more profound. • This why we say that schema.org power goes beyond RANK, and allows you to ANALYZE your site market environment better, improve site convergence and LEADS generation and helps to deliver a new kind of SEARCH capacity for your site! • What is more, to SEARCH and to ANALYZE you don’t need Google to cooperate 
  40. 40. The Applications. II. AnalyseNEW KIND OF DATA ANALYTICS
  41. 41. 41TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 SCHEMA.ORG DATA IN GOOGLE ANALYTICS The markup in the website’s code • Schema.org Google Tag Manager • Additional setup Google Analytics • Additional Dimensions and Metrics
  42. 42. 42TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 Auto Model 1 - Name - Brand Version1 Model, fuelConsumption, fuelType, numberOfDoors, Color Version 2 Version 3 Model 2 - Name - Brand Version 1 Version 2 Version 3 Model 3 - Name - brand Version 1 Version 2 Version 3 SCHEMA.ORG DATA IN GOOGLE ANALYTICS POC 1
  43. 43. 43TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 SCHEMA.ORG DATA IN GOOGLE ANALYTICS http://wisem.makolab.pl/ga/model1.html
  44. 44. 47TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 SCHEMA.ORG DATA IN GOOGLE ANALYTICS Usage within GA
  45. 45. 48TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 SCHEMA.ORG DATA IN GOOGLE ANALYTICS Usage within GA
  46. 46. 49TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 SCHEMA.ORG DATA IN GOOGLE ANALYTICS Usage within GA Which colour of a car should be used in Display Campaigns or in TV ads for Car1?
  47. 47. 50TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 SCHEMA.ORG DATA IN GOOGLE ANALYTICS Which engine model of Car1 is most popular online? Should we spend campaign money on Sport version or on Eco version? Usage within GA
  48. 48. 51TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 FINANCIAL EXTENSION SCHEMA.ORG POC • http://finances.makolab.com • Full use of fibo.schema.org • Definitions of financial dimensions • Analytics with Google “GA” POC 2
  49. 49. 52TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 POC’s page Json property Dimension Dimension name BankAccount.html price Bank Account Fee Price name Financial Product Name Financial Product Name BrokerageAccount.ht ml minValue Brokerage Account Minimum Investment Minimum name Financial Product Name Financial Product Name CreditCard.html annualPercentageRate Credit Card APR Percentage Rate minValue Credit Card Required Collateral Minimum price Credit Card Annual Fee Price name Financial Product Name Financial Product Name CreditCard8.html name Financial Product Name Financial Product Name minValue Credit Card Limit Minimum PaymentService.html name Financial Product Name Financial Product Name FinancialProducts.html name Financial Product Name Financial Product Name minValue Minimum Insurence Coverage Minimum maxValue Maximum Insurence Coverage Maximum FINANCIAL EXTENSION SCHEMA.ORG POC
  50. 50. 53TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 TRUE DATA ANALYTICS
  51. 51. 54TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 SCHEMA.ORG DATA IN GOOGLE ANALYTICS PROS: CONS: • None.• Analyse additional information available in Schema markup right in Web Analytics. • Better insights into what people look at on the website. Deeper understanding of users’ needs. • Better conclusions for website’s UX optimization. • Better conclusions for campaigns optimization.
  52. 52. The Applications. III. SearchADD SMART SEARCH TO YOUR SITES
  53. 53. 56TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 INTELLIGENT/SMART SEARCH BASED ON SCHEMA.ORG MARKUP Mark your product data with schema.org markup Run the smart Search Crawler for an Enterprise Website Check for schema.org markup (Microdata or JSON-LD) When markup is found, create property map and assign values Display enhanced search results
  54. 54. 57TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 Corporate product page + microdata http://nusil.com/product/r-2370_rtv-silicone-rubber-foam INTELLIGENT/SMART SEARCH BASED ON SCHEMA.ORG MARKUP
  55. 55. 58TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 UNDER THE HOOD… Crawler Indexer (Lucene) Microdata found Semantic Data WebSite INTELLIGENT/SMART SEARCH BASED ON SCHEMA.ORG MARKUP
  56. 56. 59TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 SEARCH AGAINST BOTH CONCEPTS AND THEIR PROPERTIES’ VALUES The real values taken from existing data found by crawler within the marked website pages INTELLIGENT/SMART SEARCH BASED ON SCHEMA.ORG MARKUP
  57. 57. 60TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 SEARCH AGAINST MULTIPLE CRITERIA INTELLIGENT/SMART SEARCH BASED ON SCHEMA.ORG MARKUP
  58. 58. Practical Session ❧ How to use it?
  59. 59. 62TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 USING SCHEMA.ORG IS EASY ! POC for financial domain: IMPLEMENTATION STEPS: • Understand the domain your website belongs to • Find schema.org types and properties that can be used to mark up your data • Add markup to your web pages – use types and properties properly! • As a general rule, you should mark up only the content that is visible to people who visit the web page • The more content you mark up, the better • Test your markup (use: Google’s rich snippets testing tool) http://finances.makolab.com
  60. 60. Reporting PERSPECTIVES FOR BUSSINESS REPORTING SCHEMA.ORG EXTENSIONS The Future ❧
  61. 61. 64TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 THE REPORTING HORIZON THE BUSINESS REPORTING and BUSINESS INFORMATION EXCHANGE IS REIGNED BY XBRL STANDARD • However, the cost of filing financial reports is still quite high, particularly for small companies* • This is why in the US, “Small Company Disclosure Simplification Act” : “(…) exempts emerging growth companies and issuers with total annual gross revenues of less than $250 million from the requirement to use Extensible Business Reporting Language (XBRL) for financial statements and other mandatory periodic reporting filed with the Securities and Exchange Commission (SEC). Such companies, however, may elect to use XBRL for such reporting.” * $2,000 to $25,000 per year according to XBRL US.
  62. 62. 65TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 THE PURPOSE OF THIS PART OF THE WORKSHOP TO DISCUSS THE POSSIBILITY OF DEEPER SIMPLIFICATION OF XBRL by adoption of schema.org principles • We have performed a series of simple technical exercises that pave the initial path for further studies • While we do not propose here any new standard nor want to shake the foundations of the old, we think it is worth to consider if schema.org principles offer the possibilities to make business reporting even simpler and more accessible.
  63. 63. 66TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 THE RELEVANT DEVELOPMENT THE USE OF SEMANTIC WEB STANDARDS • „Publishing XBRL as Linked Open Data” (Roberto García & Rosa Gil, Universitat de Lleida) • „Triplificating and linking XBRL financial data” (Roberto García & Rosa Gil, Universitat de Lleida) • „Adopting Semantic Technologies for Effective Corporate Transparency” (Maria Mora-Rodriguez, Ghislain Auguste Atemezing, Chris Preist) • „Financial Report Ontology” (Charles Hoffman)
  64. 64. 67TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 THE RELEVANT DEVELOPMENT THE EVOLUTION WITHIN XBRL WORLD • „Open Information Model” - https://specifications.xbrl.org/work-product- index-open-information-model-open- information-model.html The Open Information Model provides a syntax-independent model for XBRL data, allowing reliable transformation of XBRL data into other representations. The work product includes: xBRL-XML, xBRL-JSON, xBRL-CSV, OIM Common. • XBRLS - XBRL Simple Application Profile (how a simpler XBRL can make a better XBRL) • Inline XBRL - https://specifications.xbrl.org/spec- group-index-inline-xbrl.html
  65. 65. THE EXERCISES ❧
  66. 66. 69TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 HOW COULD IT WORK? POC: FIBO as schema.org external extension • The extension URI: http://fibo.org/voc/ • The conversion from FIBO-V (SKOS complaint ontology) • The markup example based on the extension
  67. 67. 70TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 * Charles Hoffman: http://xbrl.squarespace.com/journal/2008/12/18/ hello-world-xbrl-example.html HOW COULD IT WORK? INITIAL EXCERSISE “I”- XBRL „Hello World” * expressed as schema.org compliant markup • Converting taxonomy (XSD) to OWL ontology (with help of: http://rhizomik.net/html/redefer/) • Writing schema.org compliant JSON-LD markup
  68. 68. 71TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 HOW COULD IT WORK? INITIAL EXCERSISE “II”- iXBRL example • Based on https://www.xbrl.org/ixbrl- samples/valeo-income-statement.html • Expression of the data semantics in JSON-LD – schema.org compliant markup
  69. 69. 72TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 HOW COULD IT WORK? INITIAL EXCERSISE “III”- GAAP TAXONOMY IN SCHEMA.ORG FORMAT • Source: PROPOSED 2018 US GAAP FINANCIAL REPORTING TAXONOMY • How: Extracting parent-child taxonomy with the definitions of terms + schema.org-like RDFa formatting of the obtained model • Result: http://sdo-gaap- ee.appspot.com/GrossProfit
  70. 70. 73TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 A VISION for the future steps CREATION of SCHEMA.ORG extensions and their applications • Step I – the external extension based on selected XBRL taxonomy (like GAAP or IFRS) • Step II – the external extension based on selected SBR taxonomy • Creation of implementation guidelines and live POC • Working with interested parties on the real-life tests • Critical evaluation of the project • If successful - working on the HOSTED EXTENSION to schema.org • In general - Adopting the philosophy of bottom-up, empirical approach to the creation
  71. 71. 74TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 Discussion Let’s evaluate the soundness of the ideas presented here …
  72. 72. THANK YOU Full slide deck at: http://ml.ms/makolabtode ❧
  73. 73. 76TRUSTED OPEN DATA ECOSYSTEMS, MADRID, SPAIN, September 28, 2017 PLEASE CONTACT US! DR. MIREK SOPEK CTO sopek@makolab.com Poland: MakoLab SA, Demokratyczna 46, 93430 Lodz, Poland Phone: +48 600 814 537, www.makolab.com USA: Makolab USA Inc, 20 West University Ave, Gainesville, FL 32601 Phone: +1 551 226 5488 , www.makolab.com Dr ROBERT TRYPUZ MakoLab SA Rzgowska 30 93-172 Łódź Poland robert.trypuz@makolab.com INDUSTRY MakoLab SA Rzgowska 30 93-172 Łódź Poland robert.trypuz@makolab.com ACADEMIA JPII University Lublin trypuz@kul.pl

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