Summit Meeting Search meets Terminology. Felix Sasaki, DFKI / W3C Fellow, Berlin Christian Lieske, SAP, St. Leon-Rot

Transcription

1 Summit Meeting Search meets Terminology Felix Sasaki, DFKI / W3C Fellow, Berlin Christian Lieske, SAP, St. Leon-Rot

2 Crossing the language chasm with terminological assets User Ø Output Input 图形提供商 x Primary Content Concept English Easy Graphics Framework German Easy Graphics Framework 2

3 Terminological Assets as Value-Add in Today s Web The Web as application platform Ingredients to a universal Application Programming Interface Crossing the language chasm with terminological assets We will offer opportunities to win prices during quizzesj 3

4 About Us Felix Sasaki DFKI / W3C Senior Researcher at DFKI (LT-Lab) W3C Office Germany / Austria W3C Fellow technical area: application of web technologies for representation and processing of multilingual data Studied Japanese, linguistics, web technologies in Germany and Japan Christian Lieske SAP Knowledge Architect (SAP Language Services, Globalization Services) Topcis: Multilingual production, natural language processing, internationalisation Contribution to World Wide Web Consortium (W3C), OASIS, Unicode Consortium Studied computer science and natural language processing (including machine translation an speech processing) 4

5 Quiz 1 Question 5

6 Quiz 1 Answer Browser Web Search Engine User Client Network Server Keyword, operator, controls/configuration settings Communication Session Resource/services Distributed application Open Web Platform 6

7 Quiz 2 Question 7

8 Quiz 2 Answer Search Engine Results page (SERP) Snippet/Card 8

9 Quiz 3 Question 9

10 Quiz 3 Answer Organic results/sponsored results Informational box Rich snippet/rich card Knowledge graph card 10

11 Quiz 4 Question 11

12 Quiz 4 Answer Dynamic aggregation Discogs Dbpedia Linked Open Data No Screen Scraping but Harvesting No specialized API last.fm MusicBrainz 12

13 Quiz 5 Question User Easy Graphics Framework 图形提供商 Output Input Concept Chinese English Concept English German x 图形提供商 Easy Graphics Framework Additional Knowledge Source Primary Content x Easy Graphics Framework Easy Graphics Framework 13

14 Quiz 5 Answer? 14

15 Linked Open Data Data on a Solid Stack Universal network of units with explicit meaning to bridge semantic gaps (string of numbers is a price) Semantic Web architecture (e.g. Resource Description Framework for standardized meaning representation) Enable or facilitate computers and people to work better in cooperation 30 percent of HTML pages contain structured data <div itemscope itemtype=" <div itemprop="name"><strong>easy Graphics Framework</strong></div> </div> 15

16 Linked Open Data Representing Knowledge Subject Predicate Object Conceptualization/model = explicit, machine understandable, consensus Vocabulary = describes and represents an area of concern Classifies terms that can be used in a particular application Characterizes entities Schema.org vocabulary allows search engines to recognize information easier and more precisely 16

17 Linked Open Data Embedded Structured Data Embed structured data with explicit semantic annoations in HTML documents Microformats misuse <div class= vcard RDFa reuse <p vocab=..foaf typeof= Person ><span property= name > HTML5 microdata annoate DOM with scoped name/value pairs from custom vocabularies HTML attributes: itemscope, vocabularies: person, event, 17

18 Linked Open Data One model, various serializations (N-triples) < "Eric Miller". 18

19 Linked Open Data One model, various serializations (JSON-LD) { "@context": { "contact": " " [...] }, "@id": " "@type": "contact:person", "contact:fullname": "Eric Miller" [...]} JSON-LD: non intrusive, e.g. link from HTML file: <link href="jsonld.js" rel="alternate" type="application/ld+json" /> 19

20 Linked Open Data The Challenge Example: Describe a product along the lines of the name of the product in a certain country <div itemscope itemtype=" <div itemprop="name"><strong>easy Graphics Framework</strong></div> </div> <div itemscope itemtype=" <div itemprop="name"><strong> 图形提供商 </strong></div> </div> 20

21 Schema.org (1/2) <meta property="og:type" content="article"> <meta property="og:title" content="wochenmarkt: Hühnchensalat"> <span itemprop="logo" itemscope itemtype=" 21

22 Schema.org (2/2) 22

23 Crossing the language chasm with terminological assets (1/3) User Ø Output Input 图形提供商 x Primary Content Concept English Easy Graphics Framework German Easy Graphics Framework 23

24 Crossing the language chasm with terminological assets (2/3) User Easy Graphics Framework 图形提供商 Output Input Concept Chinese English Concept English German x 图形提供商 Easy Graphics Framework Additional Knowledge Source Primary Content x Easy Graphics Framework Easy Graphics Framework 24

25 Crossing the language chasm with terminological assets (3/3) Get terminology out Map the vocabularies of the terminology Get the mapped information serialized Creating Schema.org information 1. Write Schema.org from scratch 2. Use editing support 3. Convert your term data to Schema.org = SEO focused view on your term data 4. Annotate content automatically with your term data 25

26 From TermBase Exchange (TBX) to Schema.org (1/2) Demo at Relies on FREME framework Allows also extraction of terms and storage as Schema.org information <langset xml:lang="de">... <term> Easy Graphics Framework </term> <langset xml:lang= ZH">... <term> 图形提供商 </term> 26

27 From TermBase Exchange (TBX) to Schema.org (2/2) 27

28 Seen through the Eyes of a Search Engine = Visualisation via 28

29 The Gap Cross-Language Rich Snippet with your Language 29

30 The Gap State-of-affairs Discussion of how to improve multilingual support of Schema.org in the W3C Schema.org Community Group Current state: the general idea has agreement (see previous example) Open issue 1: The devil is in the detail sameas not tailored towards cross-lingual links CreativeWork not tailored towards terms but books / movies /... Open issue 2: a solution needs industry support We can do this if the community asks for it Want to ask for it?jjoin 30

31 Conclusions (1/2) Term Base 31

32 Conclusions (2/2) Influence search and other Web-based processing of your information Benefit from standards-based information provisioning No specification necessary, no proprietary API Easy, universal modelling (lightweight linked data view on your terminology data 32

33 Acknowledgements This presentation was supported by the FREME project, co-funded by the Horizon 2020 Framework Programme of the European Union, Grant Agreement Number More information at

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35 Disclaimer 35

36 IN 21 Presentation Summit Meeting: Search meets Terminology Felix Sasaki, DFKI / W3C Fellow, Berlin Christian Lieske, SAP, St. Leon-Rot Introduction The days in which major search engines worked on nothing but strings are long gone. In a similar vein, the Web has evolved from collections of linked Web pages to a myriad of data lakes one can tap into. Meta data annotation and processing concepts related amongst others to the Semantic Web are the backbone of these developments. Interesting questions for today s tech doc community are amongst others: 1. Which role can terminological assets play in today s Web especially in the context of search? 2. How much synergy does already exist between terminology-related tools and resources and Search Engine Optimization (SEO) based on meta data, and markup? Today s Web Content in terms of Relationships and Search Today, the term Semantic Web is used less and less. Instead, the term Linked Data is used. The rationale behind is the following: The first Semantic Web technologies were made available more than 15 years ago. At that time, the core vision of the Semantic Web was automatic inferencing of new knowledge. Example: If A is composed of B, then one can infer that B is a part of A. This vision hardly materialized beyond simple examples like the aforementioned one. Accordingly, the Semantic Web lacked from adoption. Nevertheless, the Semantic Web had a huge impact: One key aspect of the Semantic Web however has found broad adoption: The Semantic Web proposes to have a globally unique identifier (GUID) for anything, and to provide GUIDs even for relations between concepts. Over time, a powerful ensemble of technologies was developed. It encompasses 1. The Resource Description Format (RDF) to create linked data 2. RDF Schema / the Ontology Web Language (OWL) to create linked data vocabularies of different formal complexity 3. The SPARQL family of specifications for queries Furthermore, a large amount of linked data vocabularies has been created: Friend-of-a-friend (FOAF) for persons and their relations

37 Dublin Core for general metadata The Basic Geo Vocabulary for geographical information The Linked Open Vocabularies (LOV) site at maintains an overview of vocabularies. Finally, several syntaxes/serialization formats like RDF/XML or RDFa have been developed (e.g. for processing in various existing workflows). Taken together these Semantic Web concepts and technologies have laid the foundation for the Linked Data movement that is currently revolutionizing the World Wide Web. The base idea: put interesting data entities (e.g. facts) on the Web by identifying them via a GUID. Then, use Semantic Web technologies to create mashups of these entities, and to create powerful search applications. Schema.org as Facilitator In 2011, big search engine providers realized how to benefit from Linked Data, and how that they could assist in lowering the entry barrier for to the world of Linked Data. They adopted the key concepts of the Linked Data technology stack and provided simple mechanisms (markup and vocabularies) to encode (linked) information in Web pages. The outcome was Schema.org, an effort to bring the idea of linked and structured information to the Web at large. The search engine providers understood that Schema.org could only have broad adoption if ideas around GUIDs and vocabularies were not provided by a closed club. Thus, dedicated Schema.org Community Group was formed within the World Wide Web Consortium (W3C) in 2015 to provide an open and transparent forum. The basic ideas of Schema.org are: 1. Provide a way to identify uniquely concepts and relations via Uniform Resource Identifiers (URIs). Examples: The concept (in the terminology of Schema.org types") of a Person is identified via The parent of a person is identified via the relation (in the terminology of Schema.org properties ) There are galleries of examples for widely used Schema.org types, see e.g Provide simple means to embed the aforementioned information into Web content. 3. Use just one vocabulary for the Schema.org definitions. This is a key difference to Semantic Web and Linked Data in general: Vocabularies like FOAF or

38 Dublin Core are maintained independently. The benefit is flexibility; the disadvantage is uncertainty for the user how the vocabularies work together. As of today, according to the Schema.org web site, more than 10 million sites use Schema.org markup to encode Linked Data information without requiring in-depth knowledge of the complex, previously described Semantic Web/Linked Data technology stack. The coverage of domains differs per type: Markup for persons appears on more than 1 million Web site domains. Markup for news article appears in less than domains. Markup for technical articles appears in less than 1000 domains. Terminology as Additional Player Schema.org adheres to the terminology principle of concept orientation. One concept, e.g. a product, has exactly one unique Schema.org identifier. Thus, terminological assets can enter the world of Linked Data. This will be exemplified with the following a scenario: A Chinese technician familiar with Chinese terminology in his field of expertise is looking for product offerings related to 图形提供商, and searches for it on the Web. Since the Web-based user assistance is only available in English and German, the technician does not become aware of a corresponding offering Easy Graphics Framework. The vendor thus may lose a potential sales opportunity. Schema.org could help to overcome this limitation if the vendor s terminological knowledge would also be available in Chinese. Amongst the data categories of the corresponding terminological database, is of course one for a standard is_translation_of relationship. In Schema.org, this relationship is used to realize cross-lingual search that could make the user aware of the vendor s offering. Scenario: Cross-lingual Search based on Schema.org and Terminology The scenario described above so far cannot be realized in a straightforward way: Schema.org does not include a is_translation_of relation to express that something is a term, or even to express a whole term database entry (see discussions at Nevertheless, the scenario can be realized with Schema.org: It provides a sameas relation and the ability to assign a language to a concept via the inlanguage type. Taken together, the two Schema.org construct, can encode the translation relation between 图形提供商 and Easy Graphics Framework that is needed in the scenario at hand. Example: { "@id": " "schema:inlanguage": "zh",

39 "schema:name": " 图形提供商 ", "schema:sameas": { } } "@id": " "schema:inlanguage": "en", "schema:name": "Easy Graphics Framework" Since TermBase exchange (TBX) is used widely in terminological contexts, a TBX-to-schema.org converter thus can be used to use terminological information to generate Schema.org markup that can facilitate cross-lingual search (e.g. retrieving English content based on a query in Chinese). Discussion Based on Semantic Web concepts and technologies, Schema.org enhances search experience (for users), and success (for Web site administrators). As of today, Schema.org does not yet include everything that is needed to realize all cross-lingual scenarios easily. Since Schema.org is based on feedback, input from the tech doc community could help to change this. Contact: felix.sasaki@dfki.de, christian.lieske@sap.com