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Mashups: The new breed of Web Applications

Mashups: The new breed of Web Applications. Umut Orhan. Outline. The term “Mashup” Mashups Genres Technologies behind Mashups Emerging Technical and Social Challenges. History - Information Technology Spend “had” been growing nicely. 1964: S/360 debuts. 1994: Netscape Navigator.

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Mashups: The new breed of Web Applications

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  1. Mashups: The new breed of Web Applications Umut Orhan

  2. Outline • The term “Mashup” • Mashups Genres • Technologies behind Mashups • Emerging Technical and Social Challenges

  3. History - Information Technology Spend “had” been growing nicely 1964: S/360 debuts 1994: Netscape Navigator 2000: Dot-com collapse 1971: First Intel Micro 1981: IBM PC

  4. Crash Just the beginning of a “golden” age Innovation Deployment The Industrial Revolution Irruption Frenzy Synergy Maturity Dot.com Collapse - Is it the end? Panic 1797 Age of Steam and Railways 1 • Formation of Mfg. industry • Repeal of Corn Laws opening trade 1829 1771 Age of Steel, Electricity and Heavy Engineering Panic 1847 2 • Standards on gauge, time • Catalog sales companies • Economies of scale 1873 1829 Depression 1893 Age of Oil, Automobiles and Mass Production 3 • Separation of savings, investment banks • FDIC, SEC 1920 1875 Age of Information and Telecommunications 4 • Build-out of Interstate highways • IMF, World Bank, BIS Crash 1929 1974 1908 Dot.com Collapse 5 Current period of Institutional Adjustment 1971 Source: “Technological Revolutions and Financial Capital, Carlota Perez, 2002

  5. Mashups are… • … an exciting genre of interactive Web applications that • Retrieve content from external data sources • Create entirely new and innovative services • Hallmark of the Web 2.0 • Run-time integration

  6. The term Mashup • Borrowed from the pop music scene • Vocal and instrumental sounds from different source tracks are mixed to form a new “mashup” song • An unusual or innovative composition of content (often from unrelated data sources) • Made for human (rather than computerized) consumption

  7. Current Status From programmableweb.com on 1/12/2006

  8. What might a Mashup look like? • The ChicagoCrime.org Web site • A mapping mashup • One of the first popular mashups • Mashes crime data from the Chicago Police Department’s online database with cartography from Google Maps • The concept and the presentation are simple and the composition of crime and map data is visually powerful

  9. Outline • The term “Mashup” • Mashups Genres • Technologies behind Mashups • Emerging Technical and Social Challenges

  10. Mashups • A Mashup web site is characterized by the way in which it spreads roots across the Web • Building upon the content and functionality retrieved from external data source • Mostly the data source lay outside of the organizational boundaries

  11. Mashup Genres • Mapping mashups • Video and photo mashups • Search and Shopping mashups • News mashups

  12. Mapping Mashups • Locational information presented graphically using maps in a specified context • Google Maps API opened the floodgates; mash all sort of data from nuclear disasters to Boston’s CowParade cows onto maps • Other APIs • Microsoft (Virtual Earth) • Yahoo (Yahoo Maps) • AOL (MapQuest)

  13. Video and Photo Mashups • The emergence of photo/video hosting and social networking sites such as Flickr with APIs and YouTube has led to a variety of interesting mashups. • Metadata associated with the hosted images and videos • Who took the picture • What it is a picture of • Where and when it was taken • So on…

  14. Search and Shopping Mashups • Exist long before the term Mashup was coined • Combinations of B2B technologies or screen-scraping to aggregate comparative price data • eBay and Amazon have released APIs for programmatically accessing their content

  15. News Mashups • News sources such as BBC and Reuters have used syndication technologies like RSS and Atom since 2002. • Personalized newspaper by Syndication feed mashups • Doggdot.us, combines feeds from the techie-oriented news sources Digg.com, Slashdot.org and Del.icio.us

  16. Outline • The term “Mashup” • Mashups Genres • Technologies behind Mashups • Emerging Technical and Social Challenges

  17. The architecture • A mashup architecture comprimes of 3 logically and physically disjoint components • API/Content Provider • Mashup Site • Client’s Web Browser

  18. API/Content Exposition • Web Protocols • REST Services • SOAP Web Services • RSS/Atom • Screen Scraping

  19. Mashup Site • Mashup is hosted by a web site • Mashup logic resides in this site • Execution is distributed over the web • The Mashup Site can be implemented and deployed similarly to traditional Web application

  20. Client-Side Processing • Mashed content can be generated directly within the client’s browser through client-side scripting (JavaScript) or applets. • Rich Internet Applications • Less overhead on behalf of the mashup server • Data can be retrieved directly from the content provider • More seamless user-experience • Pages can request updates for portions of their content without having to refresh the entire page • Client’s Web Browser is where the application is rendered graphically and where the user interaction takes place

  21. AJAX • Asynchronous JavaScript and XML • Web application model rather than a specific technology • Comprises; • XHTML, CSS and XSL for presentation • DOM API exposed by API for dynamic display and interaction • Asynchronous data exchange, XML or JSON data • JavaScript • Aims to create a smooth, cohesive Web experience with reducing server-side overloads

  22. Web Protocols • As part of the SOA paradigm, these protocols are platform neutral to interact with any remote services • Exchanging XML based messages in general • Messages are typically conveyed over standard transports such as HTTP and SMTP

  23. Web Protocols: SOAP • Simple Object Access Protocol • Fundamental technology behind Web Services • SOAP APIs for Web Services described by WSDL documents • What operations a service expose • The format for the messages that it accepts (using XML Schema) • How to address the service

  24. Web Protocols: REST • Representational State Transfer • Similar to document-literal style of SOAP • Identification of resources by URIs • Supports less operations (POST, GET, PUT, DELETE)

  25. Screen Scraping • Scrapingis the process of using software tools to parse and analyze content that was originally written for human consumption in order to extract semantic data structures representative of that information that can be used and manipulated programmatically.

  26. Semantic Web and RDF • To create web infrastructure that augments data with metadata to give it meaning for automation, integration, reasoning and re-use • Resource Description Framework (RDF) provides methodologies to establish syntactic structures that describe data • RDF allows creation of hierarchical structures of knowledge that can be searched and formally reasoned about, ontologies

  27. Semantic Web and RDF lives in lives in eats? eats animalType: Carnivore animalType: Reasoner animalType: animalType: Carnivore eats? lives in lives in eats

  28. RSS and ATOM • XML-based syndication formats • Syndication implies that a Web site that wants to distribute content creates an RSS or ATOM document and registers the document with an RSS publisher. • RSS/ATOM-enabled client can check the publisher’s feed for new content and react to it in an appropriate manner. • Syndication technologies are useful for mashups that aggregate event-based or update-driven content

  29. Outline • The term “Mashup” • Mashups Genres • Technologies behind Mashups • Emerging Technical and Social Challenges

  30. Data Integration Challenges • According to surveys; number one enterprise IT concern today is data integration within the enterprise virtual organization • Virtual Organization: a composition of federated business units, each contained within its own administrative domain • Mashup developers are faced with challenges of deriving shared semantic meaning between heterogeneous data sets. • Mashup developers’ challenges are similar to integration challenges faced by enterprise IT. • Translator/Mapper systems between different data models must be designed.

  31. Data Pollution • Many mashups solicit public user input • it can be quite powerful because it enables open contribution and best-of-breed data evolution • it can be subject to inconsistent, incorrect or intentionally misleading data entry

  32. Social Challenges • Protection of intellectual property and consumer privacy versus fair-use and the free flow of information

  33. In general… • Publishing and Discovering External Data Services other than SOAP-based Web Services • Semantically annotation of data services • Security leaks (e.g. openness to injection attacks)

  34. In general… • Client-side processing is not suitable for handling complex queries such as “Show me the average purchase price for real estate bought by actors who have co-starred in movies with Brad Pitt” • Interoperability among different external data providers • Standard formats for persistent data and exchanged messages

  35. Thank you for your attention…

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