01 March 2011Kaiser: COMS E61251 COMS E6125 Web-enHanced Information Management (WHIM) Prof. Gail Kaiser Spring 2011

01 March 2011Kaiser: COMS E61252 Today’s Topics: What is Web 2.0? Information Sharing and Privacy Applications Beyond the Web

Tim O’Reilly, September 2005September

01 March 2011Kaiser: COMS E61254 Netscape vs. Google: The Web As Platform Netscape: free web browser as flagship to establish market for high-priced server products that push content to the “webtop” – but servers also turned out to be commoditiesNetscape Google: Native web application, never sold or packaged or ported, delivered as a service with no scheduled software releases, massively scalable - core competency is data managementGoogle

01 March 2011Kaiser: COMS E61255 Akamai vs. BitTorrent: Internet Decentralization Akamai: Treats network as platform at deeper level of stack, transparent caching and content delivery that eases bandwidth congestion – also limited by business model catering to large providersAkamai BitTorrent: P2P file fragment downloads, every client is also a server, the service automatically gets better the more people use it - architecture of participationBitTorrent

01 March 2011Kaiser: COMS E61256 Harness Collective Intelligence Google PageRank using link structurePageRank eBay enabler of user activity requiring critical masseBay Amazon uses community activity to produce better search results (real-time “most popular” computation)Amazon Wikipedia – radical experiment in trust, profound change in content creationWikipedia

01 March 2011Kaiser: COMS E61257 Harness Collective Intelligence Web of connections grows organically Viral marketing – if a site or product relies on advertising to get the word out, it isn’t Web 2.0Viral marketing Peer-production open source development of much web infrastructure – linux, apache, mysql, various perl, php, pythonopen source Network effects from user contributions are the key to market dominance

01 March 2011Kaiser: COMS E61258 Blogosphere Blogging vs. personal home pages, replaced personal dairy, daily opinion column, NNTP (Usenet’s Network News Protocol), now being supplanted by facebook and twitterNNTP being supplanted RSS (Really Simple Syndication) allows subscribing to a page – the incremental (or live) webRSS Permalink builds bridges between weblogs, effects PageRank search resultsPermalink

01 March 2011Kaiser: COMS E61259 Perpetual Beta Software delivered as a service, not a product Upgrades every day vs. every 2-3 years Operations and monitoring must become core competencies Scripting languages as duct tape Innovation in assembly

01 March 2011Kaiser: COMS E AJAX AJAX Rich User Experiences Standards-based presentation using XHTML and CSSStandards-based presentation Dynamic display and interaction using the Document Object Model Document Object Model Data Interchange and manipulation using XML and XSLTXSLT Asynchronous data retrieval using XMLHttpRequest XMLHttpRequest Javascript binding everything togetherJavascript

01 March 2011Kaiser: COMS E Infoware Database management as core competency Specialized databases: web crawl, distributed file databases Map databases: starting with Mapquest, many services now license the same data from NavTeq (digital street maps), Digital Globe (satellite images)NavTeqDigital Globe Amazon licensed ISBN registry from Bowker but added publisher-supplied data and user annotationsBowker Mashups based on lightweight programming model create value-added dataMashups  Key issue: Who owns the data?

01 March 2011Kaiser: COMS E Information Sharing: Web 1.0 The original purpose of the Web! Generally viewed as an information resource, download without upload Websites owned by “someone else” may store your information in a database – usually limited to basic identification (name, address, phone number, credit card) and “preferences” Personal websites (e.g., hosted by geocities) might be universally browse-able but in practice visited by fewgeocities Key issue: Who owns the data?

01 March 2011Kaiser: COMS E Information Sharing: Web 2.0 Message boards with user-supplied content Portals with user-selected content “portlets” Blogs, wikis, news feeds, texting Social networking, collaborative filtering RIAs (rich internet applications) The Web as Platform, widgets, mashups, user- supplied applications  Key issue: Who owns the data?

01 March 2011Kaiser: COMS E The Right To Privacy Secrecy (confidentiality): The extent to which we are known to others Anonymity: The extent to which we are the subject of others’ attention Solitude: The extent to which others have access to us

01 March 2011Kaiser: COMS E Rights to Sue (wrt Privacy) Intrusion upon seclusion or solitude, or into private affairs Public disclosure of embarrassing private facts Inaccurate reporting: Publicity that places a person in a false light in the public eye Appropriation of identity: “identity theft”

01 March 2011Kaiser: COMS E A New Yorker cartoon from 1993New Yorker cartoon

01 March 2011Kaiser: COMS E But in 2011, your browser (and its addons, plugins, etc.) know You’ve searched for local veterinarians and groomers You’ve read reviews comparing flea powders You’ve ordered “chew sticks” and “squeaky toys” You’ve printed coupons for Alpo You’ve downloaded 101 Dalmations and Lassie “on demand” movies Your contains sales notices from petco.com  Your “My Pictures” folder contains 100s of images of fire hydrants and frisbees

01 March 2011Kaiser: COMS E612518

01 March 2011Kaiser: COMS E Web Tracking Bits: How Do They Track You? Data collection events: –Pages displayed –Search queries entered –Videos played –Advertising displayed (both same party and third party) In December 2007 alone, yahoo collected 400 billion events, aol 100 billion, google 91 billion, microsoft 51 billion

01 March 2011Kaiser: COMS E From study by comScorecomScore published in NY Times online 3/9/08

01 March 2011Kaiser: COMS E Caveats Not all of this data is useful Not all of it is retained by the companies with access to it Much of it cannot be traced back to individuals Several data collection events may be triggered by a single Web page Does not include user-volunteered data (website registration, social networking)

01 March 2011Kaiser: COMS E Why Track? Targeted advertising supports “free” services and content (ad serving was the first widely deployed mashup)Targeted advertising But collected information can be used for other purposes… Ad choice (e.g., TACO, Evidon)TACOEvidon

01 March 2011Kaiser: COMS E Privacy Before and After Before the Web, you participated in a variety of activities These might have involved groups of people, in public or private, possibly even “the press” Photos or recordings might have been taken, with or without your knowledge You might have borrowed or purchased books or magazines related to your activities You might have sent/received letters by snailmail What is different now? Does it matter?

01 March 2011Kaiser: COMS E Privacy Before and After Before the Web, you might have typed your name, address, phone number, birth date, social security number, bank account numbers, credit card numbers, etc. into your PC for personal storage It was unlikely anyone outside your household could access your PC Now you type at least part of that information into your PC all the time (if you make online purchases and/or sign up for online services) And you have no idea who might be reading them, from either your PC (if connected to Internet) or from the Websites you sent them to

01 March 2011Kaiser: COMS E Privacy Before and After Your name, phone number, address were always easily available (phone book, reverse listings) So was your birth date, although harder to obtain (birth records, drivers license) And your SSN - lots of forms ask for it Your checking account and/or credit card numbers were available through the issuing banks and the merchants where you made purchases So what is different now? Does it matter?

01 March 2011Kaiser: COMS E Web 2.0 Applications for Scientific Communities Scientists collaborating together in the same lab on the same project share: –Data: specimens, samples, materials, observations, etc. –Tools: instruments, software, hardware –Knowledge: open discussion, whiteboard  Real-world social networking However, there are time and space constraints More significantly, this model does not scale well to communities of scientists working on different projects but who could possibly learn from each other’s expertise, experience, etc.

01 March 2011Kaiser: COMS E CSCW Approaches CSCW (Computer-Supported Collaborative Work) aims to augment same-time/same-place collaboration but more significantly different- time/different-place collaborations and communitiesCSCW Current generation CSCW systems support data sharing (e.g., PNNL Collaboratories) and/or tool sharing (e.g., UIUC BioCoRE)PNNL CollaboratoriesUIUC BioCoRE However, these systems do not address knowledge sharing  how/when/where/why to use tools and data

01 March 2011Kaiser: COMS E Knowledge Sharing Knowledge sharing is partially enabled through labor intensive static approaches: publications, lists, wikis, chat, shared display, etc. We seek to enable automatic knowledge sharing - without requiring “extra work” on the part of scientists

01 March 2011Kaiser: COMS E Social Networking Social Networking Metaphor Some online social networking is a form of CSCW that is potentially enjoyable and profitable but still requires “extra work”, with dynamism limited by explicit user participation –Facebook, LinkedIn, Twitter, etc. Other social networking automatically records what people do online to aggregate, data mine and disseminate in an enjoyable and profitable fashion, with no “extra work” required - but can be enhanced by very simple user actions (e.g., ratings) –Collaborative filtering – “people like you …”Collaborative filtering

01 March 2011Kaiser: COMS E genSpacegenSpace Overview We combine implicit and explicit social networking concepts in our approach to knowledge sharing Prototype implemented as a set of plugins for geWorkbench, a platform for analysis and visualization tools for integrated genomics geWorkbench Records, aggregates, data mines and disseminates geWorkbench users’ activities with tools and tool sequences (workflows)

01 March 2011Kaiser: COMS E Questions genSpace Can Answer What do I do next? Which tools work well together? Where does this tool fit in a typical workflow? Who do I know who also uses this tool? How can I get help (from an expert who is online right now)?

01 March 2011Kaiser: COMS E genSpace Features Collaborative Workflow Composition: past history of analysis tool usage is used to identify commonly-occurring sequences/workflows Tool Suggestions: suggests analysis tools that may be useful, based on what tools were previously used Social Networking: allows users to associate with each other and share knowledge within groups Data Suggestions: suggest data sets based upon previous analyses and CF

01 March 2011Kaiser: COMS E genSpace Architecture

01 March 2011Kaiser: COMS E Privacy/Confidentiality Concerns Users can choose anonymous logging or disable it entirely Security/privacy of the activity logs is being investigated (data sets are NOT recorded*) Issues when users change their collaborative networks and/or opt out preferences Must we provide privacy by default?

Research in the Cloud geWorkbench, most other analysis tools are “fat” desktop applications Why not create a browser-based client? 01 March 2011Kaiser: COMS E612535

More open questions for genSpace What other CSCW techniques can help support researchers? How can we efficiently address privacy concerns while providing helpful recommendations? 01 March 2011Kaiser: COMS E612536

01 March 2011Kaiser: COMS E Summary genSpace embodies an approach to knowledge sharing that is based on social networking metaphors genSpace is built on the geWorkbench platform for integrated genomics Potentially applicable to other kinds of scientists and engineers, including software engineers

February 22, 2011COMS Next Assignments Full paper due Tuesday March 8 thFull paper Project Proposal due Tuesday March 8 thProject Proposal

01 March 2011Kaiser: COMS E COMS E6125 Web-enHanced Information Management (WHIM) Prof. Gail Kaiser Spring 2011