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Global Grids Web 2.0 and Globalization

Global Grids Web 2.0 and Globalization . Indiana University Informatics Colloquium January 12 2007 Geoffrey Fox Computer Science, Informatics, Physics Pervasive Technology Laboratories Indiana University Bloomington IN 47401 gcf@indiana.edu http://www.infomall.org. Abstract.

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Global Grids Web 2.0 and Globalization

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  1. Global Grids Web 2.0 and Globalization Indiana University Informatics Colloquium January 12 2007 Geoffrey Fox Computer Science, Informatics, Physics Pervasive Technology Laboratories Indiana University Bloomington IN 47401 gcf@indiana.edu http://www.infomall.org

  2. Abstract • We discuss the role of Web 2.0 and Cyberinfrastructure (also called e-infrastructure and implemented by Grid technology) in a variety of global and globalization activities. • These include the linking of researchers and data world wide in many fields; new generations of digital libraries and tools like Google Scholar; study of ice-sheets at the poles and the dramatic impact of Global warming; the study of earthquakes across the Pacific ocean; the linking of apparel manufacturers in Asia to designers in different continents and the command and control system for the Department of Defense. • Conversely Web 2.0 and Cyberinfrastructure are inherently democratic and support the broadening of communities involved in science and business. • They allow members of the Navajo Nation to participate in society and commerce from their homeland while many see this infrastructure as allowing broader participation in Science. We discuss recent efforts to implement these dreams!

  3. Why Cyberinfrastructure Useful • Supports distributed science – data, people, computers • Exploits Internet technology (Web2.0) adding (via Grid technology) management, security, supercomputers etc. • It has two aspects: parallel – low latency (microseconds) between nodes and distributed – highish latency (milliseconds) between nodes • Parallel needed to get high performance on individual 3D simulations, data analysis etc.; must decompose problem • Distributed aspect integrates already distinct components • Cyberinfrastructure is in general a distributed collection of parallel systems • Cyberinfrastructure is made of services (usually Web services) that are “just” programs or data sources packaged for distributed access

  4. e-moreorlessanything and Cyberinfrastructure • ‘e-Science is about global collaboration in key areas of science, and the next generation of infrastructure that will enable it.’ from its inventor John Taylor Director General of Research Councils UK, Office of Science and Technology • e-Science is about developing tools and technologies that allow scientists to do ‘faster, better or different’ research • Similarly e-Business captures an emerging view of corporations as dynamic virtual organizations linking employees, customers and stakeholders across the world. • The growing use of outsourcing is one example • The Grid or Web 2.0 (Enterprise 2.0) provides the information technology e-infrastructure for e-moreorlessanything. • A deluge of data of unprecedented and inevitable size must be managed and understood. • People (see Web 2.0), computers, data and instruments must be linked. • On demand assignment of experts, computers, networks and storage resources must be supported

  5. Virtual Observatory Astronomy GridIntegrate Experiments Radio Far-Infrared Visible Dust Map Visible + X-ray Galaxy Density Map

  6. Grid Capabilities for Science • Open technologies for any large scale distributed system that is adopted by industry, many sciences and many countries (including UK, EU, USA, Asia) • Security, Reliability, Management and state standards • Service and messaging specifications • User interfaces via portals and portlets virtualizing to desktops, email, PDA’s etc. • ~20 TeraGrid Science Gateways (their name for portals) • OGCE Portal technology effort led by Indiana • Uniform approach to access distributed (super)computers supporting single (large) jobs and spawning lots of related jobs • Data and meta-data architecture supporting real-time and archives as well as federation • Links to Semantic web and annotation • Grid (Web service) workflow with standards and several successful instantiations (such as Taverna and MyLead) • Many Earth science grids including ESG (DoE), GEON, LEAD, SCEC, SERVO; LTER and NEON for Environment • http://www.nsf.gov/od/oci/ci-v7.pdf

  7. Old and New (Web 2.0) Community Tools • e-mail and list-serves are oldest and best used • Kazaa, Instant Messengers, Skype, Napster, BitTorrent for P2P Collaboration – text, audio-video conferencing, files • del.icio.us, Connotea, Citeulike, Bibsonomy, Biolicious manage shared bookmarks • MySpace, YouTube, Bebo, Hotornot, Facebook, or similar sites allow you to create (upload) community resources and share them; Friendster, LinkedIn create networks • http://en.wikipedia.org/wiki/List_of_social_networking_websites • Writely, Wikis and Blogs are powerful specialized shared document systems • ConferenceXP and WebEx share general applications • Google Scholar tells you who has cited your papers while publisher sites tell you about co-authors • Windows Live Academic Search has similar goals • Note sharing resources creates (implicit) communities • Social network tools study graphs to both define communities and extract their properties

  8. “Best Web 2.0 Sites” -- 2006 • Extracted from http://web2.wsj2.com/ • Social Networking • Start Pages • Social Bookmarking • Peer Production News • Social Media Sharing • Online Storage (Computing)

  9. Why Web 2.0 is Useful • Captures the incredible development of interactive Web sites enabling people to create and collaborate

  10. Web 2.0 v Grid I • Web 2.0 allows people to nurture the Internet Cloud and such people got Time’s person of year award • Platt in his Blog (courtesy Hinchcliffe http://web2.wsj2.com/the_state_of_web_20.htm) identifies key Web 2.0 features as: • The Web and all its connected devices as one global platform of reusable services and data • Data consumption and remixing from all sources, particularly user generated data • Continuous and seamless update of software and data, often very rapidly • Rich and interactive user interfaces • Architecture of participation that encourages user contribution • Whereas Grids support Internet scale Distributed Services • Maybe Grids focus on (number of) Services (there aren’t many scientists) and Web 2.0 focuses on number of People • But they are basically same!

  11. Web 2.0 v Grid II • Web 2.0 has a set of major services like GoogleMaps or Flickr but the world is composing Mashups that make new composite services • End-point standards are set by end-point owners • Many different protocols covering a variety of de-facto standards • Grids have a set of major software systems like Condor and Globus and a different world is extending with custom services and linking with workflow • Popular Web 2.0 technologies are PHP,JavaScript, JSON, AJAX and REST with “Start Page” e.g. (Google Gadgets) interfaces • Popular Grid technologies are Apache Axis,BPEL WSDL and SOAP with portlet interfaces • Robustness of Grids demanded by the Enterprise? • Not so clear that Web 2.0 won’t eventually dominate other application areas and with Enterprise 2.0 it’s invading Grids

  12. Mashup Tools are reviewed at http://blogs.zdnet.com/Hinchcliffe/?p=63 Workflow Tools are reviewed by Gannon and Fox http://grids.ucs.indiana.edu/ptliupages/publications/Workflow-overview.pdf Both include scripting in PHP, Python, sh etc. as both implement distributed programming at level of services Mashups use all types of service interfaces and do not have the potential robustness (security) of Grid service approach Typically “pure” HTTP (REST) Mashups v Workflow?

  13. Streaming Data Support Archival Transformations Data Checking Hidden MarkovDatamining (JPL) Real Time Display (GIS) Grid Workflow Datamining in Earth Science NASA GPS • Work with Scripps Institute • Grid services controlled by workflow process real time data from ~70 GPS Sensors in Southern California Earthquake

  14. Web 2.0 uses all types of Services • Here a Gadget Mashup uses a 3 service workflow with a JavaScript Gadget Client

  15. Web 2.0 APIs • http://www.programmableweb.com/apis currently (Jan 10 2007) 356 Web 2.0 APIs with GoogleMaps the most used in Mashups • This site acts as a “UDDI” for Web 2.0

  16. The List of Web 2.0 API’s • Each site has API and its features • Divided into broad categories • Only a few used a lot (31 API’s used in more than 10 mashups) • RSS feed of new APIs

  17. Mashups using GoogleMaps Mashup Matrix

  18. Indiana Map Grid(Mashup) GIS Grid of “Indiana Map” and ~10 Indiana counties with accessible Map (Feature) Servers from different vendors. Grids federate different data repositories (cf Astronomy VO federating different observatory collections)

  19. Adapter Adapter Adapter Tile Server Cache Server Google Maps Server Marion County Map Server (ESRI ArcIMS) Hamilton County Map Server (AutoDesk) Cass County Map Server (OGC Web Map Server) Must provide adapters for each Map Server type . Browser client fetches image tiles for the bounding box using Google Map API. Tile Server requests map tiles at all zoom levels with all layers. These are converted to uniform projection, indexed, and stored. Overlapping images are combined. The cache server fulfills Google map calls with cached tiles at the requested bounding box that fill the bounding box. Browser + Google Map API

  20. Mash Planet Web 2.0 Architecture http://www.imagine-it.org/mashplanet Display too large to be a Gadget

  21. Searched on Transit/Transportation Searched on Transit/Transportation

  22. Grid-style portal as used in Earthquake Grid The Portal is built from portlets – providing user interface fragments for each service that are composed into the full interface – uses OGCE technology as does planetary science VLAB portal with University of Minnesota

  23. Note the many competitions powering Web 2.0 Mashup Development Portlets v. Google Gadgets • Portals for Grid Systems are built using portlets with software like GridSphere integrating these on the server-side into a single web-page • Google (at least) offers the Google sidebar and Google home page which support Web 2.0 services and do not use a server side aggregator • Google is more user friendly! • The many Web 2.0 competitions is an interesting model for promoting development in the world-wide distributed collection of Web 2.0 developers • I guess Web 2.0 model will win!

  24. Google Gadgets are an example of Start Page technologySee http://blogs.zdnet.com/Hinchcliffe/?p=8 Typical Google Gadget Structure • … Lots of HTML and JavaScript </Content> </Module> Portlets build User Interfaces by combining fragments in a standalone Java Server Google Gadgets build User Interfaces by combining fragments with JavaScript on the client

  25. So there is more or less no architecture difference between Grids and Web 2.0 and we will use e-infrastructure or Cyberinfrastructure to refer to either architecture We should bring Web 2.0 People capabilities to Grids (eScience, Enterprises) We should use robust Grid (motivated by Enterprise) technologies in Mashups See Enterprise 2.0 discussion at http://blogs.zdnet.com/Hinchcliffe/

  26. Grids/Web 2.0 enable distributed activities to be effective • Enable Generalized Outsourcing – Enterprises can be split with components (centers of expertise) separated • Software is easiest as “all electronic” but also can link • Apparel Industry i.e. Manufacturing • Sports training • Change model for Publishers and Libraries as current model where publishers own material fits poorly with technology as prevents innovative access • Enable new communities to contribute to research, education and commerce • The advantages of R1 powerhouses with concentrated expertise are reduced by electronic linkage of distributed new contributors • The Navajo communities can be integrated and participate in global activities from their homeland • Enable new generation of open powerful distributed systems supporting • Command and Control (Crisis Management in civilian application) • Study of impact of Global warming on polar regions • Integration of sensors and simulation for Earthquake prediction

  27. eApparel • Much of the world’s manufacturing industry is globalized and the apparel/textile industry is typical • We are working with Hong Kong Textile Industry to link the Asian manufacturers with design/marketing/purchase functions elsewhere (USA, Europe) • Need to exchange designs, available fabrics and discussions • Good example of e-infrastructure enabling specialization in one geographical area to thrive • Software and digital animation outsourcing are other good examples

  28. eSports? • YouTube illustrates asynchronous video sharing and video conferencing illustrates synchronous video sharing • One can link trainers (or spectators) and athletes (exercisers) globally with real time video supporting video and text annotation • Technically hard due to network issues and allowing real-time playing of annotated video • Exploring with China and HPER • Note IU could export coaching in Soccer, Basketball etc • Example of e-infrastructure supporting geographically distributed specialization

  29. MyResearchDatabase Bibliographic Database Web serviceWrappers Web 2.0 Semantic Scholars Grid MySpace Windows Live Academic Search Traditional GridCyberinfrastructure Export:RSS, BibtexEndnote etc. Del.icio.us Google Scholar CiteULike Citeseer Connotea Science.gov Bibsonomy PubChem Biolicious Generic Document Tools MASHUP PubMed CMT ConferenceManagement Manuscript Central Community Tools Integration/Enhancement User Interface etc. Existing User Interface New Document-enhanced Research Tools Existing Documentbased Tools

  30. Delicious Semantic Web/Grid • http://del.icio.us purchased by Yahoo for ~$30M • http://www.CiteULike.org • http://www.connotea.org (Nature) • Associate metadata with Bookmarks specified by URL’s, DOI’s (Digital Object Identifiers) • Users add comments and keywords (called tags) • Users are linked together into groups (communities) • Information such as title and authors extracted automatically from some sites (PubMed, ACM, IEEE, Wiley etc.) • Bibtex like additional information in CiteULike • This is perhaps de facto Semantic Web – remarkable for its simplicity • We built Mashup linking to del.icio.us, CiteULike, Connotea allowing exchange of tags between sites and between local repositories • Repositories (MyResearch) also link to local sources (PubsOnline) and Google Scholar and Microsoft Academic Live

  31. del.icio.us Tags Download to Local System del.icio.us Tags

  32. General Document Semantic Analysis • Citeseer and Google Scholar scour the Internet and analyze documents for incidental metadata • Title, author and institution of documents • Citations with their own metadata allowing one to match to other documents • These capabilities are sure to become more powerful and to be extended • Give “Citation Index” in real time • Tell you all authors of all papers that cite a paper that cites you etc. (Note it’s a small world so don’t go too far in link analysis) • Tell you all citations of all papers in a workshop • Helps journal editor by suggesting referees based on document analysis or by doing a “plagiarism” analysis by scoring comparison with other Internet documents

  33. Domain Specific Semantic Document Analysis • It is natural to develop core document Servicessuch as those used in Citeseer/Google Scholar but applied to “your” documents of interest that may not have been processed yet • As just submitted to a conference perhaps • These tools can help form useful lists such as authors of all cited or submitted papers to a journal • OSCAR3 (from Peter Murray-Rust’s group at Cambridge) augments the application independent “core” metadata (Title, authors, institutions, Citations) with a list of all chemical terms • This tool is a Service that can be applied to “your” document or to a set of documents harvested in some fashion • Luis Rocha has developed related ideas for Biology • Other fields have natural application specific metadata and OSCAR like tools can be developed for them • This is another Semantic Scholar Grid Tool

  34. OSCAR3 Chemistry Document analysis • It detects “magic” chemical strings in text and then • Stores them as metadata associated with document • Queries ChemInformatics repositories to tell you lots of information about identified compounds • Tells you which other documents have this compound

  35. Initial Results from OSCAR on PubMed • We have a small sample (100) of full text Chemistry papers selected at random from 15 years of PubMed with over 5 million abstracts • OSCAR3 generates 4.17 compound names per abstract • and 36.7 compound names per full text • 555,007 PubMed abstracts of 2005 – 2006 (part) used for Abstracts (on Big Red) • Illustrates how much knowledge journal publishers are hiding from us

  36. CICC Chemical Informatics Cyberinfrastructure Collaboratory MOAD Database Integrating document (OSCAR) and conventional services on the IU Big Red Supercomputer PubMed Database OSCAR Text Analysis Cluster Grouping Toxicity Filtering Docking PubChem Database Initial 3D Structure Calculation NIH PubChem Database NIH PubChem Database Molecular Mechanics Calculations Product databases are wrapped with Web service interfaces and are suitable for inclusion in Taverna workflows. Quantum Mechanics Calculations IU’s Varuna Database POV-Ray Parallel Rendering

  37. Knowledge Model for Scientific Journals • There are classes of scientific journals • Large circulation society journals effectively subsidized by fees of professional society membership; circulations can be more than 10,000 • “Popular” magazine style journals • A few prestigious journals • Many specialized journals publishing archival refereed papers with circulations from one hundred to a few thousand • The specialized journals largely sell a mix of paper and (a growing number of) electronic subscriptions to libraries and very few individuals subscribe • Access is limited and expensive • Even if one subscribes, one is often restricted on the number of full text papers one can access • Collections like PubMed only include abstracts • Systems like OSCAR3,Google Scholar, Microsoft Academic Live and Citeseer cannot fully analyze knowledge in papers unless get access to full text • Current publishing model hindering and not helping science • Similar discussion for journal papers and research data

  38. Publishing Business Model in the Internet Age • Journal publishing currently has a business model where the price reflects neither the cost nor the value-added • Publishers currently do not have significant internal expertise in new approaches/technologies to drive new business models • However much is outsourced already and so one can outsource to organizations with new expertise e.g. to those that know Web 2.0 rather than putting ink on paper • There is no clear new business model but plausible that current model will not survive for that long • So need to change even if less lucrative or success unclear • Note libraries provide funds to publishers and libraries will continue • Some think that one role of university libraries will be curation of data produced by university faculty and this will move naturally to different business models

  39. Strengths of Current Publishing Model • Permanent “guaranteed” archival storage but there are other approaches such as Amazon S3 to this • Uniform look and feel and copyediting to remove language errors. • Useful but not so valuable that we can trade access for this. • In particular can only correct some language errors as only a subject expert can really rewrite in good grammar and expression • Refereeing of a quality implied by the journal and the editorial board • Most important strength but business model does not directly reflect this as only a small part of subscription price goes to editorial function • For most papers cost of refereeing much less than other costs of producing paper • Not clear why viewer should pay for refereeing • Large amount of pre-existing papers from old issues of journals

  40. Pressures on Current Publishing Model • Mandated open access to scholarly work funded by government • Cornyn-Lieberman bill in the US • NIH PubMed Central requires deposited of full text of articles after a length of time • Electronic access to publisher sites is not especially good • Division of articles into journals and publishers is not very helpful today where technology does not care about location of information • Location is just a rather simple annotation (meta data) specifying aspects of provenance of article • Publishing on the Internet is not a valuable service and has been addressed by Web servers in general and by Web 2.0 in attractive ways • Essentially nobody reads or even has access to paper copies of journal • Not clear it is useful to print specialized journals on paper

  41. Scholarly Research Community Site • Best product should allow one to make best use of knowledge in scholarly publications and data but not be tied to “fragile”” attractive services • So preserve data (annotations, comments, people) managed by services separately • Should integrate journal and conference publications and services • Should contain integrated or support outside services for curation, annotation, analysis and search • Content is scholarly journals and data • Services include • Share data and set up communities • Annotation as in Connotes, CiteULike, Del.icio.us • Semantic analysis for citations, authors, chemical compounds etc. • Biolicious style custom classifications including added value contacts • Search as in Google Scholar, Microsoft Academic Live • MySpace/Facebook/LinkedIn style services for existing or new contacts • Support of conference and journalrefereeing • Other conference/journal services such as registration, advertising • Integration with research such as electronic log books • Internal integration e.g. Authors in citations are linked to community • Links to more general document services such as: • Online Office style Tools • WebEx type collaboration

  42. Business Model for Scholarly Journal/Research Community Site • One can charge for advertising, better content, better services or better implementation • Natural is to start with a basic free content and services with advertising. • Content must be free eventually “by law” • Services will have open source versions anyway so counter this with free basic services • One could use page charge model for charging for refereeing. • One charges user for features that add value. These include: • Better or better implemented community/digital library services • Premium Content possibly contracted by site owner • Problem with Advertising Business model: Audience specialized (i.e. small) but upscale • Problem with charging for Community Tools: Competing with free software but likely can offer much better service than free software just as WebEx does fine in spite of free VNC

  43. Basic Idea of Cyberinfrastructure for MSI’s • Cyberinfrastructure is critical to all involved in Research and Education • Cyberinfrastructure is intrinsically democratic supporting broad participation • MSI’s (Minority-Serving Institutions) should lead MSI integration with Cyberinfrastructure to ensure it is truly useful for them and consistent with goals and constraints • One should guide the projects with experts • One should aim at scalable (systemic) approaches • Goal is peer collaborations involving all institutions of higher education

  44. Some Key Organizations in MSI-CIEC • MSI-CIEC Minority-Serving Institution Cyberinfrastructure (CI) Empowerment Coalition involves UHD, IU, AIHEC, HACU, NAFEO • UHD University of Houston Downtown as a major Hispanic Serving Institution • Alliance for Equity in Higher Education. Working with the Alliance will have systemic impact on at least 335 Minority Serving Institutions covered by the • AIHEC American Indian Higher Education Consortium) • HACU Hispanic Association of Colleges and Universities • NAFEO National Association for Equal Opportunity in Higher Education • Indiana University is correctly not a very key organization here! We advise and will build a Web 2.0 MSI Portal with 3 NSF and one (Lumina) foundation proposal

  45. Minority Serving Institutions and the Grid • Historically the R1 Research University powerhouses dominated research due to their concentration of expertise • Cyberinfrastructure allows others to participate in same way it supports distributed open source software and distributed Web 2.0 • Navajo Nation (Colorado Plateau covering over 25,000 square miles in northeast Arizona, northwest New Mexico, and southeast Utah) with 110 communities and over 40% unemployment. Building a wireless grid for education, healthcare • http://www.win-hec.org/ World Indigenous Nations Higher Education Consortium • Cyberinfrastructure allows Nations to preserve their geographical identity but participate fully with world class jobs and research • Some 335 MSI’s in Alliance have similar hopes for Cyberinfrastructure to jump start their advancement!

  46. Typical Illustration of effect of Climate Change on Greenland: Velocity of Jakobshavn from 1995 to 2005 as a function of distance from its end Example: Setting up a Polar CI-Grid • The North and South poles are melting with potential huge environmental impact • As a result of MSI meetings, I am working with MSI ECSU in North Carolina and Kansas University to design and set up a Polar Grid (Cyberinfrastructure) • This is a network of computers, sensors (on robots and satellites), data and people aimed at understanding science of ice-sheets and impact of global warming • We have changed the 100,000 year Glacier cycle into a ~50 year cycle; the field has increased dramatically in importance and interest • Good area to get involved in as not so much established work

  47. PolarGrid • Important Polar Grid Cyberinfrastructure components include • Managed data from sensors and satellites • Data analysis such as SAR processing – possibly with parallel algorithms • Electromagnetic simulations (currently commercial codes) to design instrument antennas • 3D simulations of ice-sheets (glaciers) with non-uniform meshes • GIS Geographical Information Systems • Also need capabilities present in many Grids • Portal i.e. Science Gateway • Submitting multiple sequential or parallel jobs • Power/Bandwidth Challenged Expedition Grids

  48. Polar Expeditions F F F B B B F F F Archival – High Latency IU Adaptorlayer Educationand Training Real Time Monitor Low Bandwidth ECSUHaskell Core simulationand Data analysis Field Base Camps ECSU IU Existing IU Real Time Monitor Low Bandwidth Existing CRESIS Archival – High Latency TeraGrid Other Polar Sensors andSensor Aggregators (Non-polar and Polar Sites) OSG Prototype Base/Field Grid

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