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New Perspectives for Business Intelligence: Library and Research Technologies and Research Collaboration for New Data Models
 

New Perspectives for Business Intelligence: Library and Research Technologies and Research Collaboration for New Data Models

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This is our presentation for Educause 2012 entitled New Perspectives for Business Intelligence: Library and Research Technologies and Research Collaboration for New Data Models held on Nov 8, 2012.

This is our presentation for Educause 2012 entitled New Perspectives for Business Intelligence: Library and Research Technologies and Research Collaboration for New Data Models held on Nov 8, 2012.

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  • barnettw@indiana.edu – winkler4@upenn.edu – jgz10101@gmail.com
  • Opening: Here to discuss Penn’s Metridoc project. Presentation is divided into 4 chapters (Task, Challenge, BI Framework, Strategic Priorities—infrastructure/collaboration), a prologue on Organizational Learning and an epilogue on Opportunity and Transformation
  • Throughout several years of work on management information services, I saw the uderlying priority being the need to support decision-making, to discover best practice, drive efficiency and the like. All those are worthy and important goals, but I’ve come to realize the overarching significance of behind business or organizational intelligence is, Learning—fostering and expanding the organization’s capacity to learn. This is what we need tools like metridoc to do.
  • This quote from Hagel and Brown captures the idea nicely as it places it into the context of disruptive change—the change that’s so apparently obvious in libraries…
  • So the task is really this… It’s not a novel idea, the conversation about the learning organization is a pretty well-worn idea, but it does help define the task before libraries and indeed other aactors on campus engaged in academic support.
  • Here it is in three connect ideas….
  • So there are many challenges to surmount in developing robust BI capabilities in organizations that don’t have broad experience in the field, but libraries have pecular issues of their own. It’s the breadth and depth of our service profile.
  • Consider this question
  • Examples
  • And behind this array of products and services is an equally broad set of supporting systems each with a trove of data containing useful information to help us learn what users do, how they do it, why and with what expectation from their partners, like the library.
  • In thinking about a framework, it helps to begin localizing the challenge. We’re good at operating the systems of the enterprise and we may have cobbled together some solutions of doing analysis, but libraries and many academic support providers like the basic infrastructure to draw these pieces together into a mutually supportive system of capabilities.
  • The framework has to be designed around the event as its working model…
  • Here’s an event captured in the slice of ezproxy log… point out some elementsIP- ( a proxy for the users environment) date, time, resource consulted (PsychInfo) , technology employed (all the stuff about agents), a link between this log and a system to look up normalized resource name (Proxysession ID), and finally, and SFX id that be resolved into a citation., and finally a penn credential for detailed information about who is engaged in this moment of discovery. Granular, detailed, heavy with information about a user and their situation
  • An abstract representation of the real life event that preceded this slide
  • Need a system to capture, and make available the event data so described above. Summary of what metridoc does in this context
  • What’s the strategic priority here: What it’s not, what it is….The next slides talk about collaboration as a key priority for building BI capacity, and about organizational readiness (resources, talent, time, community sourcing and governance) rather than technology being the key.
  • There important opportunities here for us and the campus: to improve the reach and effectiveness of current service, to design new services, to realize collective aspirations (eg collective data on resource sharing driving collection development and access models of the future for collections that will be increasingly distributed and ephemerally used.
  • Technical summary. Where we are today.

New Perspectives for Business Intelligence: Library and Research Technologies and Research Collaboration for New Data Models New Perspectives for Business Intelligence: Library and Research Technologies and Research Collaboration for New Data Models Presentation Transcript

  • November 7, 2012
  • New Perspectives for BusinessIntelligence: Library and ResearchTechnologies and ResearchCollaboration for New Data ModelsWilliam Barnett-Indiana UniversityRobert H. McDonald (@mcdonald)-Indiana UniversityMike Winkler (@winkler4)-University of PennsylvaniaJoe Zucca-University of Pennsylvania November 8, 2012
  • Tweet Us: #EDU12 #E12_SESS113 http://slidesha.re/ #busintel #EDU12
  • BI Research Engage PageTake Notes-Ask Questions? http://bit.ly/RHg0C8
  • Outline General Strategies for Research Business Intelligence in the Academy Data Openness/Transparency for Research Business Intelligence Research Business Intelligence Use Cases  Research Support/Team Science  Libraries Discussion on comprehensive strategies and needs for Research Business Intelligance in the academy Tweet us: #EDU12 #busintel #E12_SESS113
  • Consortia Science teste Birney, Nature 489 Tweet us: #EDU12 #busintel #E12_SESS113
  • Team Science Tweet us: #EDU12 #busintel #E12_SESS113
  • BI Data Supporting Consortia Science Tweet us: #EDU12 #busintel #E12_SESS113
  • IU Faculty Profile Mapping Tweet us: #EDU12 #busintel #E12_SESS113
  • Typical VIVO Data Ingest/Cleaning WorkflowRIS2N3 Components LOCAL CLIENT SERVER CONTEXT RIS FILES VIVO RIS2N3 Jena N3 Jena MySQL Tweet us: #EDU12 #busintel #E12_SESS113 https://github.com/dgcliff/RIS2N3
  • Varying Views of Research Intelligence Data Administrator View Researcher View Research Intelligence Development View Team Science View Tweet us: #EDU12 #busintel #E12_SESS113
  • Types of Systems in the RI Path Faculty Profile Systems Faculty Annual Review Systems Research Profile Systems  Research Profile System Comparative Analytics (Peer to Peer) Resource Profile Systems Research Management Systems Tweet us: #EDU12 #busintel #E12_SESS113
  • Open Source vs Vended Systems Faculty Profile/Networking Systems  Open Source  VIVO  Digital Vita  Loki  Harvard Profiles  CAP/Stanford Profiles  Vended  Symplectics (MacMillan part of Digital Science)  SciVal Experts (Elsevier)  Pivot (Proquest)  Research In View (Thomson Reuters) Tweet us: #EDU12 #busintel #E12_SESS113
  • Data Openness and Transparency Tweet us: #EDU12 #busintel #E12_SESS113
  • Research Data, Instruments and Resources Tweet us: #EDU12 #busintel #E12_SESS113
  • Linked Open Data in the Enterprise Not at Enterprise Level  Graph Databases  NoSQL Stacks  Semantic Triple Store Systems Data Policy/ Governance  Public Profiles  Faculty  Resources  Instruments Tweet us: #EDU12 #busintel #E12_SESS113
  • Thank you! Robert H. McDonaldrhmcdona@indiana.edu Tweet us: #EDU12 #busintel #E12_SESS113
  • Business Intelligence inTranslational Research:Research Networking as aTest CaseWilliam Barnett, Indiana University
  • Tweet us: #EDU12 #busintel #E12_SESS113
  • How Traditional Research Works… Get FundingWrite Proposal Do Research Publish Results Tweet us: #EDU12 #busintel #E12_SESS113
  • How Traditional Medical Research Works…Basic Pre-clinical Clinical Pharma Tweet us: #EDU12 #busintel #E12_SESS113
  • How CTSAs want Translational Research to Work Tweet us: #EDU12 #busintel #E12_SESS113
  • Why Research Networking?Translational research is a team sport1. Investigators don’t know of potential collaborators in their institutions to improve research2. Investigators don’t know of complementary investigators or opportunities to make their projects more competitive.3. Investigators don’t know of partners to cross translational boundaries.4. Investigators don’t know of non-research partners (industry, public sector, public) needed for trials recruitment, implementation, or commercialization Tweet us: #EDU12 #busintel #E12_SESS113
  • What is Research Networking?1. An approach that strives to help overcome barriers by connecting people to undertake translational research2. Institutional repositories to manage rich faculty profiles of grants, publications, classes, etc. and expose them publicly.3. An information model based on individuals and cohorts.4. A national federated architecture of Linked Open Data that can connect these repositories.5. Applications that consume these profile data to accomplish translational goals Tweet us: #EDU12 #busintel #E12_SESS113
  • NIH Investments in Research Networking VIVO – a project to develop an ontology and architectural standards to create, manage, and share rich faculty profile information. Eagle-I – a project to develop an ontology and architectural standards to create, manage, and share rich resource profile information CTSAConnect – a project to create an integrated ontology to connect faculty, resource, and other dataIt’s all about Linked Open Data… Tweet us: #EDU12 #busintel #E12_SESS113
  • What are Big Challenge Use Cases inTranslational Research?1. Finding Funding2. Recruiting Volunteers for Clinical Trials3. Creating Translational Teams/Processes4. Education and Training Tweet us: #EDU12 #busintel #E12_SESS113
  • How Does NIH measure Translational Success? Logic Model from each CTSA, documented as XML files, exported to NIH annually. Logic Model is:  Activities – things that happen  Outcomes – science that results from the things that happen  Impacts – what good comes of the science that comes from the things that happenThis is what we’ll use today… Tweet us: #EDU12 #busintel #E12_SESS113
  • How can Research Networking HelpFind Funding?By matching investigators with fundingopportunities Activities – Community of Science and SciVal Funding commercial applications potentially provide better funding matches Outcomes – unknown if they are any better than traditional means Impacts – unclear if there is any differentiation Tweet us: #EDU12 #busintel #E12_SESS113
  • How can Research Networking HelpRecruiting Volunteers?By matching researchers with communitygroups and volunteers Activities – A few initial attempts to start developing VIVO-like profiles of community groups Outcomes - None Impacts - None Tweet us: #EDU12 #busintel #E12_SESS113
  • How can Research Networking Help Creating Translational Teams?With Applications that are used to discover complimentary andnext step collaborators Activities – Many faculty profile systems developed and implemented and one national pilot, direct2experts.org, has been launched Outcomes – some CTSAs show increased activity among groups that have not collaborated before Impacts – some new teams and multi-team systems have begun to form. Unclear of link to profile systems. Tweet us: #EDU12 #busintel #E12_SESS113
  • Direct2Experts • 44 Institutions (at present). • Returns summary numbers by institution. • Finding individuals is a manual institution-by- institution basis. Tweet us: #EDU12 #busintel #E12_SESS113
  • CTSAConnect (ctsaconnect.org)A semantic framework that will facilitate the production andconsumption of Linked Open Data aboutinvestigators, physicians, biomedical researchresources, services, and clinical activities. Use cases: Team Formation Cross-Institutional Collaboration Evaluation and ReportingBut… Where are the applications? Tweet us: #EDU12 #busintel #E12_SESS113
  • How can Research Networking HelpEducation and Training?Mentor matching and MD – PhD awareness Activities - mentoring has been happening and translational education programs have sprung up without these systems Outcomes – no use of Research Networking Impacts – none. Tweet us: #EDU12 #busintel #E12_SESS113
  • Other BI Roles for Research Networking?  Investigators  Automated CV generation, particularly for center grants  Research topic trend analysis  Administrators  Competitive landscape review  Productivity assessments for tenure, etc.  Research  Network Science and Science of Team Science Tweet us: #EDU12 #busintel #E12_SESS113
  • Rich profiles could help findcollaborators, subjects, resources, mentors, and funding and pursueother, undetermined, great things.There are business models that can helpsustain an institutional strategyChallenges: applications that delivervalue, policy, data quality, and momentum.It is early yet, and this has so Tweet us: #EDU12 #busintel #E12_SESS113 far been atechnology looking for a problem to solve.
  • Thank you! Bill Barnett barnettw@iu.eduThanks to Dave Eichmann for reviewing an early version of this presentation! Tweet us: #EDU12 #busintel #E12_SESS113
  • Mike Winkler | Joe ZuccaUniversity of Pennsylvania Libraries
  • Tweet us: #EDU12 #busintel #E12_SESS113
  • Tweet us: #EDU12 #busintel #E12_SESS113
  • Tweet us: #EDU12 #busintel #E12_SESS113
  • ’’ Tweet us: #EDU12 #busintel #E12_SESS113
  • Tweet us: #EDU12 #busintel #E12_SESS113
  • Tweet us: #EDU12 #busintel #E12_SESS113
  •  Tweet us: #EDU12 #busintel #E12_SESS113
  • Tweet us: #EDU12 #busintel #E12_SESS113
  • Tweet us: #EDU12 #busintel #E12_SESS113
  • Tweet us: #EDU12 #busintel #E12_SESS113
  • Tweet us: #EDU12 #busintel #E12_SESS113
  • xxx.xx.xxx.xxx|-|zucca|[26/Jul/2007:15:41:01 -0500]| GEThttps://proxy.library.upenn.edu:443/login?proxySessionID=10335905&url=http://www.csa.com/htbin/dbrng.cgi?username=upenn3&access=upenn34&cat=psycinfo&adv=1 HTTP/1.1|302|0|http://www.library.upenn.edu/cgibin/res/sr.cgi?community=59|Mozilla/5.0 (Macintosh; U; PPC Mac OS X; en) AppleWebKit/418.9.1(KHTML, like Gecko) Safari/419.3| NGpmb6dT6JXswQH__utmc=94565761;ezproxy=NGpmb6dT6JXswQH;hp=/;proxySessionID=10335514; __utmc=247612227;__utmz=247612227.1184251774.1.1.utmccn=(direct)|utmcsr=(direct)|utmcmd=(none);UPennLibrary=AAAAAUaWP5oAACa4AwOOAg==;sfx_session_id=s6A37A3E0-3B8E-11DC-80E985076F88F67F Tweet us: #EDU12 #busintel #E12_SESS113
  • Srvice Genre Library Cognzt Staff Parameters Orgn’l Unit User & Program Budget cntrParameters College | Dept Bibliographic Parameters Rank Course Title Host College Date | Time URI Host Dept Location Format Environmental Instructor IP Address Parameters Cost| Supplr Grant Spnsr URL Tweet us: #EDU12 #busintel #E12_SESS113
  • Tweet us: #EDU12 #busintel #E12_SESS113
  • Tweet us: #EDU12 #busintel #E12_SESS113
  • ’ Analytics Repository Tweet us: #EDU12 #busintel #E12_SESS113
  • “ ” “ ” ” Tweet us: #EDU12 #busintel #E12_SESS113
  • Tweet us: #EDU12 #busintel #E12_SESS113
  • Tweet us: #EDU12 #busintel #E12_SESS113
  • Tweet us: #EDU12 #busintel #E12_SESS113
  • Questions? Online – Tweet them to us:  #EDU12 #busintel Or write them into our engage page  http://bit.ly/RHg0C8 (open googledoc) Tweet us: #EDU12 #busintel #E12_SESS113
  • MetriDoc Tiered Architecture Abstracts 4 key functions, exposes interfaces for interoperability 1. Extract 2. Transform 3. Load 4. Query Target Source, Resolution Results e.g. Relais, Sources Document Illiad, ILS e.g. IdM, WorldCat Ingest Log Query Srvc Resolve User Parse Codes & IDs Interface Normalize Data Format Repo Refined Refined output output Local Query Data Document Stores Tweet us: #EDU12 #busintel #E12_SESS113