STICK: Science & Technology Innovation Concept Knowledge-base

Transcription

1 AAAS+NSF SciSIP Workshop: Building a Community of Practice II Washington, DC, October 19, 2010 STICK: Science & Technology Innovation Concept Knowledge-base Ping Wang Ben Shneiderman Yan Qu

2 Why Do We Develop STICK? Artificial or disciplinary divide between Science and technology Invention and innovation Innovation production/supply and use/demand Over-emphasis on success Lack of tools for analyzing large-scale data So We develop STICK to capture large-scale, multisource, multi-field, longitudinal data on successful and failed innovations and to advance visual analytic tools for using such data. 2

3 Where Do Data Come From? News & trade press ProQuest newspapers Lexis-Nexis Factiva Scholarly work Web of science Google scholar ProQuest dissertations ACM Digital Library Company data Hoovers Wharton Research Data Services (WRDS) Patents USPTO Full-text & image database (PatFT) and application fulltext & image database (AppFT) Google patents Government funding NSF and NIH awards Social/informal media Wikipedia Techmeme Slashdot 3

4 What Is In STICK? Three fields IT, biotech, & nanotech Innovations Concepts Products/services People/organizations Developers/producers Universities, research labs, vendors Adopters/users Companies, nonprofits Intermediaries Relationships Among innovations Broader, narrower, complementary, competing Among actors Collaborative, affiliated transactional, competitive Btw innovation & actor Invent, commercialize, invest, adopt Time of relationship 4

5 Is STICK Useful? (Study 1) Trade Press Articles TM=Treemaps CT=Cone Trees HT=Hyperbolic Trees Academic Papers Trajectories help tell Innovation success/failure stories. Patents Shneiderman et al

6 Is STICK Useful? (Study 2) Popularity shapes impact of innovation Adjusted number of articles on IT innovations except e-commerce Groupware BPR Data Warehouse ERP ASP E-Commerce CRM KM Adjusted number of articles on e-commerce Wang 2010 BPR ERP KM Data Warehouse Groupware CRM ASP E-Commerce 6

7 7 Is STICK Useful? (Study 3) VPN DLearn DSL Telecommute SmartCard PDA Multimedia WiFi IM DigiCam GPS TabletPC Bluetooth MP3 RFID Web2.0 Wiki Wikipedia YouTube SocNet MySpace Blog iphone ipod Linux WebServ SOA UtiComp CloudCom Virtualization OSS ExpertSys NeuralNet AI OLAP DecisionSS Outsource ecom ERP CRM ebiz ASP EDI Grpware SFA SCM DW KM BI BizProReen VPN VPN DLearn DSL Telecommute SmartCard PDA Multimedia WiFi IM DigiCam GPS TabletPC Bluetooth MP3 RFID Web2.0 Wiki Wikipedia YouTube SocNet MySpace Blog iphone ipod Linux WebServ SOA UtiComp CloudCom Virtualization OSS ExpertSys NeuralNet AI OLAP DecisionSS Outsource ecom ERP CRM ebiz ASP EDI Grpware SFA SCM DW KM BI BizProReen DLearn DSL Telecommute SmartCard PDA Multimedia WiFi IM DigiCam GPS TabletPC Bluetooth MP3 RFID Web2.0 Wiki Wikipedia YouTube SocNet MySpace Blog iphone ipod Linux WebServ SOA UtiComp CloudCom Virtualization OSS ExpertSys NeuralNet AI OLAP DecisionSS Outsource ecom ERP CRM ebiz ASP EDI Grpware SFA SCM DW KM BI BizProReen Tsui et al Dashboard helps monitor relations among innovations.

8 Is STICK Useful? (Study 4) Dashboard helps monitor innovation, community, and their interactions. Zhang et al

9 How to Make STICK More Useful? STICK helps researchers & policy makers Monitor and make sense of innovations Find evidence in theorizing and policy-making Social computing system allows users to Specify fields and domains Suggest innovations to study Specify level of abstraction Suggest additional attributes e.g., innovation benefits, unintended consequences 9

10 Who Are We? PopIT: Scalable Computational Analysis of the Diffusion of Technological Concepts STICK: Science & Technology Innovation Concept Knowledge-base Thanks to National Science Foundation for grants IIS (HSD) and SBE (SciSIP) STICK.ischool.umd.edu 10

11 References Shneiderman, B., Wang, P., Qu, Y. and Dunne, C. Analyzing Trends in Science & Technology Innovation, in Proceedings of the 27th Annual Human-Computer Interaction Lab Symposium, College Park, MD, Tsui, C.-j., Wang, P., Fleischmann, K.R., Oard, D.W., and Sayeed, A.B., Exploring the Relationships among ICTs, in Proceedings of the 43rd Hawai'i International Conference on System Sciences, Kauai, HI, Wang, P., 2010, Chasing the Hottest IT: Effects of Information Technology Fashion on Organizations, MIS Quarterly, 34(1), pp Zhang, P., Qu, Y., and Huang, C., Designing a Multi-layered Ontology for the Science and Technology Innovation Concept Knowledge-base, in Proceedings of the 44th Hawai'i International Conference on System Sciences, Kauai, HI,