1 / 24

General approaches to data quality and Internet generated data

General approaches to data quality and Internet generated data. associate professor Karsten Boye Rasmussen kbr@sam.sdu.dk Institute of Marketing and Management University of Southern Denmark Campusvej 55, DK-5230 Odense M, Denmark +45 6550 2115 fax: +45 6593 1766

akira
Download Presentation

General approaches to data quality and Internet generated data

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. General approaches to data quality and Internet generated data • associate professor Karsten Boye Rasmussen • kbr@sam.sdu.dk • Institute of Marketing and Management • University of Southern Denmark • Campusvej 55, DK-5230 Odense M, Denmark • +45 6550 2115 fax: +45 6593 1766 • Areas: organization and information technology, business intelligence • 'it, communication and organization' www.itko.dk HandbookLondon 2007 1 kbr

  2. Internet improving data quality • concepts and dimensions of data quality • consequences of having poor data quality! - the intuitive approach • what are you talking about? - empirical approach • what can the system talk about? - the ontological • 'fitness for use' - metadata and the dimension of 'documentality' • categories of data generated on or in relation to the Internet • primary data (being generated for this particular use) and secondary • data response (survey questionnaire S-R) • non-reactive sources: • e-mails, blogs, Internet web-logs (on hits, visits, users, etc.), commercial transaction data • mixing methods • data being: validated, used, and plentiful HandbookLondon 2007 2 kbr

  3. The intuitive approach to data quality • data quality metrics • proportion experiencing problems with data quality • 'that 75% of 599 companies surveyed experienced financial pain from defective data' • 'about 14% of the potential taxes due are not collected' • summarized metric of the financial loss • 'poor data management is costing global businesses more than $1.4 billion per year' • error rates of data fields • about 1-5 per cent • but are they all equal? HandbookLondon 2007 3 kbr

  4. Intuitive dimensions • Some OK dimensions • The intuitive approach certainly lacks method with rigor • A somewhat unsystematic and sporadic description HandbookLondon 2007 4 kbr

  5. The empirical approach to data quality • also in committee work HandbookLondon 2007 5 kbr

  6. The theoretical foundation of data quality • Information System (IS) as a representation • of the Real World system (RW) • The ontological approach (Wand & Wang, 1996) • The data representation and recording (Fox et al., 1994) • The conceptual view (Levitin & Redman, 1995) • The systems approach (Huang et al., 1999:34) • the semantics part of the semiotic approach (Price and Shanks, 2004) HandbookLondon 2007 6 kbr

  7. Three categories of 'deficiencies' • a quite "binary" view HandbookLondon 2007 7 kbr

  8. Media approach to data quality • Syntactic quality is thus how well data corresponds to stored meta-data, which can be exemplified by conformance to contingencies of the database • Semantic quality is how the stored data corresponds to the represented external phenomena • Pragmatic quality is how data is suitable and worthwhile for a given use • ("semiotics", Price and Shanks) HandbookLondon 2007 8 kbr

  9. Fitness for use • The 'proof of the pudding' for data quality is the use of the data • 'All the news that's fit to print' New York Times • semiotic framework with degree of objectivity ranging from the syntactic 'completely objective' to the pragmatic 'completely subjective' • 'fitness for use' is subjectivity • 'The single most significant source of error in data analysis is misapplication of data that would be reasonably accurate in the right context' • Error 40 • The relativity moves the attention from the data to the user HandbookLondon 2007 9 kbr

  10. Use, metadata and documentality • data is description - of reality • description of data - is metadata • DDI 'The Data Documentation Initiative' • The quality measures of validity, reliability, accuracy, precision, bias, representativity, etc. • only available through the documentation of the data • the metadata • high documentality means the dataset is a 'pattern' and 'model' HandbookLondon 2007 10 kbr

  11. Errors in survey data • survey is the "ability to estimate with considerable precision the percentage of a population that has a particular attribute by obtaining data from only a small fraction of the total population" (Dillman, 2007) HandbookLondon 2007 11 kbr

  12. Internet & Research • a shift in the medium for data collection • self administered • web surveys • e-mail surveys • e-mail with links • the link points to a web-questionnaire • a mixed-mode within the Internet media • e-mail with attached questionnaire • the questionnaire in software formats (Word of PDF) • e-mail text without attachments or links - answering mail • 3-5 questions • PLUS • completely new type of direct recording of actual behavior in electronic non-reactive data HandbookLondon 2007 12 kbr

  13. Web survey - some problems • uneven accessibility to the Internet • unevenness in regard to the technical abilities • bandwidth, computing power, and software (web-browsers) • however general web-site competences exist • and telephone ownership is now too widespread • - an other medium needed • no random mail generation HandbookLondon 2007 13 kbr

  14. Web survey - the many pros • some reliable e-mail registers do exist • random selection - but not random generated ;-) • CAxI (Computer assisted telephone interviewing) • more complicated structures possible in the answering • software will enforce consistent rule following • experiments using different sequencing of questions • the use of paradata in web (later) HandbookLondon 2007 14 kbr

  15. Web survey - the respondent • Internet coverage, sampling, and the right respondent • sampling is not secured by a large number of respondents • the problem of self-selection • a systematic bias • have to secure the right - or at least only one respondent on the inquiry • the new problem of a 150 per cent answer rate • log-in procedure with a PIN-code is recommended HandbookLondon 2007 15 kbr

  16. Web survey - success and hazard • quicker turnaround than through the postal or face-to-face questionnaire • raising the data quality by securing timely data • the Internet surveys have a much lower 'marginal cost' • with the Internet and supportive software for web surveys • many more surveys are taking place • maybe too many • respondents tend to be more reluctant to participate in surveys HandbookLondon 2007 16 kbr

  17. Secondary data – a richness of data • The data is ready to use • data is being made available and retrievable • raising the data quality through a higher documentation level • ... a long list ... • for some areas the complete data is available • as the data in the operational system of the company • who bought what when and where? • the electronic traces left by the behavior HandbookLondon 2007 17 kbr

  18. Types of online behavior / traces • Investigating the sources • actual e-mails • e-mail fields: sender, date, subject, response - a network • blogs • the web-sites themselves • all these have ethical as well as legal implications (Allen) • Research into the virtual • Logs of behavior • web-log • paradata • ISP-log HandbookLondon 2007 18 kbr

  19. Web-log analysis • hits, pages, visits, users of a web-site • cookies and explicit user log-in • 'click-stream analysis' CLF • pages where the session stops? • patterns of web-movements that explain the stops • going in circles on a web site? • behavior from non-buyers and buyers HandbookLondon 2007 19 kbr

  20. Paradata in surveys • web-log of the process of answering a web survey • timing of the respondent's progression in shifting the web page • paradata is data about the process of data collection (Couper) • collection at the client-side (Heerwegh) • JavaScript can trace with timing different types of answering mechanisms: drop-down lists, radio-buttons, click-items, give value etc. • and client-side can also track how the respondent has changed the answers HandbookLondon 2007 20 kbr

  21. Analyzing virtual communities • Amazon first among communities of costumers • making customer comments and evaluations available to other customers • many more sites of communities are being added • blogs are kind-of • research in the dating sites • potential in personal links as in Linkedin.com • or the links contained in the web itself • and in the constructed virtual reality of 'Second Life' • or other "games" HandbookLondon 2007 21 kbr

  22. Mixed modes and mixed methods • modes of surveys with questionnaires • postal, with interviewer, face-to-face or telephone, or web-mode • mixed-mode has the ability to reduce non-response • 'sequential mixed-mode ... do not pose any problems' (de Leeuw) • but different modes often produce different results (Dillman) • the 'unimode design' • later a mode-specific design taking full advantage of the mode • 'mixed methods' more the combination of qualitative and quantitative methods - and S-R and non-reactive data HandbookLondon 2007 22 kbr

  23. Conclusion • more data is out there • with high syntactic quality • with high validity by interest from sources • and by data - as traces of actual behavior HandbookLondon 2007 23 kbr

  24. ? • Thanks • Karsten Boye Rasmussen • SDU HandbookLondon 2007 24 kbr

More Related