Skip to main content
SpringerLink
Log in

Framework

  • Chapter
  • First Online:
Applied Data-Centric Social Sciences

  • 924 Accesses

Abstract

A framework of the applied data-centric social sciences is based on data-centric science. A methodology of data-centric science is very common and applicable to all the types of sciences. In this chapter, we will see a methodology used in applied data-centric sciences commonly.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 54.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    IBM Netezza: http://www-01.ibm.com/software/data/netezza/.

  2. 2.

    SAP Data Quality Management software: http://www.sap.com/pc/tech/enterprise-information-management/software/data-quality/index.html.

  3. 3.

    Talend Enterprise Data Quality solution: http://www.talend.com/resource/data-quality.html.

  4. 4.

    http://unstats.un.org/unsd/databases.htm.

  5. 5.

    http://epp.eurostat.ec.europa.eu/portal/page/portal/sdi/indicators.

References

  1. Abbasi, S., Cimato, S., Damiani, E.: Toward secure clustered multi-party computation: a privacy-preserving clustering protocol. In: Mustofa, K., Neuhold, E., Tjoa, A., Weippl, E., You, I. (eds.) Information and Communication Technology. Lecture Notes in Computer Science, vol. 7804, pp. 447–452. Springer, Berlin (2013)

    Google Scholar 

  2. AB-ROAD travel retrieval WebAPI: http://webservice.recruit.co.jp/ab-road/

  3. Barnett, V., Lewis, T.: Outliers in Statistical Data. Wiley, New York (1998)

    Google Scholar 

  4. BBC Timeline: Libor-fixing scandal (6 Feb 2013) http://www.bbc.com/news/business-18671255. Accessed 29 Mar 2014

  5. Ben-Gal, I.: Outlier detection. In: Maimon, O., Rockach, L. (eds.) Data Mining and Knowledge Discovery Handbook: A Complete Guide for Practitioners and Researchers, pp. 131–147. Springer, New York (2005)

    Chapter  Google Scholar 

  6. Chan, P.K., Wei, F., Prodromidis, A.L., Stolfo, S.J.: Distributed data mining in credit card fraud detection. Intel. Syst. Appl. IEEE 14(6), 67–74 (1999)

    Article  Google Scholar 

  7. Chauvenet, W.: A Manual of Spherical and Practical Astronomy V.II, 1st edn. Lippincott, Philadelphia (1863) (Reprint of 1891 5th edn: Dover, NY (1960))

    Google Scholar 

  8. Data Protection Act 1998: http://www.legislation.gov.uk/ukpga/1998/29/contents

  9. Dean, R.B., Dixon, W.J.: Simplified statistics for small numbers of observations. Anal. Chem. 23(4), 636–638 (1951)

    Article  Google Scholar 

  10. Ebookers: http://www.ebookers.com/

  11. Expedia: http://www.expedia.co.jp/

  12. Facebook: https://www.facebook.com/

  13. Google Scholar: http://scholar.google.co.jp/

  14. Google Translate WebAPI: https://developers.google.com/translate/

  15. Grubbs, F.E.: Procedures for detecting outlying observations in samples. Technometrics 11(1), 1–21 (1969)

    Article  Google Scholar 

  16. Haas, S., Wohlgemuth, S., Echizen, I., Sonehara, N., Müller, G.: Aspects of privacy for electronic health records. Int. J. Med. Inform. 80(2), e26–e31 (2011)

    Article  Google Scholar 

  17. Helbling, D., Balietti, S.: From social data mining to forecasting socio-economic crises. Eur. Phys. J. Spec. Top. 195(1), 3–68 (2011)

    Article  Google Scholar 

  18. Jalan vacant room information retrieval WebAPI: http://www.jalan.net/jw/jwp0000/jww0001.do

  19. Jensen, M.: Towards privacy-friendly transparency services in inter-organizational business processes. In: 2013 IEEE 37th Annual Computer Software and Applications Conference Workshop, pp. 200–205 (2013)

    Google Scholar 

  20. Machanavajjhala, A., Kifer, D., Abowd, J., Gehrke, J., Vilhuber, L.: Privacy: theory meets practice on the map. In: 2008 IEEE 24th International Conference on Data Engineering, pp. 277–286 (2008)

    Google Scholar 

  21. Mahalanobis, P.C.: On the generalised distance in statistics. Proc. Natl. Inst. Sci. India 2(1), 49–55 (1936)

    MathSciNet  MATH  Google Scholar 

  22. Mehta, S.R., Vinterbo, S.A., Little, S.J.: Ensuring privacy in the study of pathogen genetics. Lancet Infect. Dis. 14, 70016 (2014)

    Article  Google Scholar 

  23. Peirce, B.: Criterion for the rejection of doubtful observations. Astron. J. 2(43), 161–163 (1852)

    Article  Google Scholar 

  24. Rahm, E., Do, H.H.: Data cleaning: problems and current approaches. IEEE Bull. Tech. Comm. Data Eng. 23(4), 3–13 (2000)

    Google Scholar 

  25. Rakuten Web Service WebAPI: http://webservice.rakuten.co.jp/api/ichibaitemsearch/

  26. ResearchGate: http://www.researchgate.net/

  27. Reuters: Libor scandal may cost banks \({\$}\)14 billion in settlements: analysts (12 July 2012) http://uk.reuters.com/article/2012/07/12/uk-libor-scandal-estimates-idUKBRE86B1EE20120712. Accessed 29 Mar 2014

  28. Soni, S., Mehta, S., Hans, S.: Towards providing data validation as a service. In: 2012 IEEE 9th International Conference on Services Computing, pp. 570–577 (2012)

    Google Scholar 

  29. SurveyMonkey: https://www.surveymonkey.com/

  30. Takeuchi, H., Kodama, N., Hashiguchi, T., Hayashi, D.: Automated healthcare data mining based on a personal dynamic healthcare system. In: Engineering in Medicine and Biology Society, EMBS ’06. 28th Annual International Conference of the IEEE, 30 Aug–3 Sept 2006, pp. 3604–3607 (2006)

    Google Scholar 

  31. The World DataBank of the World Bank: http://data.worldbank.org

  32. Tripadvisor: http://www.tripadvisor.com/

  33. Tsubaki, H.: Valuation of partly disclosed datasets for prediction.In: icdmw, 2013 IEEE 13th International Conference on Data Mining Workshops, pp. 733–734 (2013)

    Google Scholar 

  34. Tukey, J. W.: Exploratory Data Analysis. Addison-Wesley, Reading (1977)

    Google Scholar 

  35. Twitter: https://twitter.com/

  36. Vatsalan, D., Christen, P., Verykios, V.S.: A taxonomy of privacy-preserving record linkage techniques. Inform. Syst. 38(6), 946–969 (2013)

    Article  Google Scholar 

  37. Yahoo! JAPAN text analytics WebAPI: http://developer.yahoo.co.jp/webapi/jp/

Download references

Author information

Authors and Affiliations

  1. Graduate School of Informatics, Kyoto University, Kyoto, Kyoto, Japan

    Aki-Hiro Sato

Authors
  1. Aki-Hiro Sato
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Aki-Hiro Sato .

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Japan

About this chapter

Cite this chapter

Sato, AH. (2014). Framework. In: Applied Data-Centric Social Sciences. Springer, Tokyo. https://doi.org/10.1007/978-4-431-54974-1_2

Download citation

Publish with us

Policies and ethics

Search

Navigation