Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
SpringerLink
Log in

Contextual Preferences to Personalise Semantic Data Lake Exploration

  • Conference paper
  • First Online:
Database and Expert Systems Applications (DEXA 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12392))

Included in the following conference series:

  • 837 Accesses

Abstract

In the latest years, the availability of data collected within Smart Cities is enabling citizens to take decisions about their daily life in an autonomous way. In this landscape, data aggregation according to different analysis dimensions may help users to take decisions, leveraging indicators as powerful tools for meaningful exploration. However, due to the volume and heterogeneity of Smart City data, data lakes have to be used as flexible repositories for enabling data storage and organisation. Despite they are usually based on centralisation of data storage, data lakes compel to consider pay-as-you-go or on-demand solutions, where integration is progressively carried out, to cope with the cumbersome nature of Big Data. Given the variety of interested users, their goals and preferences on available data, personalised data access, as well as representation and use of preferences, are required and need to be adapted to the unique characteristics of data lakes. In this paper, we describe an approach to model preferences on Smart City indicators built on top of a data lake. Preferences are used for personalised data exploration. Main contributions of this paper concern: (a) the definition of users’ preferences and preference constructors over the semantic representation of indicators; (b) the definition of users’ contexts and contextual preferences; (c) preference-based personalised exploration of Smart City data.

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

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    http://tomee.apache.org/.

References

  1. Bagozi, A., Bianchini, D., De Antonellis, V., Garda, M., Melchiori, M.: Personalised exploration graphs on semantic data lakes. In: 27th International Conference on Cooperative Information Systems (CoopIS 2019), Rhodes, Greece, pp. 22–39 (2019)

    Google Scholar 

  2. Chauhan, S., Agarwal, N., Kar, A.: Addressing big data challenges in smart cities: a systematic literature review. Info 18(4), 73–90 (2016)

    Article  Google Scholar 

  3. Chomicki, J.: Preference formulas in relational queries. ACM Trans. Database Syst. (TODS) 28(4), 427–466 (2003)

    Article  MathSciNet  Google Scholar 

  4. Ciaccia, P., Martinenghi, D., Torlone, R.: Foundations of context-aware preference propagation. J. ACM (JACM) 67(1), 1–43 (2020)

    Article  MathSciNet  Google Scholar 

  5. de Amo, S., Ribeiro, M.R.: CPref-SQL: a query language supporting conditional preferences. In: 24th Annual ACM Symposium on Applied Computing (SAC 2009), Honolulu, Hawaii, USA, pp. 1573–1577 (2009)

    Google Scholar 

  6. Golfarelli, M., Rizzi, S., Biondi, P.: myOLAP: an approach to express and evaluate OLAP preferences. IEEE Trans. Knowl. Data Eng. 23(7), 1050–1064 (2010)

    Article  Google Scholar 

  7. Kießling, W.: Foundations of preferences in database systems. In: 28th International Conference on Very Large Databases (VLDB 2002), Hong Kong, China, pp. 311–322 (2002)

    Google Scholar 

  8. Nargesian, F., Zhu, E., Miller, R.J., Pu, K.Q., Arocena, P.C.: Data lake management: challenges and opportunities. Proc. VLDB Endow. 12(12), 1986–1989 (2019)

    Article  Google Scholar 

  9. Polo, L., Mínguez, I., Berrueta, D., Ruiz, C., Gómez, J.M.: User preferences in the web of data. Semant. Web 5(1), 67–75 (2014)

    Article  Google Scholar 

  10. Troumpoukis, A., Konstantopoulos, S., Charalambidis, A.: An extension of SPARQL for expressing qualitative preferences. In: d’Amato, C., et al. (eds.) ISWC 2017. LNCS, vol. 10587, pp. 711–727. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-68288-4_42

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Information Engineering, University of Brescia, Via Branze 38, 25123, Brescia, Italy

    Devis Bianchini, Valeria De Antonellis, Massimiliano Garda & Michele Melchiori

Authors
  1. Devis Bianchini
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Valeria De Antonellis
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Massimiliano Garda
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Michele Melchiori
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Devis Bianchini .

Editor information

Editors and Affiliations

  1. Clausthal University of Technology, Clausthal-Zellerfeld, Germany

    Sven Hartmann

  2. Johannes Kepler University of Linz, Linz, Austria

    Josef Küng

  3. Johannes Kepler University of Linz, Linz, Austria

    Gabriele Kotsis

  4. IFS, Vienna University of Technology, Vienna, Wien, Austria

    A Min Tjoa

  5. Johannes Kepler University of Linz, Linz, Austria

    Ismail Khalil

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bianchini, D., De Antonellis, V., Garda, M., Melchiori, M. (2020). Contextual Preferences to Personalise Semantic Data Lake Exploration. In: Hartmann, S., Küng, J., Kotsis, G., Tjoa, A.M., Khalil, I. (eds) Database and Expert Systems Applications. DEXA 2020. Lecture Notes in Computer Science(), vol 12392. Springer, Cham. https://doi.org/10.1007/978-3-030-59051-2_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-59051-2_22

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-59050-5

  • Online ISBN: 978-3-030-59051-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation