Abstract
The objective of this paper is to fill in the gap existing between the need of business companies and analysts to spatially correlate open geo-data and social network geo-tagged information, and the lack of tools to enable this task in an easy way. To this end we propose a novel declarative query language named J-CO (JSON Collections) to perform complex queries on heterogeneous collections of data stored within a NoSQL database as JSON objects.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
The work was partially supported by the FHfFC Project jointly funded by CNR and Regione Lombardia D.G.R. n.3866 17/07/2015.
References
Banker K (2011) MongoDB in action. Manning Publications Co
Bordogna G, Pagani M, Psaila G (2006) Database model and algebra for complex and heterogeneous spatial entities. In: Progress in spatial data handling. Springer, pp 79–97
Butler H, Daly M, Doyle A, Gillies S, Hagen S, Schaub T (2016) The geojson format. Technical report
Campagna M, Floris R, Massa P, Girsheva A, Ivanov K (2015) The role of social media geographic information (SMGI) in spatial planning. In: Planning Support systems and smart cities. Springer, pp 41–60
Han J, Haihong E, Le G, Du J (2011) Survey on NoSQL database. In: 2011 6th international conference on pervasive computing and applications (ICPCA). IEEE, pp 363–366
Hansen D, Shneiderman B, Smith MS (2010) Insights from a connected world. Analyzing social media networks with NodeXL. Morgan Kaufmann
Kumar S, Morstatter F, Liu H (2013) Twitter data analytics. Springer
Luo W, MacEachren AM (2014) Geo-social visual analytics. J Spat Inf Sci 2014(8):27–66
Nayak A, Poriya A, Poojary D (2013) Type of NOSQL databases and its comparison with relational databases. Int J Appl Inf Syst 5(4):16–19
Olston C, Reed B, Srivastava U, Kumar R, Tomkins A (2008) Pig latin: a not-so-foreign language for data processing. In: Proceedings of the 2008 ACM SIGMOD international conference on management of data. ACM, pp 1099–1110
Ong KW, Papakonstantinou Y, Vernoux R (2014) The SQL++ semi-structured data model and query language: a capabilities survey of sql-on-hadoop, nosql and newsql databases. CoRR. arXiv:1405.3631
Psaila G (2011) A database model for heterogeneous spatial collections: definition and algebra. In: 2011 international conference on data and knowledge engineering (ICDKE). IEEE, pp 30–35
Wakamiya S, Belouaer L, Brosset D, Lee R, Kawai Y, Sumiya K, Claramunt C (2015) Measuring crowd mood in city space through twitter. In: International symposium on web and wireless geographical information systems. Springer, pp 37–49
White T (2012) Hadoop: the definitive guide. O’Reilly Media, Inc
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Bordogna, G., Capelli, S., Psaila, G. (2017). A Big Geo Data Query Framework to Correlate Open Data with Social Network Geotagged Posts. In: Bregt, A., Sarjakoski, T., van Lammeren, R., Rip, F. (eds) Societal Geo-innovation. AGILE 2017. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-56759-4_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-56759-4_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-56758-7
Online ISBN: 978-3-319-56759-4
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)