Abstract
Big Data is recently used as a keyword to discuss technologies and methods which should enable the processing of big, fast growing, in many cases weak structured amounts of data, which cannot or limited be analysed with traditional approaches. This publication is aiming at the analysis of connections between concepts which are relevant in the context of Big Data and those, playing a role in Green IS in order to systematically utilize findings from the field of Big Data for Environmental Management Information Systems. We explore in a Green IT perspective, if already resource-efficient Big Data applications are discussed and in how far Big Data concepts can be applied for the design of resource-efficient business processes.
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
References
Blei D, Ng A, Jordan M (2003) Latent Dirichlet allocation. J Mach Learn Res 3:993–1022
Dumbill E (2010) The SMAQ stack for big data. http://strata.oreilly.com/2012/01/what-is-big-data.html
Loukides M (2010) What is data science? http://radar.oreilly.com/2010/06/what-is-data-science.html
Manyika J, Chui M, Brown B, Bughin J, Dobbs R, Roxburgh C, Byers AH (2011) Big data: the next frontier for innovation, competition, and productivity., McKinsey Global Institute. http://www.mckinsey.com/Insights/MGI/Research/Technology_and_Innovation/Big_data_The_next_frontier_for_innovation
Madden S (2012) From databases to big data. IEEE Comput 16(3):4–6
Laney D (2001) 3D data management: controlling data volume, velocity, and variety. http://blogs.gartner.com/doug-laney/files/2012/01/ad949-3D-Data-Management-Controlling-Data-Volume-Velocity-and-Variety.pdf
Jacobs A (2009) The pathologies of big data. Commun ACM 52(8):36
Blei DB, Lafferty JD (2009) Topic models. In: Srivastava A, Sahami M (eds) Text mining: classification, clustering, and applications. Chapman and Hall, Boca Raton, pp 71–93
Landauer TK, Dumais ST (1997) A solution to Plato’s problem: the latent semantic analysis theory of acquisition, induction, and representation of knowledge. Psychol Rev 104(2):211–240
Chang J (2012) Collapsed Gibbs sampling methods for topic models. http://cran.r-project.org/web/packages/lda/
Feinerer I (2011) Text mining package. http://cran.r-project.org/web/packages/tm/index.html
Porter M (1980) An algorithm for suffix stripping. Program 14(3):130–137
Kaushik R, Bhandarkar M (2010) GreenHDFS: towards an energy-conserving storage-efficient, hybrid Hadoop compute cluster. In: Proceedings of the 2010 international conference on power aware computing and systems, pp 1–9
Mao Y, Wu W, Zhang H, Luo L (2012) GreenPipe: a Hadoop based workflow system on energy-efficient clouds. In 2012 IEEE 26th international parallel and distributed processing symposium workshops and PhD forum. IEEE, pp 2211–2219
Goiri IN, Le K, Nguyen TD, Guitart J, Torres J, Bianchini R (2012) GreenHadoop: leveraging green energy in data-processing frameworks. In: Proceedings of the 7th ACM European conference on computer systems—EuroSys’12. ACM Press, New York, USA, p 57
Czajkowski G (2008) Sorting 1 PB with MapReduce. http://googleblog.blogspot.de/2008/11/sorting-1pb-with-mapreduce.html
Borthakur D (2008) HDFS architecture guide. http://hadoop.apache.org/docs/r1.0.4/hdfs_design.pdf
Weidema BP, Thrane M, Christensen P, Schmidt J, Lokke S (2008) Carbon footprint: a catalyst for life cycle assessment? J Ind Ecol 12(1):3–6
Funk B, Niemeyer P (2010) Abbildung von Umweltwirkungen in betrieblichen informationssystemen. HMD 274:37–46
Möller A (2000) Grundlagen stoffstrombasierter betrieblicher Umweltinformationssysteme. Projektverlag, Bochum
van der Aalst WMP (2012) Process mining. Commun ACM 55(8):76–83
Frischknecht R (2005) Notions on the design and use of an ideal regional or global LCA database. Int J Life Cycle Assess 11(S1):40–48
Griffiths T, Steyvers M (2004) Finding scientific topics. Proc Natl Acad Sci USA 101:5228–5235
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Hansmann, T., Funk, B., Niemeyer, P. (2014). Green Big Data: A Green IT/Green IS Perspective on Big Data. In: Funk, B., Niemeyer, P., Gómez, J. (eds) Information Technology in Environmental Engineering. Environmental Science and Engineering(). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36011-4_6
Download citation
DOI: https://doi.org/10.1007/978-3-642-36011-4_6
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36010-7
Online ISBN: 978-3-642-36011-4
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)