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Composite Visualization Features in PEVNET: A Framework for Visualization of Criminal Networks
Highlighting the Importance of Big Data Management and Analysis for Various Applications pp 37-44 | Cite as
Amer Rasheed (1) Email author ([email protected]) Uffe Kock Wiil (1)
Azween Abdullah (2)
1. The Maersk Mc-Kinney Moeller Institute, University of Southern Denmark, Odense M, Denmark 2. SOCIT, Taylors University, Subang Jaya, Malaysia
Chapter
First Online: 23 August 2017 66 Downloads
Part of the Studies in Big Data book series (SBD, volume 27)
Abstract
Grouping of data is recognized as an effective way of managing a huge amount of data. Groups are very important for exploratory analysis of visualized networks. There are different issues with grouping; for instance data gets meshed up together which makes the interaction between the group members difficult to trace, the analysts find it difficult to analyze the data properly, and thus visualizing data for finding patterns become complex. We have studied different techniques for visualization of criminal data and found that by using different features of composites, the interaction between the different sub-groups can be improved to a large extent. In our proposed framework for visualization of networks, PEVNET, we have made an implementation with which the analysts can drag and drop data for efficient manipulation and have introduced two novel ways of grouping individual and composite data which include grouping the selected nodes and merging group into another group. Finally un-grouping groups is performed. We hope that by including these features, the PEVNET will serve as a handy tool for the analysts, since each and every feature of PEVNET is fulfilling most of the requirements that are needed to conduct a comprehensive analysis.
References
Petersen RR. Criminal network investigation: processes, tools, and techniques. Diss. SDUSDU, Det Tekniske Fakultet Faculty of Engineering, Mærsk Mc-Kinney Møller Instituttet The Maersk Mc-Kinney Moller
Institute; 2012.
Google Scholar (https://scholar.google.com/scholar?
q=Petersen%20RR.%20Criminal%20network%20investigation%3A%20processes%2C%20tools%2C%20and
%20techniques.%20Diss.%20SDUSDU%2C%20Det%20Tekniske%20Fakultet%20Faculty%20of%20Enginee ring%2C%20M%C3%A6rsk%20Mc-Kinney%20M%C3%B8ller%20Instituttet%20The%20Maersk%20Mc- Kinney%20Moller%20Institute%3B%202012.)
Ebel H, Davidsen J, Bornholdt S. Dynamics of social networks. Complexity. 2002;8(2):24–7. Analysis and visualization of criminal networks, 2002
CrossRef (https://doi.org/10.1002/cplx.10066)
Google Scholar (http://scholar.google.com/scholar_lookup?
title=Dynamics%20of%20social%20networks&author=H.%20Ebel&author=J.%20Davidsen&author=S.%20 Bornholdt&journal=Complexity&volume=8&issue=2&pages=24-27&publication_year=2002)
Yi JS, Kang YA, Stasko JT, Jacko JA. Toward a deeper understanding of the role of interaction in information visualization. IEEE Trans Vis Comput Graph. 2007;13(6):1224–31.
CrossRef (https://doi.org/10.1109/TVCG.2007.70515) Google Scholar (http://scholar.google.com/scholar_lookup?
title=Toward%20a%20deeper%20understanding%20of%20the%20role%20of%20interaction%20in%20infor mation%20visualization&author=JS.%20Yi&author=YA.%20Kang&author=JT.%20Stasko&author=JA.%20J acko&journal=IEEE%20Trans%20Vis%20Comput%20Graph&volume=13&issue=6&pages=1224-
1231&publication_year=2007)
Rasheed A, Wiil UK. The 2014 IEEE/ACM international conference on advances in social networks analysis and mining (ASONAM 2014): IEEE Computer Society Press; 2014. p. s876–81.
Google Scholar (https://scholar.google.com/scholar?
q=Rasheed%20A%2C%20Wiil%20UK.%20The%202014%20IEEE%2FACM%20international%20conference
%20on%20advances%20in%20social%20networks%20analysis%20and%20mining%20%28ASONAM%2020 14%29%3A%20IEEE%20Computer%20Society%20Press%3B%202014.%20p.%20s876%E2%80%9381.) Rasheed A, Will UK. Novel analysis and visualization features in PEVNET. Unpublished (2017, submitted for acceptance).
Google Scholar (https://scholar.google.com/scholar?
q=Rasheed%20A%2C%20Will%20UK.%20Novel%20analysis%20and%20visualization%20features%20in%2 0PEVNET.%20Unpublished%20%282017%2C%20submitted%20for%20acceptance%29.)
Wiil UK. Issues for the next generation of criminal network investigation tools. In: European Intelligence and Security Informatics Conference; 2013.
Google Scholar (https://scholar.google.com/scholar?
q=Wiil%20UK.%20Issues%20for%20the%20next%20generation%20of%20criminal%20network%20investig
23/01/2018 Composite Visualization Features in PEVNET: A Framework for Visualization of Criminal Networks | SpringerLink
https://link.springer.com/chapter/10.1007/978-3-319-60255-4_3 2/2
7.
8.
9.
10.
© 2017 Springer International Publishing AG. Part of Springer Nature.
Not logged in 8638.01-05 SpringerProtocols Malaysia Consortium (3000504908) - Taylor's University Library (3000505115) - 9936 SpringerProtocols Malaysia Consortium (3000709475) - SpringerProtocols Malaysia Consortium (3991460342) 180.200.233.250
ation%20tools.%20In%3A%20European%20Intelligence%20and%20Security%20Informatics%20Conferenc e%3B%202013.)
Halasz FG, Moran TP, Trigg RH. NoteCards in a nutshell. In: Proceedings of the ACM CHI+GI ’87. Toronto, Canada; 1987. p. 345–365.
Google Scholar (https://scholar.google.com/scholar?
q=Halasz%20FG%2C%20Moran%20TP%2C%20Trigg%20RH.%20NoteCards%20in%20a%20nutshell.%20I n%3A%20Proceedings%20of%20the%20ACM%20CHI%2BGI%20%E2%80%9987.%20Toronto%2C%20Can ada%3B%201987.%20p.%20345%E2%80%93365.)
Halasz FG. Reflections on NoteCards: seven issues for the next generation of hypermedia systems. Commun ACM. 1988;31(7):836–52.
CrossRef (https://doi.org/10.1145/48511.48514)
Google Scholar (http://scholar.google.com/scholar_lookup?
title=Reflections%20on%20NoteCards%3A%20seven%20issues%20for%20the%20next%20generation%20of
%20hypermedia%20systems&author=FG.%20Halasz&journal=Commun%20ACM&volume=31&issue=7&pag es=836-852&publication_year=1988)
Marshall CC, Halasz FG, Rogers RA, Janssen WC. Aquanet: a hypertext tool to hold your knowledge in place.
In: Proceedings of Hypertext Ô91. New York: ACM; 1991. p. 261–275.
Google Scholar (https://scholar.google.com/scholar?
q=Marshall%20CC%2C%20Halasz%20FG%2C%20Rogers%20RA%2C%20Janssen%20WC.%20Aquanet%3A
%20a%20hypertext%20tool%20to%20hold%20your%20knowledge%20in%20place.%20In%3A%20Proceedi ngs%20of%20Hypertext%20%C3%9491.%20New%20York%3A%20ACM%3B%201991.%20p.%20261%E2%8 0%93275.)
Petersen RR, Wiil UK. Crimefighter investigator: a novel tool for criminal network investigation. In: European intelligence and security informatics conference (EISIC); Sept. 2011. p. 197–202.
Google Scholar (https://scholar.google.com/scholar?
q=Petersen%20RR%2C%20Wiil%20UK.%20Crimefighter%20investigator%3A%20a%20novel%20tool%20fo r%20criminal%20network%20investigation.%20In%3A%20European%20intelligence%20and%20security%
20informatics%20conference%20%28EISIC%29%3B%20Sept.%202011.%20p.%20197%E2%80%93202.)
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Cite this chapter as:
Rasheed A., Wiil U.K., Abdullah A. (2018) Composite Visualization Features in PEVNET: A Framework for Visualization of Criminal Networks. In:
Moshirpour M., Far B., Alhajj R. (eds) Highlighting the Importance of Big Data Management and Analysis for Various Applications. Studies in Big Data, vol 27. Springer, Cham
DOI (Digital Object Identifier) https://doi.org/10.1007/978-3-319-60255-4_3 Publisher Name Springer, Cham
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