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Linked Data and Visualization: Two Sides of the Transparency Coin

Author:

Auriol DegbeloAuthors Info & Claims

UrbanGIS'17: Proceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics

Article No.: 13, Pages 1 - 8

https://doi.org/10.1145/3152178.3152191

Published: 07 November 2017 Publication History

Abstract

Transparency is an important element of smart cities, and ongoing work is exploring the use of available open data to maximize it. This position paper argues that Linked Data and visualization play similar roles, for different agents, in this context. Linked Data increases transparency for machines, while visualization increases transparency for humans. The work also proposes a quantitative approach to the evaluation of visualization insights which rests on two premises: (i) visualizations could be modelled as a set of statements made by authors at some point in time, and (ii) statements made by experts could be used as ground truth while evaluating how much insights are effectively conveyed by visualizations on the Web. Drawing on the linked data rating scheme of Tim Berners-Lee, the paper proposes a five-stars rating scheme for visualizations on the Web. The ideas suggested are relevant to the development of techniques to automatically assess the transparency level of existing visualizations on the Web.

References

[1]

Natalia Andrienko, Gennady Andrienko, and Peter Gatalsky. 2003. Exploratory spatio-temporal visualization: an analytical review. Journal of Visual Languages & Computing 14, 6 (dec 2003), 503--541.

[2]

Judie Attard, Fabrizio Orlandi, Simon Scerri, and Sören Auer. 2015. A systematic review of open government data initiatives. Government Information Quarterly 32, 4 (2015), 399--418.

[3]

Robert Brauneis and Ellen P. Goodman. 2017. Algorithmic transparency for the smart city. Yale Journal of Law & Technology (2017), Forthcoming.

[4]

Sheelagh Carpendale. 2008. Evaluating information visualizations. In Information Visualization, Andreas Kerren, John T. Stasko, Jean-Daniel Fekete, and Chris North (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 19--45.

Digital Library

[5]

Remco Chang, Caroline Ziemkiewicz, Tera Marie Green, and William Ribarsky. 2009. Defining insight for visual analytics. IEEE Computer Graphics and Applications 29, 2 (mar 2009), 14--17.

[6]

Arzu Coltekin, Susanne Bleisch, Gennady Andrienko, and Jason Dykes. 2017. Persistent challenges in geovisualization -- a community perspective. International Journal of Cartography (apr 2017), 1--25.

[7]

Maria Cucciniello, Nicola Belle, Greta Nasi, and Marco Mena. 2016. Smart cities and transparency. Does smartness influence transparency?. In 49th Hawaii International Conference on System Sciences (HICSS 2016), Tung X. Bui and Ralph H. Sprague Jr. (Eds.). IEEE Computer Society, Koloa, Hawaii, USA, 2944--2952.

Digital Library

[8]

Aba-Sah Dadzie and Emmanuel Pietriga. 2017. Visualisation of Linked Data - Reprise. Semantic Web 8, 1 (2017), 1--21.

[9]

Mathieu D'Aquin, John Davies, and Enrico Motta. 2015. Smart cities' data: challenges and opportunities for semantic technologies. IEEE Internet Computing 19, 6 (nov 2015), 66--70.

[10]

Auriol Degbelo, Devanjan Bhattacharya, Carlos Granell, and Sergi Trilles. 2016. Toolkits for smarter cities: a brief assessment. In UCAmI 2016 - 10th International Conference on Ubiquitous Computing & Ambient Intelligence, R García, P Caballero-Gil, M Burmester, and A Quesada-Arencibia (Eds.). Springer International Publishing, Las Palmas, Gran Canaria, Spain, 431--436.

[11]

Auriol Degbelo, Carlos Granell, Sergio Trilles, Devanjan Bhatacharya, Sven Casteleyn, and Christian Kray. 2016. Opening up smart cities: citizen-centric challenges and opportunities from GIScience. ISPRS International Journal of Geo-Information 5, 2 (2016), 16.

[12]

I J Dowman. 1999. Encoding and validating data from maps and images. In Geographical information systems: principles and technical issues (2nd ed.), P A Longley, D J Maguire, M F Goodchild, and D W Rhind (Eds.). John Wiley and Sons, New York, Chapter 31, 437--450.

[13]

Jason Dykes, Gennady Andrienko, Natalia Andrienko, Volker Paelke, and Jochen Schiewe. 2010. Editorial -- GeoVisualization and the Digital City. Computers, Environment and Urban Systems 34, 6 (nov 2010), 443--451.

[14]

Giuseppe Futia, Alessio Melandri, Antonio Vetrò, Federico Morando, and Juan Carlos De Martin. 2017. Removing barriers to transparency: A case study on the use of semantic technologies to tackle procurement data inconsistency. In The Semantic Web: 14th International Conference, ESWC 2017, Eva Blomqvist, Diana Maynard, Aldo Gangemi, Rinke Hoekstra, Pascal Hitzler, and Olaf Hartig (Eds.). Portoroz, Slovenia, 623--637.

Digital Library

[15]

Alvaro Graves and James Hendler. 2013. Visualization tools for open government data. In Proceedings of the 14th Annual International Conference on Digital Government Research - dg.o '13, Sehl Mellouli, Luis F. Luna-Reyes, and Jing Zhang (Eds.). 136.

Digital Library

[16]

Amy L. Griffin, Anthony C. Robinson, and Robert E. Roth. 2017. Envisioning the future of cartographic research. International Journal of Cartography (may 2017), 1--8.

[17]

David Heald. 2006. Varieties of transparency. In Transparency: The Key to Better Governance?, Christopher Hood and David Heald (Eds.). British Academy, 24--43.

[18]

Pascal Hitzler and Krzysztof Janowicz. 2013. Linked Data, Big Data, and the 4th Paradigm. Semantic Web 4, 3 (2013), 233--235.

Digital Library

[19]

Tobias Isenberg, Petra Isenberg, Jian Chen, Michael Sedlmair, and Torsten Moller. 2013. A systematic review on the practice of evaluating visualization. IEEE Transactions on Visualization and Computer Graphics 19, 12 (dec 2013), 2818--2827.

Digital Library

[20]

M Janssen, Y Charalabidis, and A Zuiderwijk. 2012. Benefits, adoption barriers and myths of open data and open government. Information Systems Management 29, 4 (2012), 258--268.

[21]

Marius Rohde Johannessen and Lasse Berntzen. 2018. The transparent smart city. In Smart Technologies for Smart Governments, Manuel Pedro Rodríguez Bolívar (Ed.). Springer International Publishing, 67--94. Forthcoming.

[22]

John B. Horrigan and Lee Rainie. 2015. Americans' views on open government data. Pew Research Center April (2015). http://www.pewinternet.org/2015/04/21/open-government-data/ (last accessed: October 17, 2017).

[23]

Jeff Johnson. 2010. Designing with the mind in mind. Elsevier.

[24]

Soonhee Kim and Jooho Lee. 2017. Citizen participation and transparency in local government: Do participation channels and policy making phases matter?. In 50th Hawaii International Conference on System Sciences - HICSS 2017. AIS Electronic Library (AISeL), Hilton Waikoloa Village, Hawaii, USA.

[25]

W Kuhn, T Kauppinen, and K Janowicz. 2014. Linked Data - A paradigm shift for Geographic Information Science. In Geographic Information Science - Eighth International Conference, M Duckham, E Pebesma, K Stewart, and A U Frank (Eds.). Springer International Publishing, Vienna, Austria, 173--186.

[26]

Michael Martin, Claus Stadler, Philipp Frischmuth, and Jens Lehmann. 2014. Increasing the financial transparency of European Commission project funding. Semantic Web 5, 2 (2014), 157--164.

Digital Library

[27]

Edgard Marx, Amrapali Zaveri, Mofeed Mohammed, Sandro Rautenberg, Jens Lehmann, Axel-Cyrille Ngonga Ngomo, and Gong Cheng. 2016. DBtrends: Publishing and benchmarking RDF ranking functions. In Proceedings of the 2nd International Workshop on Summarizing and Presenting Entities and Ontologies (SumPre 2016), Andreas Thalhammer, Gong Cheng, and Kalpa Gunaratna (Eds.). CEUR-WS.org, Anissaras, Greece.

[28]

G Michener and K Bersch. 2013. Identifying transparency. Information Polity 18, 3 (2013), 233--242.

Digital Library

[29]

Michael E. Milakovich. 2010. The internet and increased citizen participation in government. eJournal of Democracy (JeDEM) 2, 1 (2010), 1--9.

[30]

Maria Mora-Rodriguez, Ghislain Auguste Atemezing, and Chris Preist. 2017. Adopting semantic technologies for effective corporate transparency. In The Semantic Web: 14th International Conference, ESWC 2017, Eva Blomqvist, Diana Maynard, Aldo Gangemi, Rinke Hoekstra, Pascal Hitzler, and Olaf Hartig (Eds.). Portoroz, Slovenia, 655--670.

Digital Library

[31]

Chris North. 2006. Toward measuring visualization insight. IEEE Computer Graphics and Applications 26, 3 (2006), 6--9.

Digital Library

[32]

Adegboyega Ojo, Zamira Dzhusupova, and Edward Curry. 2016. Exploring the nature of the smart cities research landscape. In Smarter as the New Urban Agenda: A Comprehensive View of the 21st Century City, Ramon J Gil-Garcia, A Theresa Pardo, and Taewoo Nam (Eds.). Springer International Publishing, 23--47.

[33]

Anthony C. Robinson, Urška Demšar, Antoni B. Moore, Aileen Buckley, Bin Jiang, Kenneth Field, Menno-Jan Kraak, Silvana P. Camboim, and Claudia R. Sluter. 2017. Geospatial big data and cartography: research challenges and opportunities for making maps that matter. International Journal of Cartography (mar 2017), 1--29.

[34]

Robert E. Roth, Arzu Çöltekin, Luciene Delazari, Homero Fonseca Filho, Amy Griffin, Andreas Hall, Jari Korpi, Ismini Lokka, André Mendonça, Kristien Ooms, and Corné P.J.M. van Elzakker. 2017. User studies in cartography: opportunities for empirical research on interactive maps and visualizations. International Journal of Cartography (may 2017), 1--29.

[35]

S Scheider, J Jones, A Sanchez, and C Keßler. 2014. Encoding and querying historic map content. In The 17th AGILE International Conference on Geographic Information Science - Connecting a Digital Europe Through Location and Place, J Huerta, S Schade, and C Granell (Eds.). Castelloén, Spain, 251--273.

[36]

Birgit Schmidt, Birgit Gemeinholzer, and Andrew Treloar. 2016. Open data in global environmental research: The belmont forum's open data survey. PLOS ONE 11, 1 (jan 2016), e0146695.

[37]

Edward Segel and Jeffrey Heer. 2010. Narrative visualization: Telling stories with data. IEEE Transactions on Visualization and Computer Graphics 16, 6 (2010), 1139--1148.

Digital Library

[38]

B. Shneiderman. 1996. The eyes have it: a task by data type taxonomy for information visualizations. In Proceedings of the IEEE Symposium on Visual Languages. IEEE Computer Society Press, Boulder, Colorado, USA, 336--343.

Digital Library

[39]

Wang Tao. 2013. Interdisciplinary urban GIS for smart cities: advancements and opportunities. Geo-spatial Information Science 16, 1 (2013), 25--34.

[40]

Jarke J van Wijk. 2005. The value of visualization. In IEEE Visualization 2005. IEEE, Minneapolis, Minnesota, USA, 79--86.

[41]

Jarke J. van Wijk. 2013. Evaluation: A challenge for visual analytics. Computer 46, 7 (2013), 56--60.

Digital Library

[42]

C T Yin, Z Xiong, H Chen, J Wang, D Cooper, and B David. 2015. A literature survey on smart cities. Science China Information Sciences 58, 10 (2015).

Cited By

Degbelo A(2021)FAIR geovisualizations: definitions, challenges, and the road aheadInternational Journal of Geographical Information Science10.1080/13658816.2021.198357936:6(1059-1099)Online publication date: 28-Oct-2021
https://doi.org/10.1080/13658816.2021.1983579
Degbelo ATeka BPurves RJones C(2019)Spatial search strategies for open government dataProceedings of the 13th Workshop on Geographic Information Retrieval10.1145/3371140.3371142(1-10)Online publication date: 28-Nov-2019
https://dl.acm.org/doi/10.1145/3371140.3371142
Degbelo ASarfraz SKray C(2019)Data scale as cartography: a semi-automatic approach for thematic web map creationCartography and Geographic Information Science10.1080/15230406.2019.1677176(1-18)Online publication date: 5-Nov-2019
https://doi.org/10.1080/15230406.2019.1677176
Show More Cited By

Index Terms

Linked Data and Visualization: Two Sides of the Transparency Coin
1. Human-centered computing
  1. Visualization
    1. Visualization design and evaluation methods
2. Information systems
  1. World Wide Web
    1. Web searching and information discovery

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cover image ACM Conferences

UrbanGIS'17: Proceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics

November 2017

118 pages

ISBN:9781450354950

DOI:10.1145/3152178

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Published: 07 November 2017

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SIGSPATIAL'17: 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 7 - 10, 2017

CA, Redondo Beach, USA

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Cited By

Degbelo A(2021)FAIR geovisualizations: definitions, challenges, and the road aheadInternational Journal of Geographical Information Science10.1080/13658816.2021.198357936:6(1059-1099)Online publication date: 28-Oct-2021
https://doi.org/10.1080/13658816.2021.1983579
Degbelo ATeka BPurves RJones C(2019)Spatial search strategies for open government dataProceedings of the 13th Workshop on Geographic Information Retrieval10.1145/3371140.3371142(1-10)Online publication date: 28-Nov-2019
https://dl.acm.org/doi/10.1145/3371140.3371142
Degbelo ASarfraz SKray C(2019)Data scale as cartography: a semi-automatic approach for thematic web map creationCartography and Geographic Information Science10.1080/15230406.2019.1677176(1-18)Online publication date: 5-Nov-2019
https://doi.org/10.1080/15230406.2019.1677176
Degbelo AWissing JKauppinen T(2018)A Comparison of Geovisualizations and Data Tables for Transparency Enablement in the Open Government Data LandscapeInternational Journal of Electronic Government Research10.4018/IJEGR.201810010414:4(39-64)Online publication date: Oct-2018
https://doi.org/10.4018/IJEGR.2018100104
Degbelo AKray CBanaei-Kashani FHoel EGüting RTamassia RXiong L(2018)Intelligent geovisualizations for open government data (vision paper)Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems10.1145/3274895.3274940(77-80)Online publication date: 6-Nov-2018
https://dl.acm.org/doi/10.1145/3274895.3274940

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