Nicolas Tempelmeier
Elena Demidova
ABSTRACT
With the increasing availability of mobility-related data, such as GPS-traces, Web queries and climate conditions, there is a growing demand to utilize this data to better understand and support urban mobility needs. However, data available from the individual actors, such as providers of information, navigation and transportation systems, is mostly restricted to isolated mobility modes, whereas holistic data analytics over integrated data sources is not sufficiently supported. In this paper we present our ongoing research in the context of holistic data analytics to support urban mobility applications in the Data4UrbanMobility (D4UM) project. First, we discuss challenges in urban mobility analytics and present the D4UM platform we are currently developing to facilitate holistic urban data analytics over integrated heterogeneous data sources along with the available data sources. Second, we present the MiC app - a tool we developed to complement available datasets with intermodal mobility data (i.e. data about journeys that involve more than one mode of mobility) using a citizen science approach. Finally, we present selected use cases and discuss our future work.
- L. Anthopoulos and P. Fitsilis. 2010. From Digital to Ubiquitous Cities: Defining a Common Architecture for Urban Development. In Proceedings of the 2010 Sixth International Conference on Intelligent Environments. 301–306. Google Scholar
Digital Library
- Tarique Anwar, Chengfei Liu, Hai L. Vu, and Md. Saiful Islam. 2016. Tracking the Evolution of Congestion in Dynamic Urban Road Networks. In Proceedings of the ACM CIKM 2016. Google ScholarDigital Library
- Michele Berlingerio, Francesco Calabrese, Giusy Di Lorenzo, Rahul Nair, Fabio Pinelli, and Marco Luca Sbodio. 2013. AllAboard: A System for Exploring Urban Mobility and Optimizing Public Transport Using Cellphone Data. In Machine Learning and Knowledge Discovery in Databases, Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, and Filip Železný (Eds.). 663–666. Google ScholarDigital Library
- Stefan Dietze, Elena Demidova, and Konstantin Todorov. 2019. RDF Dataset Profiling. In Encyclopedia of Big Data Technologies.Google Scholar
- Mohamed Ben Ellefi, Zohra Bellahsene, John G. Breslin, Elena Demidova, Stefan Dietze, Julian Szymanski, and Konstantin Todorov. 2018. RDF dataset profiling - a survey of features, methods, vocabularies and applications. Semantic Web 9, 5 (2018), 677–705.Google ScholarDigital Library
- U. Feuerhake, O. Wage, M. Sester, N. Tempelmeier, W. Nejdl, and E. Demidova. 2018. Identification of similarities and prediction of unknown features in an urban street network. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4 (2018), 185–192.Google Scholar
- Gerhard Gossen, Elena Demidova, and Thomas Risse. 2015. iCrawl: Improving the Freshness of Web Collections by Integrating Social Web and Focused Web Crawling. In Proceedings of the JCDL’15. Google ScholarDigital Library
- Gerhard Gossen, Elena Demidova, and Thomas Risse. 2017. Extracting Event-Centric Document Collections from Large-Scale Web Archives. In Proceedings of the 21st International Conference on Theory and Practice of Digital Libraries, TPDL 2017. 116–127.Google ScholarCross Ref
- Gerhard Gossen, Thomas Risse, and Elena Demidova. 2018. Towards extracting event-centric collections from Web archives. International Journal on Digital Libraries (27 Oct 2018).Google Scholar
- Simon Gottschalk and Elena Demidova. 2018. EventKG: A Multilingual Event-Centric Temporal Knowledge Graph. In Proceedings of the 15th International Conference, ESWC 2018. 272–287.Google ScholarCross Ref
- Simon Gottschalk and Elena Demidova. 2019. EventKG - the Hub of Event Knowledge on the Web - and Biographical Timeline Generation. Semantic Web (2019).Google Scholar
- Liang Hong, Yu Zheng, Duncan Yung, Jingbo Shang, and Lei Zou. 2015. Detecting Urban Black Holes Based on Human Mobility Data. In Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems(SIGSPATIAL ’15). ACM, Article 35, 10 pages. Google ScholarDigital Library
- Li Jin, Zhuonan Feng, and Ling Feng. 2016. A Context-aware Collaborative Filtering Approach for Urban Black Holes Detection. In Proceedings of the ACM CIKM 2016. Google ScholarDigital Library
- Kira Kempinska, Paul Longley, and John Shawe-Taylor. 2018. Interactional regions in cities: making sense of flows across networked systems. International Journal of Geographical Information Science 32, 7(2018), 1348–1367.Google ScholarCross Ref
- Simon Kwoczek, Sergio Di Martino, and Wolfgang Nejdl. 2014. Predicting and visualizing traffic congestion in the presence of planned special events. Journal of Visual Languages & Computing 25, 6 (2014), 973 – 980. Google ScholarDigital Library
- Simon Kwoczek, Sergio Di Martino, and Wolfgang Nejdl. 2015. Stuck Around the Stadium? An Approach to Identify Road Segments Affected by Planned Special Events. In IEEE ITSC 2015. Google ScholarDigital Library
- Freddy Lécué, Simone Tallevi-Diotallevi, Jer Hayes, Robert Tucker, Veli Bicer, Marco Luca Sbodio, and Pierpaolo Tommasi. 2014. STAR-CITY: Semantic Traffic Analytics and Reasoning for CITY. In Proceedings of the IUI ’14. Google ScholarDigital Library
- Ming Li, René Westerholt, Hongchao Fan, and Alexander Zipf. 2018. Assessing spatiotemporal predictability of LBSN: a case study of three Foursquare datasets. GeoInformatica 22, 3 (2018), 541–561. Google ScholarDigital Library
- Yuxuan Liang, Zhongyuan Jiang, and Yu Zheng. 2017. Inferring Traffic Cascading Patterns. In Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2017, Redondo Beach, CA, USA, November 7-10, 2017. 2:1–2:10. Google ScholarDigital Library
- Xiaolei Ma, Haiyang Yu, Yunpeng Wang, and Yinhai Wang. 2015. Large-Scale Transportation Network Congestion Evolution Prediction Using Deep Learning Theory. PLOS ONE 10, 3 (03 2015), 1–17.Google Scholar
- Michael McNally. 2008. The four step model. In Handbook of Transport Modeling, David A. Hensher and Kenneth J. Button (Eds.). Emerald, Bingley, 35–53.Google Scholar
- Chuishi Meng, Xiuwen Yi, Lu Su, Jing Gao, and Yu Zheng. 2017. City-wide Traffic Volume Inference with Loop Detector Data and Taxi Trajectories. In Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2017. 1:1–1:10. Google ScholarDigital Library
- Robert Meusel, Petar Petrovski, and Christian Bizer. 2014. The WebDataCommons Microdata, RDFa and Microformat Dataset Series. In Proceedings of the ISWC’14. Google ScholarDigital Library
- Vaia Moustaka, Athena Vakali, and Leonidas G. Anthopoulos. 2018. A Systematic Review for Smart City Data Analytics. ACM Comput. Surv. 51, 5, Article 103 (Dec. 2018), 41 pages. Google ScholarDigital Library
- Ming Ni, Qing He, and Jing Gao. 2017. Forecasting the Subway Passenger Flow Under Event Occurrences With Social Media. IEEE Trans. Intelligent Transportation Systems 18, 6 (2017), 1623–1632.Google ScholarDigital Library
- G. Pan, G. Qi, Z. Wu, D. Zhang, and S. Li. 2013. Land-Use Classification Using Taxi GPS Traces. IEEE Transactions on Intelligent Transportation Systems 14, 1(2013), 113–123. Google ScholarDigital Library
- F. Rodrigues, S. S. Borysov, B. Ribeiro, and F. C. Pereira. 2017. A Bayesian Additive Model for Understanding Public Transport Usage in Special Events. IEEE Transactions on Pattern Analysis and Machine Intelligence 39, 11(2017).Google ScholarDigital Library
- Gao Song, Janowicz Krzysztof, and Couclelis Helen. 2017. Extracting urban functional regions from points of interest and human activities on location-based social networks. Transactions in GIS 21, 3 (2017), 446–467.Google ScholarCross Ref
- R. Soua, A. Koesdwiady, and F. Karray. 2016. Big-data-generated traffic flow prediction using deep learning and dempster-shafer theory. In Proceedings of the 2016 International Joint Conference on Neural Networks (IJCNN). 3195–3202.Google Scholar
- Ying Sun, Hengshu Zhu, Fuzhen Zhuang, Jingjing Gu, and Qing He. 2018. Exploring the Urban Region-of-Interest Through the Analysis of Online Map Search Queries. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining(KDD ’18). 2269–2278. Google ScholarDigital Library
- Nicolas Tempelmeier, Elena Demidova, and Stefan Dietze. 2018. Inferring Missing Categorical Information in Noisy and Sparse Web Markup. In Proceedings of The Web Confonference 2018. Google ScholarDigital Library
- Hongjian Wang and Zhenhui Li. 2017. Region Representation Learning via Mobility Flow. In Proceedings of the 2017 ACM on Conference on Information and Knowledge Management(CIKM ’17). ACM, 237–246. Google ScholarDigital Library
- L. Wang, Y. Zheng, X. Xie, and W. Ma. 2008. A Flexible Spatio-Temporal Indexing Scheme for Large-Scale GPS Track Retrieval. In Proceedings of the Ninth International Conference on Mobile Data Management (mdm 2008). 1–8. Google ScholarDigital Library
- Xiaomeng Wang, Ling Peng, Tianhe Chi, Mengzhu Li, Xiaojing Yao, and Jing Shao. 2016. A Hidden Markov Model for Urban-Scale Traffic Estimation Using Floating Car Data. PLOS ONE 10, 12 (12 2016), 1–20.Google Scholar
- Yilun Wang, Yu Zheng, and Yexiang Xue. 2014. Travel Time Estimation of a Path Using Sparse Trajectories. In Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining(KDD ’14). ACM, 25–34. Google ScholarDigital Library
- Junjun Yin, Aiman Soliman, Dandong Yin, and Shaowen Wang. 2017. Depicting urban boundaries from a mobility network of spatial interactions: a case study of Great Britain with geo-located Twitter data. International Journal of Geographical Information Science 31, 7(2017), 1293–1313. Google ScholarDigital Library
- Bang Zhang, Lelin Zhang, Ting Guo, Yang Wang, and Fang Chen. 2018. Simultaneous Urban Region Function Discovery and Popularity Estimation via an Infinite Urbanization Process Model. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining(KDD ’18). 2692–2700. Google ScholarDigital Library
- Desheng Zhang, Juanjuan Zhao, Fan Zhang, and Tian He. 2015. UrbanCPS: A Cyber-physical System Based on Multi-source Big Infrastructure Data for Heterogeneous Model Integration. In Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical Systems(ICCPS ’15). 238–247. Google ScholarDigital Library
- Xun Zhou, Amin Vahedian Khezerlou, Alex X. Liu, M. Zubair Shafiq, and Fan Zhang. 2016. A traffic flow approach to early detection of gathering events. In Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2016. 4:1–4:10. Google ScholarDigital Library
Index Terms
- Data4UrbanMobility: Towards Holistic Data Analytics for Mobility Applications in Urban Regions
Index terms have been assigned to the content through auto-classification.
Recommendations
The Challenge of Data Analytics with Climate-Neutral Urban Mobility (Vision Paper)
Urban mobility is a major contributor to human-induced climate change, a challenge that urban and transport planning and spatial computing academic communities have been actively addressing. In this paper we argue, however, that the common data analytics ...
Comments