This page provides a chronologically ordered list of my work by publication type. For a quick overview, please check my Google Scholar profile. My ORCID is 0000-0001-5361-2885. I also serve as a reviewer for multiple journals, for details see my Publons profile.

Books:

• Cutts, A., & Graser, A. (2018). Learn QGIS – Fourth Edition. Packt Publishing Ltd. ISBN: 9781788997423.
• Graser, A., & Peterson, G. N. (2018). QGIS Map Design – Second Edition. Locate Press. ISBN: 9780998547749.
• Graser, A. (2016). Learning QGIS – Third Edition. Packt Publishing Ltd. ISBN: 9781785880339.
• Graser, A., & Peterson, G. N. (2016). QGIS Map Design. Locate Press. ISBN: 9780989421751.
• Mandel, A., Olaya Ferrero, V., Graser, A., & Bruy, A. (2016). QGIS 2 Cookbook. Packt Publishing Ltd. ISBN: 9781783984961.
• Graser, A. (2014). Learning QGIS – Second Edition. Packt Publishing Ltd. ISBN: 9781784392031.
• Graser, A. (2013). Learning QGIS 2.0. Packt Publishing Ltd. ISBN: 9781782167488.

Book chapters:

• Arribas-Bel, D. & Graser, A. (tba) Geographic Data Science. In: A Research Agenda for Spatial Analysis.
• Graser, A., Dragaschnig, M., & Koller, H. (2021). Exploratory analysis of massive movement data. In: Handbook of Big Geospatial Data, Editors: Werner, Martin, Chiang, Yao-Yi (pp. 285-319). Springer.
• Graser, A. & Dragaschnig, M. (2020). Potentiale entdecken ‒  Explorative räumliche Analyse von Bewegungsdaten. In Geo-IT in Mobilität und Verkehr: Geoinformatik als Grundlage für moderne Verkehrsplanung und Mobilitätsmanagement (pp. 137-154). Wichmann Verlag/VDE. ISBN 978-3-87907-682-6.
• Straub, M., Graser, A., Loidl, M., Zagel, B., & Witzmann-Müller, U. (2020). Effizient geteilt-räumliche Optimierung von Verleihsystemen. In Geo-IT in Mobilität und Verkehr: Geoinformatik als Grundlage für moderne Verkehrsplanung und Mobilitätsmanagement (pp. 175-190). Wichmann Verlag/VDE.

Journal papers (with IF):

• Graser. A., Widhalm, P., & Dragaschnig, M. (2020). The M³ massive movement model: a distributed incrementally updatable solution for big movement data exploration. International Journal of Geographical Information Science, 34(12), 2517-2540. doi:10.1080/13658816.2020.1776293.
• Graser, A., Schmidt, J., Roth, F., & Brändle, N. (2019). Untangling origin-destination flows in geographic information systems. Information Visualization, 18(1), 153-172. doi:10.1177/1473871617738122. (Article first published online: November 30, 2017)
• Fritze, R., Graser, A., & Sinnl, M. (2018). Combining spatial information and optimization for locating emergency medical service stations: A case study for Lower Austria. International Journal of Medical Informatics. doi:10.1016/j.ijmedinf.2017.12.008.
• Brezina, T., Graser, A., & Leth, U. (2017). Geometric methods for estimating representative sidewalk widths applied to Vienna’s streetscape surfaces database. Journal of Geographical Systems, 19(2), 157-174, doi:10.1007/s10109-017-0245-2.
• Loidl, M., Wallentin, G., Cyganski, R., Graser, A., Scholz, J., & Haslauer, E. (2016). GIS and transport modeling—Strengthening the spatial perspective. ISPRS Int. J. Geo-Inf. 2016, 5, 84. doi:10.3390/ijgi5060084.
• Asamer, J., Graser, A., Heilmann, B., & Ruthmair, M. (2016). Sensitivity Analysis for Energy Demand Estimation of Electric Vehicles. Transportation Research Part D: Transport and Environment, Volume 46, Pages 182-199, doi:10.1016/j.trd.2016.03.017. – pre-print
• Graser, A., & Olaya, V. (2015). Processing: A Python Framework for the Seamless Integration of Geoprocessing Tools in QGIS. ISPRS Int. J. Geo-Inf. 2015, 4, 2219-2245. doi:10.3390/ijgi4042219.
• Graser, A., Straub, M., & Dragaschnig, M. (2014). Towards an open source analysis toolbox for street network comparison: indicators, tools and results of a comparison of OSM and the official Austrian reference graph. Transactions in GIS, 18(4), 510-526. doi:10.1111/tgis.12061. – Zenodo version – pre-print

Full papers in peer-reviewed conference proceedings or journals without IF:

• Graser, A. (2022). The State of Trajectory Visualization in Notebook Environments. GI_Forum 2022, 10(2), 73-91. doi:10.1553/giscience2022_02_s73.
• Graser, A. (2021). An exploratory data analysis protocol for identifying problems in continuous movement data. Journal of Location Based Services, 15(2), 89-117. doi:10.1080/17489725.2021.1900612.
• Graser, A., Widhalm, P., & Dragaschnig, M. (2020). Extracting Patterns from Large Movement Datasets. GI_Forum 2020, 8(1), 153-163. doi:10.1553/giscience2020_01_s153. 
• Graser, A. & Dragaschnig, M. (2020). Open Geospatial Tools for Movement Data Exploration. KN ‒ Journal of Cartography and Geographic Information, 70(1), 3-10. doi:10.1007/s42489-020-00039-y.
• Graser, A. (2019). MovingPandas: Efficient Structures for Movement Data in Python. GI_Forum 2019, 7(1), 54-68. doi:10.1553/giscience2019_01_s54.
• Graser, A. (2018). Evaluating Spatio-temporal Data Models for Trajectories in PostGIS Databases. GI_Forum 2018, 1-2018, 16-33. doi:10.1553/giscience2018_01_s16.
• Straub, M., Rudloff, C., Graser, A., Kloimüllner, C., Raidl, G., Pajones, M., & Beyer, F. (2018). Semi-Automated Location Planning for Urban Bike-Sharing Systems. 7th Transport Research Arena TRA 2018, April 16-19, 2018, Vienna, Austria.
• Graser, A. (2017). Tessellating Urban Space Based on Street Intersections and Barriers to Movement. GI_Forum 2017, 5(1), 114-125, doi:10.1553/giscience2017_01_s112.
• Graser, A. (2016). Integrating open spaces into OpenStreetMap routing graphs for realistic crossing behavior in pedestrian navigation. GI_Forum 2016, 1-2016, 217-230, doi:10.1553/giscience2016_01_s217.
• Graser, A., Leodolter, M., Koller, H., & Brändle, N. (2016). Improving vehicle speed estimates using street network centrality. International Journal of Cartography. doi:10.1080/23729333.2016.1189298. – pre-print
• Koller, H., Widhalm, P., Dragaschnig, M., & Graser, A. (2015). Fast Hidden Markov Model Map-Matching for Sparse and Noisy Trajectories. In Intelligent Transportation Systems (ITSC), 2015 IEEE 18th International Conference on (pp. 2557-2561). IEEE.
• Graser, A., & Straub, M. (2015). Improving Navigation: Automated Name Extraction for Separately Mapped Pedestrian and Cycle Links. GI_Forum 2015, 3(1), 546-556, doi:10.1553/giscience2015s546.
• Straub, M., & Graser, A. (2015). Learning from Experts: Inferring Road Popularity from GPS Trajectories. GI_Forum 2015, 3(1), 41-50, doi:10.1553/giscience2015s41.
• Graser, A., Asamer, J., & Ponweiser, W. (2015). The elevation factor: Digital elevation model quality and sampling impacts on electric vehicle energy estimation errors. In Models and Technologies for Intelligent Transportation Systems (MT-ITS), 2015 International Conference on (pp. 81-86). IEEE. doi:10.1109/MTITS.2015.7223240
• Graser, A., Straub, M., & Dragaschnig, M. (2015). Is OSM Good Enough for Vehicle Routing? A Study Comparing Street Networks in Vienna. In Progress in Location-Based Services 2014 (pp. 3-17). Springer International Publishing. doi:10.1007/978-3-319-11879-6_1. – pre-print
• Graser, A., Asamer, J., & Dragaschnig, M. (2014). How to Reduce Range Anxiety? The Impact of Digital Elevation Model Quality on Energy Estimates for Electric Vehicles. GI_Forum 2014, Salzburg, Austria. doi: 10.1553/giscience2014s165. – pre-print with color figures
• Graser, A., Aleksa, M., Straub, M., Saleh, P., Wittmann, S., & Lenz, G. (2014, April). Safety of urban cycling: A study on perceived and actual dangers. In Transport Research Arena (TRA) 5th Conference.
• Graser, A., Straub, M., & Dragaschnig, M. (2013). Ein systematischer Vergleich der Straßennetzwerke von GIP und OpenStreetMap im Großraum Wien. Angewandte Geoinformatik 2013, 424-433. – presentation
• Graser, A., Ponweiser, W., Dragaschnig, M., Brandle, N., & Widhalm, P. (2012, September). Assessing traffic performance using position density of sparse FCD. In Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on (pp. 1001-1005). IEEE.
• Graser, A., Koller, H., Ponweiser, W., Dragaschnig, M., & Pohl, F. (2012). Effiziente Bewertung verkehrlicher Maßnahmen auf Basis von Floating-Car-Daten. Angewandte Geoinformatik 2012. 450-458.
• Graser, A., Dragaschnig, M., & Rudel, B. (2010). Sensorwebs für die Terminallogistik. Angewandte Geoinformatik 2010. 348-353.

Short papers or abstracts in peer-reviewed conference proceedings:

• Graser, A., Heistracher, C., & Pruckovskaja, V. (2022). On the Role of Spatial Data Science for Federated Learning. In: Spatial Data Science Symposium (SDSS2022). https://doi.org/10.25436/E24K5T – 🎬 video
• Ignjatović, D., Liakhovets, D., Simon, R., Neubauer, G., Graser, A., Schütz, M., … & Resch, B. (2022). Combining Social Media and Open Source Data With Relevance Analysis and Expert Knowledge To Improve Situational Awareness in Crisis and Disaster Management–Concept. IDIMT-2022, 153.
• Ochoa-Ortiz, H., Gartner, G., and Graser, A. (2022). Pedestrian routing of periodically changing areas using Volunteered Geographical Information (OpenStreetMap), Abstr. Int. Cartogr. Assoc., 5, 92, https://doi.org/10.5194/ica-abs-5-92-2022.
• Graser, A., Dragaschnig, M., Widhalm, P., Koller, H., & Brändle, N. (2020). Exploratory Trajectory Analysis for Massive Historical AIS Datasets. In: 21st IEEE International Conference on Mobile Data Management (MDM) 2020. doi:10.1109/MDM48529.2020.00059
• Graser, A., Schmidt, J., Dragaschnig, M., Widhalm, P. (2019). Data-driven Trajectory Prediction and Spatial Variability of Prediction Performance in Maritime Location Based Services, LBS 2019, 11-13 November 2019, Vienna, Austria.
• Graser, A., & Widhalm, P. (2018). Modelling Massive AIS Streams with Quad Trees and Gaussian Mixtures. In: Mansourian, A., Pilesjö, P., Harrie, L., & von Lammeren, R. (Eds.), 2018. Geospatial Technologies for All : short papers, posters and poster abstracts of the 21th AGILE Conference on Geographic Information Science. Lund University 12-15 June 2018, Lund, Sweden. ISBN 978-3-319-78208-9. doi:10.31223/osf.io/sz34w.
• Leodolter, M., & Graser, A. (2017). Improving Vehicle Speed Prediction Transferability With Network Centrality, MT-ITS 2017, Napoli, Italy.
• Graser, A. (2017). Towards landmark-based instructions for pedestrian navigation systems using OpenStreetMap. AGILE 2017, Wageningen, Netherlands.
• Graser, A. (2016). Recent Advances and Challenges in the Development of Landmark-based Pedestrian Navigation Systems using OSM. In Proceedings of the 13th International Conference on Location-Based Services, LBS 2016, 14-16 November 2016, Vienna, Austria.
• Asamer, J., Ruthmair, M., Graser, A., & Prandtstetter, M. (2016). Optimizing Checkpoints for Arrival Time Prediction.  In ICCL 2016 Book of Abstracts, S. 86 – 88.
• Graser, A., Leodolter, M., & Koller, H. (2015). Towards Better Urban Travel Time Estimates Using Street Network Centrality. In Proceedings of the 1st ICA European Symposium on Cartography, EuroCarto 2015, 10-12 November 2015, Vienna, Austria. – presentation
• Graser, A., Straub, M., Sellitsch, D., Schwarz, S., Olaverri Monreal, C. (2015). Why Pedestrians are Still Stuck with Navigation Tools Designed for Cars, Walk21, Vienna, Austria.
• Ulm, M., Heilmann, B., Asamer, J., Graser, A., & Ponweiser, W. (2015). Identifying Congestion Patterns in Urban Road Networks Using Floating Car Data. In Transportation Research Board 94th Annual Meeting (No. 15-1231).
• Graser, A., Dragaschnig, M., Ponweiser, W., Koller, H., Marcinek, M. S., & Widhalm, P. (2012). FCD in the Real World–System Capabilities and Applications. In 19th ITS World Congress, Vienna, Austria, 22/26 October 2012.
• Graser, A., Dragaschnig, M., Koller, H., & Piff, M. (2012). Kartenunabhängige Übertragung von Routenempfehlungen mittels offener Standards. Angewandte Geoinformatik 2012. 447-449.
• Graser, A. (2011). Visualisierung raum-zeitlicher Daten in Geoinformationssystemen am Beispiel von Quantum GIS mit „Time Manager“-Plug-In”. Proceedings of FOSSGIS2011, Heidelberg, Germany. ISBN: 978-3-00-034124-3. 73-75.

Preprints:

• Graser, A., Zimányi, E., & Bommakanti, K.C. (2020). From Simple Features to Moving Features and Beyond? arXiv:2006.16900.

Reports:

• Graser, A., Cheng, H., Cheng, T., Giannopoulos, I., Nüst, D., Tomko, M., & Xin, Y. (2022). Urban Mobility Analytics – Group on Methods and Explainability. In: Jonietz, D., Sester, M., Stewart, K., Winter, S, Tomko, M., & Xin, Y. (eds). Urban Mobility Analytics (Dagstuhl Seminar 22162). Dagstuhl Reports, 12(4), 26–53. https://doi.org/10.4230/DagRep.12.4.26
• Mokbel, M., Sakr, M., Xiong, L., Züfle, A., Almeida, J., Anderson, T., Aref, W., Andrienko, G., Andrienko, N., Cao, Y., Chawla, S., Cheng, R., Chrysanthis, P., Fei, X., Ghinita, G., Graser, A., Gunopulos, D., Jensen, C., Kim, J.-S., … Zimányi, E. (2022). Mobility Data Science (Dagstuhl Seminar 22021). Dagstuhl Reports, 12(1), 1–34. https://doi.org/10.4230/DagRep.12.1.1

Conference presentations:

• Graser, A. (2022). The State of Trajectory Visualization in Notebook Environments. GI_Salzburg 2022, Salzburg, Austria.
• Graser, A. (2022). MovingPandas: general purpose visual movement data analytics. GeoPython 2022.
• Graser, A. (2021). Exploratory Movement Data Analysis. GeoPython 2021. – 🎬 video
• Graser, A. (2021). Spatial data exploration in Jupyter notebooks The power of interactive visualization with GeoPandas and HoloViews. FOSDEM 2021. – 🎬 video
• Graser, A. (2019). Big Spatial(!) Data Processing mit GeoMesa. AGIT 2019, Salzburg, Austria. – 🎬 video
• Graser, A. (2019). Neuigkeiten vom QGIS-Projekt. AGIT 2019, Salzburg, Austria. – 🎬 video
• Graser. A. (2019). MovingPandas: efficient trajectory data handling. PyDays Vienna, Austria.
• Graser, A. (2019). QGIS: Das OpenSource Geoinformationssystem. Linuxwochen Wien, Vienna, Austria.
• Graser, A. (2018). Haltung und Analyse großer Mengen räumlicher und zeitlicher Daten mit GeoMesa. AGIT 2018, Salzburg, Austria.
• Graser, A. (2018). Neuigkeiten vom QGIS-Projekt. AGIT 2018, Salzburg, Austria.
• Graser, A. (2017). Neuigkeiten vom QGIS-Projekt. AGIT 2017, Salzburg, Austria.
• Graser, A. (2017). A Python Framework for the Seamless Integration of Geoprocessing Tools in QGIS. PyDays, Vienna, Austria.
• Graser, A. (2016). Neues vom QGIS-Projekt. AGIT 2016, Salzburg, Austria.
• Graser, A. (2016). Developing an Open Pedestrian Landmark Navigation Model. Free and Open Source Software for Geospatial (FOSS4G). Bonn, Germany. – preprint – 🎬 video
• Naumann, S., Graser, A., Straub, M. (2016). Converting OSM data into a routable graph for pedestrians. EURO2016, Poznan, Poland.
• Graser, A. (2015). Kartendesign mit QGIS. AGIT 2015, Salzburg, Austria.
• Graser, A., Straub, M., & Dragaschnig, M. (2013). An Open Source Analysis Toolbox for Street Network Comparison: How OSM Compares to the Official Austrian Reference Graph. FOSS4G2013, Nottingham, UK. – 🎬 video
• Graser, A., & Macho, W. (2011). Neues vom Quantum GIS-Projekt. AGIT 2011, Salzburg, Austria.

Invited talks:

A playlist of recorded talks is available on Youtube.

• Graser, A. (2022-11-17). Shaping Open Spatial Data Science. Keynote at FOSS4G:UK Local 2022.
• Graser, A. (2022-11-16). Mobility Data Science. IAEA Workshop on the improvement of capabilities for Satellite Imagery and Geospatial Information, Vienna, Austria.
• Graser, A. (2022-09-23). Movement data science meets Archeology. Keynote at ARCHEO.FOSS 2022 Panel: Moving in the past.
• Graser, A. (2022-06-14). Intro to MovingPandas. University Piraeus. Department of Computer Science.
• Graser, A. (2022-02-11). University of Edinburgh Earth Observation – AGI Scotland Seminar Series
• Graser, A. (2021-11-24). Open LBS Research: Why (not)? Keynote at LBS2021, Glasgow, UK. – 🎬 video
• Graser, A. (2021-11-18). Bewegungsdaten besser verstehen & nutzen. Women in Mobility Winter School.
• Graser, A. (2021-10-25). Understanding Tracking Data (with MovingPandas). SDSC2021 Spatial Data Science Conference. – 🎬 video
• Graser, A. (2021-10-01). Open source for open spatial data science. Keynote at FOSS4G 2021, Buenos Aires, Argentina. – 🎬 video
• Graser, A. (2021-09-16). Understanding Movement Data. SystemX Seminar Series. – 🎬 video
• Graser, A. (2021-07-09). Urban Data Science – More than a buzzword? Keynote at GI_Forum 2021, Salzburg, Austria. – 🎬 video
• Graser, A. (2021-06-15). Exploratory Spatial Data Analysis. BEGIN Webinar. Bell Edwards Geographic Data Institute. Univ. of St. Andrews, UK.
• Graser, A. (2021-05-25). Geospatial Data Analysis. Keynote at Canadian Cartographic Association (CCA) Conference.
• Graser, A. (2021-05-18). Spatial Data Science Using QGIS. UN Open GIS QGIS Workshop.
• Graser, A. (2021-03-18). Movement Data in GIS. Lightning Talk at Geobeer Switzerland.
• Graser, A. (2021-03-10). Exploratory Analysis of Massive Movement Data. RGS-IBG GIScience Research Group Seminar, UK. – 🎬 video
• Graser, A. (2020-10-22). Exploring Movement Data. Geographic Data Science Lab Brown Bag Seminar. Univ. of Liverpool, UK. – 🎬 video
• Graser, A. (2020-10-21). Bewegungsdatenanalyse. HEiKA Urban Data Science Workshop. Univ. Heidelberg & Karlsruher Institut für Technologie, Germany.
• Graser, A. (2020-09-22). MovingPandas – open source movement data exploration library. CIHT Webinar.
• Graser, A., Zimányi, E., & Bommakanti, K.C. (2020-09-15). From Simple Features to Moving Features and Beyond? OGC Member Meeting Sept 2020, Moving Features SWG.
• Graser, A. (2019). Python for Movement Data Analysis. Vienna Data Science Group Meetup, Vienna, Austria.
• Graser, A. (2019). Towards an exploratory analysis of time in massive movement data. DASTU, Politecnico di Milano, Italy.
• Graser, A. (2019). Exploring movement data with open geospatial tools. Politecnico di Milano, Italy. – 🎬 video
• Graser, A. (2019). Exploring movement data with open geospatial tools. Urban Mobility Symposium, Citylab Berlin, Germany.
• Graser, A. (2019). Geospatial Data Analysis – Quo Vadis? CODE Conference, University of the Bundeswehr Munich, Germany.
• Graser, A. (2019). Geomarketing: offen & dynamisch. WIGeoGIS Knowledge Day, Wien, Austria.
• Graser, A. (2019). Einblicke vom Bazaar des QGIS-Projekts. Keynote at FOSSGIS 2019, Dresden, Germany. – 🎬 video
• Graser, A. (2019). Managing massive amounts of spatio-temporal data using GeoMesa, Bern, Switzerland.
• Graser, A. (2018). QGIS: open and dynamic. Keynote at QGIS User Group Meeting Mexico. (remote)
• Graser, A. (2018). Advanced Visualization in QGIS3. Workshop at Netzwerktreffen des DFG-Forschungsnetzwerks “Digitale Geographien”, TU Wien, Vienna, Austria.
• Graser, A. (2018). QGIS: open and dynamic. Keynote at FOSS4G Korea, Seoul, South Korea.
• Graser, A. (2018). Managing massive amounts of spatio-temporal data using GeoMesa. Vienna Data Science Group, Knowledgefeed, Vienna, Austria. – 🎬 video
• Graser, A. (2018). Neuigkeiten von QGIS3. 31. Open Government Plattform Wien, Vienna, Austria.
• Graser, A. (2018). GIScience for Dynamic Transportation Systems. GI-Forum, University of Muenster, Germany.
• Graser, A. (2018). Exploring Open Source: QGIS and its analysis tools. New York GIS Association webinar.
• Graser, A. (2018). Mobilitätsdatenanalyse mit OpenSource-GIS. Vienna Geo Meetup, Vienna, Austria.
• Graser, A. (2017). GIScience for Dynamic Transportation Systems. GIScience Colloquium, University of Zurich, Switzerland.
• Graser, A. (2017). QGIS – open & dynamic. Keynote at FOSS4G-FI, Helsinki, Finland.
• Graser, A. (2017). Einblicke vom Bazaar eines Open Source Projekts: Das Beispiel QGIS, 13. Netzpolitischer Abend AT, Wien, Austria. – 🎬 video
• Graser, A. (2016). QGIS – Community-powered GIS. Keynote at FOSS4G-NOR, Oslo, Norway. – 🎬 video
• Graser, A. (2016). Offen und dynamisch – OpenSource, OpenData & OpenScience, Keynote at AGIT2016, Salzburg, Austria. 
• Graser, A. (2016). QGIS for Cartography. CartoTalk, TU Wien, Austria.
• Graser, A. (2015). Die Time-Manager-Erweiterung. Anwendertreffen der QGIS Anwendergruppe Deutschland, Kassel, Germany.
• Graser, A. (2015). Freie und offene GIS-Software. OVG Vortragsreihe WS2015/16, TU Wien, Austria.
• Graser, A., & Straub, M. (2015). Routing mit OSM. OpenStreetMap Spezialforum AGIT 2015, Salzburg, Austria.
• Graser, A. (2015). Die dritte und vierte Dimension in QGIS. KAGIS-Fachtag 2015, Klagenfurt, Austria.
• Graser, A., & Alexiou, K. (2015). Visual exploration and presentation of spatial data using QGIS – Time Manager Workshop. QGIS Conference 2015, Nodebo, Denmark.
• Graser, A. (2014). GIScience for Dynamic Transportation Systems. Laboratory for Geocomputation, Ryerson University, Toronto, Canada.
• Graser, A. (2013). GIS in der Mobilitätsforschung. GIS-Day 2013, Linz, Austria.
• Graser, A. (2011). Time Manager Plugin. 2nd German-speaking QGIS user conference, Rapperswil, Switzerland. 
• Graser, A. (2011). Routing mit QGIS + pgRouting. 2nd German-speaking QGIS user conference, Rapperswil, Switzerland. 

Workshop presentations:

• Graser, A., Jalali, A., Lampert, J., Weißenfeld, A., & Janowicz, K. (accepted). Deep Learning From Trajectory Data: a Review of Neural Networks and the Trajectory Data Representations to Train Them. Workshop on Big Mobility Data Analysis BMDA2023 in conjunction with EDBT/ICDT 2023.
• Graser, A. (2021). Notebook-based Visual Analysis of Large Tracking Datasets. Workshop on Big Mobility Data Analysis BMDA2021 in conjunction with EDBT/ICDT 2021. – 🎬 video
• Graser, A., & Dragaschnig. M. (2020). Exploring movement data in notebook environments. Workshop on Information Visualization of Geospatial Networks, Flows and Movement (MoVis) in conjunction with IEEE VIS 2020. – 🎬 video
• Graser, A., Schmidt, J., & Widhalm, P. (2018). Predicting trajectories with probabilistic time geography and massive unconstrained movement data. Workshop on Analysis of Movement Data AMD2018 in conjunction with GIScience 2018, Melbourne, Australia.
• Graser, A., Straub, M., & Dragaschnig, M. (2013). A comparative study of OpenStreetMap and the official Austrian reference graph for vehicle routing. ICA Workshop on Street Networks and Transport in conjunction with the 26th International Cartographic Conference, Dresden, Germany.
• Graser, A., & Rudloff, Ch. (2012). On the portability of map-independent mode detection algorithms. Urbanism on Track Workshop 2012, Delft, The Netherlands.

Poster presentations:

• Graser, A., Twaroch, F., & Widhalm, P. (2019). Monitoring the impacts of urban construction works on city traffic. GI_Forum 2019, Salzburg, Austria.
• Graser, A. (2012). Where are we going? Spatial and Mobility Aspects of Twitter Streams. Summer School on Social Media Modeling and Search .

Articles in non-refereed media:

• Graser, A. (2021). Bewegungsdaten in GIS – eine Bestandsaufnahme. UNIGIS offline. Newsletter für UNIGIS Studierende und Alumni. 86. 6-7. (invited article)
• Graser, A., Ponweiser, W., & Dragaschnig, M. (2013). Generierung detaillierter Geschwindigkeitsprofile aus grob aufgelösten Floating-Car-Daten. Österreichische Zeitschrift für Verkehrswissenschaft – ÖZV 1-2/2013.
• Graser, A. (2012). Introducing the Quantum GIS Ecosystem. GIS Lounge (invited article).
• Graser, A. (2011). Mit offenen Daten auf Wohnungssuche. Futurezone.at – Open Data Blog. (invited article)

Theses:

• Graser, A. (2021). Exploratory Analysis of Massive Movement Data. PhD thesis at the University of Salzburg, Austria.
• Graser, A. (2010). OGC-Sensorweb-Services für Fragestellungen in Straße-Schiene-Terminals. Master’s thesis at the University of Applied Sciences, Wiener Neustadt, Austria.
• Graser, A. (2008). Analyse von Map-Matching- und Routing-Algorithmen mithilfe eines GIS. 2nd Bachelor’s thesis at the University of Applied Sciences, Wiener Neustadt, Austria.
• Graser, A. (2007). Analyse und Darstellung von Mautdaten mithilfe einer Webapplikation. 1st Bachelor’s thesis at the University of Applied Sciences, Wiener Neustadt, Austria.

Co-supervised theses:

• Ochoa Ortiz, H. (2022) Pedestrian routing of dynamic areas using Volunteered Geographical Information (OpenStreetMap). MSc thesis, TU Wien, Dept. for Geodesy and Geoinformation.
• Enenkel, G. (2020). On the volatility of construction site entailed traffic deflections – A floating car data example from Vienna. MSc thesis, Faculty of Civil Engineering, Technical University of Vienna.
• Waldburger, T. (2020). Large-scale analysis of taxi drivers’ route choice behaviour in San Francisco, Shanghai, and Vienna. MSc thesis, Department of Geography, University of Zurich.
• Westermeier, E.M. (2018). Contextual Trajectory Modeling and Analysis. MSc thesis, Interfaculty Department of Geoinformatics, University of Salzburg.
• Schumacher, D. (2018). Do Taxi Drivers Take the Shortes Routes? A Large-Scale Analysis Using GPS-based Floating Car Data in Vienna. MSc thesis, Department of Geography, University of Zurich.

Videos: https://www.youtube.com/anitagraser

Program committee memberships at scientific conferences:

• AGILE 2021
• COSIT 2022
• FOSS4G 2022
• FOSS4G-EU 2015
• LBS 2020, 2023
• MBDW 2020
• MoVIS 2020
• SIGSPATIAL 2022