Methods for Spatial Data Quality of 3D City Models. - Michel Krämer; Jörg Haist; Thorsten Reitz (Eurographics Italian Chapter Conference, 2007)

A processing pipeline for X3D earth-based spatial data view services. - Thorsten Reitz; Michel Krämer; Simon Thum (Web3D, 2009)

DeepCity3D : Integration von 3D-Stadtmo-dellen und Untergrundinformationen. - Michel Krämer; Tobias Ruppert; Eva Kien; Jörn Kohlhammer (Geoinformatik, 2010)

Reducing maintenance complexity of user-centric web portrayal services. - Simon Thum; Michel Krämer (Web3D, 2011)

Domain-Specific Languages For Agile Urban Policy Modelling. - Michel Krämer; David Ludlow; Zaheer Abbas Khan (ECMS, 2013)

Controlling the Processing of Smart City Data in the Cloud with Domain-Specific Languages. - Michel Krämer (UCC, 2014)

Leveraging public participation in urban planning with 3D web technology. - Jens Dambruch; Michel Krämer (Web3D, 2014)

A case study on 3D geospatial applications in the web using state-of-the-art WebGL frameworks. - Michel Krämer; Ralf Gutbell (Web3D, 2015)

A modular software architecture for processing of big geospatial data in the cloud. - Michel Krämer; Ivo Senner (Comput. Graph., 2015)

A microservice architecture for the processing of large geospatial data in the Cloud. - Michel Krämer (2018)

Implementing secure applications in smart city clouds using microservices. - Michel Krämer; Sven Frese; Arjan Kuijper (Future Gener. Comput. Syst., 2019)

Dynamic searchable symmetric encryption for storing geospatial data in the cloud. - Benedikt Hiemenz; Michel Krämer (Int. J. Inf. Sec., 2019)

Scalable processing of massive geodata in the cloud: generating a level-of-detail structure optimized for web visualization. - Michel Krämer; Ralf Gutbell; Hendrik M. Würz; Jannis Weil (AGILE Conf., 2020)

Capability-based Scheduling of Scientific Workflows in the Cloud. - Michel Krämer (DATA, 2020)

Efficient Scheduling of Scientific Workflow Actions in the Cloud Based on Required Capabilities. - Michel Krämer (DATA (Revised Selected Papers), 2020)

A System for Fast and Scalable Point Cloud Indexing Using Task Parallelism. - Pascal Bormann; Michel Krämer (STAG, 2020)

GeoRocket: A scalable and cloud-based data store for big geospatial files. - Michel Krämer (SoftwareX, 2020)

Executing cyclic scientific workflows in the cloud. - Michel Krämer; Hendrik M. Würz; Christian Altenhofen (J. Cloud Comput., 2021)

Comparison of CNN-based segmentation models for forest type classification. - Kevin Kocon; Michel Krämer; Hendrik M. Würz (AGILE Conf., 2022)

Working Efficiently with Large Geodata Files using Ad-hoc Queries. - Pascal Bormann; Michel Krämer; Hendrik M. Würz (DATA, 2022)

A cloud-based data processing and visualization pipeline for the fibre roll-out in Germany. - Michel Krämer; Pascal Bormann; Hendrik M. Würz; Kevin Kocon; Tobias Frechen; Jonas Schmid (J. Syst. Softw., 2024)

Migrating monolithic applications to function as a service. - Hendrik M. Würz; Michel Krämer; Marvin Kaster; Arjan Kuijper (Softw. Pract. Exp., 2024)

Executing Ad-Hoc Queries on Large Geospatial Data Sets Without Acceleration Structures. - Pascal Bormann; Michel Krämer; Hendrik M. Würz; Patrick Göhringer (SN Comput. Sci., 2024)

Real-time indexing and visualization of LiDAR point clouds with arbitrary attributes using the M3NO data structure. - Paul Hermann; Michel Krämer; Tobias Dorra; Arjan Kuijper (Comput. Graph., 2025)