Hasso-Plattner-Institut
Prof. Dr. h.c. mult. Hasso Plattner
 

Keven Richly

Research Assistant, PhD Candidate

 Phone:+49 (331) 5509 - 1328
 Fax:+49 (331) 5509 - 579
 E-Mail:keven.richly(at)hpi.de
 Address:August-Bebel-Str. 88 Potsdam, Brandenburg, 14482 Germany
 Room:Hasso-Plattner-Villa, V 2.01
  DBLP  ORCID  Google Scholar  ResearchGate  LinkedIn

Research Topics

Research Abstract: Optimized Spatio-Temporal Data Structures for Hybrid Transactional and Analytical Workloads on Columnar In-Memory Databases

Rapid advances in location-acquisition technologies have led to large amounts of trajectory data. These data are the foundation for a broad spectrum of services driven and improved by trajectory data mining (e.g., ride-sharing, soccer analytics). However, for hybrid transactional and analytical workloads, the storing and processing of rapidly accumulated trajectory data is a non-trivial task. Due to high data volumes and data velocity, performance and memory consumption issues have to be addressed. 
 
Based on the required performance of various applications to analyze trajectory data, we develop approaches to optimize columnar relational in-memory database systems to store and process spatio-temporal data. The relational database structure is well suited to store trajectory data in the common sample point format, enables the efficient combination with other data sources (e.g., business data), and allows us to leverage recent developments in query processing and compression techniques for columnar database systems.  
 
In our research, we focus on optimized data structures and selection mechanisms for workload-aware compression schemas to minimize the data footprint of trajectory data. To address the over time changing access patterns, we introduce a framework that divides the spatio-temporal data into partitions of fixed size and applies specific compression techniques based on the data characteristics and the access patterns for each partition.  Additionally, we analyze various real-world use cases to evaluate the proposed optimizations. 

Publications

  • 1.
    Richly, K., Schlosser, R., Boissier, M.: Budget-Conscious Fine-Grained Configuration Optimization for Spatio-Temporal Applications. Proceedings of the VLDB Endowment. pp. 4079–4092 (2022).
     
  • 2.
    Richly, K., Schlosser, R., Brauer, J.: Enabling Risk-averse Dispatch Processes for Transportation Network Companies by Probabilistic Location Prediction. Communications in Computer and Information Science, Springer. 1623, 21–42 (2022).
     
  • 3.
    Richly, K., Schlosser, R., Boissier, M.: Joint Index, Sorting, and Compression Optimization for Memory-Efficient Spatio-Temporal Data Management. 37th IEEE International Conference on Data Engineering, ICDE 2021, Chania, Greece, April 19-22, 2021. pp. 1901–1906 (2021).
     
  • 4.
    Richly, K., Schlosser, R., Brauer, J., Plattner, H.: A Probabilistic Location Prediction Approach to Optimize Dispatch Processes in the Ride-Hailing Industry. HICSS 2021. pp. 1830–1840 (2021).
     
  • 5.
    Richly, K., Brauer, J., Schlosser, R.: Predicting Location Probabilities of Drivers to Improve Dispatch Decisions of Transportation Network Companies Based on Trajectory Data. 9th International Conference on Operations Research and Enterprise Systems, ICORES 2020. pp. 47–58 (2020).
     
  • 6.
    Richly, K.: Optimized Spatio-Temporal Data Structures for Hybrid Transactional and Analytical Workloads on Columnar In-Memory Databases. Proceedings of the VLDB 2019 PhD Workshop, co-located with the 45th International Conference on Very Large Databases (VLDB 2019). (2019).
     
  • 7.
    Schlosser, R., Richly, K.: Dynamic Pricing under Competition with Data-Driven Price Anticipations and Endogenous Reference Price Effects. Journal of Revenue & Pricing Management. 18, 451–464 (2019).
     
  • 8.
    Schlosser, R., Richly, K.: Dynamic Pricing Competition with Unobservable Inventory Levels: A Hidden Markov Model Approach. Communications in Computer and Information Science. pp. 15–36. Springer (2019).
     
  • 9.
    Richly, K.: A survey on trajectory data management for hybrid transactional and analytical workloads. 2018 IEEE International Conference on Big Data (Big Data). pp. 562–569. IEEE (2018).
     
  • 10.
    Richly, K.: Leveraging Spatio-Temporal Soccer Data to Define a Graphical Query Language for Game Recordings. 2018 IEEE International Conference on Big Data (Big Data). pp. 3456–3463. IEEE (2018).
     
  • 11.
    Schlosser, R., Richly, K.: Dynamic Pricing Strategies in a Finite Horizon Duopoly with Partial Information. 7th International Conference on Operations Research and Enterprise Systems, ICORES 2018. pp. 21–30 (2018).
     
  • 12.
    Richly, K., Moritz, F., Schwarz, C.: Utilizing Artificial Neural Networks to Detect Compound Events in Spatio-Temporal Soccer Data. SIGKDD’17 Workshop on Mining and Learning from Time Series (MiLeTS) (2017).
     
  • 13.
    Richly, K., Lorenz, M., Oergel, S.: S4J - Integrating SQL into Java at Compiler-Level. To appear in Information and Software Technologies - 22st International Conference, ICIST 2016, Proceedings (Springer - Communications in Computer and Information Science) (2016).
     
  • 14.
    Richly, K., Teusner, R.: Where is the Money Made? An Interactive Visualization of Profitable Areas in New York City. The 2nd EAI International Conference on IoT in Urban Space (Urb-IoT) (2016).
     
  • 15.
    Kowark, T., Richly, K., Uflacker, M., Plattner, H.: Incremental, Per-Query Ontology Matching with RepMine. 25th International World Wide Web Conference (WWW), Demo Track, Montreal, Canada (2016).
     
  • 16.
    Matthies, C., Kowark, T., Richly, K., Uflacker, M., Plattner, H.: How Surveys, Tutors, and Software Help to Assess Scrum Adoption in a Classroom Software Engineering Project. Proceedings of the 38th International Conference on Software Engineering Companion. pp. 313–322. ACM, New York, NY, USA (2016).
     
  • 17.
    Richly, K., Bothe, M., Rohloff, T., Schwarz, C.: Recognizing Compound Events in Spatio-Temporal Football Data. International Conference on Internet of Things and Big Data (IoTBD) (2016).
     
  • 18.
    Matthies, C., Kowark, T., Richly, K., Uflacker, M., Plattner, H.: ScrumLint: Identifying Violations of Agile Practices Using Development Artifacts. Proceedings of the 9th International Workshop on Cooperative and Human Aspects of Software Engineering. pp. 40–43. ACM, New York, NY, USA (2016).
     
  • 19.
    Richly, K., Teusner, R., Immer, A., Windheuser, F., Wolf, L.: Optimizing Routes of Public Transportation Systems by Analyzing the Data of Taxi Rides. Workshop on Smart Cities and Urban Analytics, in conjunction with 23rd ACM International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL) (2015).
     
  • 20.
    Kowark, T., Teusner, R., Richly, K., Plattner, H.: RepMine: A System for Transferrable Analyses of Collaboration Activities in Software Engineering. 2015 Workshop on Software Support for Collaborative and Global Software Engineering, In conjunction with the 30th IEEE/ACM International Conference on Automated Software Engineering (2015).
     
  • 21.
    Teusner, R., Richly, K., Staubitz, T., Renz, J.: Enhancing Content between Iterations of a MOOC – Effects on Key Metrics. EMOOCs 2015: European MOOCs Stakeholder Summit. pp. 147–156 (2015).
     
  • 22.
    Richly, K., Bross, J., Kohnen, M., Meinel, C.: Identifying the top-dogs of the blogosphere. Social Network Analysis and Mining. (2012).
     
  • 23.
    Bross, J., Richly, K., Schilf, P., Meinel, C.: Social Physics of the Blogosphere: Capturing, Analyzing and Presenting Interdependencies of Partial Blogospheres. From Sociology to Computing in Social Networks (2010).
     

Reviewing

  • The International Journal on Very Large Data Bases (VLDBJ 2021)
  • The 22nd International Conference on Information and Software Technologies (ICIST 2016)
  • The Hawaii International Conference on System Sciences (HICSS 2020, 2021)

Teaching Activities

TermTypeTitle

Winter '20

Lecture

Global Team-based Innovation I

Winter '20

Seminar

Global Team-based Innovation - Coaching Research

Winter '19

Lecture

Global Team-based Innovation I

Winter '19

Seminar

Global Team-based Innovation - Coaching Research

Winter '19Lecture

Softwaretechnik II - Agile Software Development in Large Teams

Summer '19LectureGlobal Team-based Innovation II

Winter '18

Lecture

Global Team-based Innovation I

Winter '18

Seminar

Global Team-based Innovation - Coaching Research

Winter '18Lecture

Softwaretechnik II - Agile Software Development in Large Teams

Summer '18LectureGlobal Team-based Innovation II
Summer '18Seminar

Trends and Concepts in the Software Industry III - Exercise: In-Memory Geospatial Analysis

Winter '17Lecture

Trends and Concepts in the Software Industry II - Spatiotemporal Analysis of Healthcare Data

Winter '17LectureGlobal Team-based Innovation I
Winter '17Seminar Global Team-based Innovation - Coaching Research
Winter '17LectureSoftwaretechnik II - Agile Software Development in Large Teams
Summer '17LectureTrends and Concepts in Software Industry I
Summer '17Lecture

Global Team-based Innovation II

Winter '16LectureSoftwaretechnik II - Agile Software Development in Large Teams
Winter '16LectureGlobal Team-based Innovation I
Winter '16SeminarGlobal Team-based Innovation - Coaching Research
Winter '16LectureTrends and Concepts II - Cloud-based Apps for Digital Healthcare
Summer '16LectureTrends and Concepts in the Software Industry I: Next-Generation Enterprise Applications
Summer '16Lecture

Global Team-Based Product Innovation & Engineering II (ME 310)

Winter '15Lecture

Softwaretechnik II - Agile Software Development in Large Teams

Winter '15Online Lecture"In-Memory Data Management" on openHPI
Winter '15Lecture

Global Team-Based Product Innovation & Engineering I (ME 310)

Winter '15Seminar

ME310: Global Team-based Product Innovation & Engineering - Coaching Seminar

Winter '15Lecture

Trends and Concepts in the Software Industry II

Winter '15Seminar

In-Memory Data Management Research

Summer '15Lecture

Trends and Concepts in the Software Industry I - In-Memory Applications

Summer '15SeminarEnterprise Applications 
Summer '15Seminar

Parallel Programming and Algorithms for In-Memory Databases

Winter '14

LectureSoftwaretechnik II
Winter '14Online Lecture"In-Memory Data Management" on openHPI
Winter '14Lecture

Trends and Concepts II - Exploiting Point-of-Sales Data

Summer '14Lecture

Trends and Concepts in the Software Industry I - Principles of In-Memory Databases

Summer '14Bachelor Project

Modern Computer-aided Software Engineering

Summer '14Master Project

Code better, run faster

Winter '13LectureSoftwaretechnik II
Winter '13Lecture

Trends and Concepts in the Software Industry II - Next Generation Clinical Information Systems

Winter '13Seminar

In-Memory Data Management Research

Winter '13Bachelor Project

Modern Computer-aided Software Engineering

Winter '13Online Lecture"In-Memory Data Management" on openHPI
Summer '13Lecture

Trends and Concepts in the Software Industry I: Inner Mechanics of In-Memory Databases