Current research projects
Acronym: ODDA
Project leader:
Prof. Dr. Richard Lenz
Professorship for Evolutionary Data Management
Ontologies are powerful tools for structuring and formalizing knowledge and enabling interoperability. They play a crucial role in research data management by making data machine-interpretable and facilitating the integration of diverse datasets from various researchers. Ideally, the integrated datasets contribute to global use cases aimed at inferring new knowledge.To achieve this, it is essential that researchers align the data collected for their local use cases with existing domain or applic…
Acronym: SKYSHARK
Project leader:
To test and evaluate a heterogeneous stream-processing system consisting of an FPGA-based systemon-chip and a host, we develop a benchmark called SKYSHARK. It uses real-world data from air-traffic control that is publicly available. These data are enhanced for the purpose of the benchmark without changing their characteristics. They are further enriched with aircraft and airport data. We define 14 queries with respect to the particular requirements of our system. They should be useful for other…
Funding source: Siemens AG
Acronym: DQ@Healthineers
Project leader:
Prof. Dr. Richard Lenz
Professorship for Evolutionary Data Management
We will create a generic data quality framework which can be deployed into an evolutionary data lake environment which makes data quality quantifiable and can direct efforts for data quality improvement.
Acronym: FST
Project leader:
With the ongoing rise in global data volumes, database compression is becoming increasingly relevant. While the compression of numeric data types has been extensively researched, the compression of strings has only recently received renewed scientific attention.A promising approach to string compression is the use of symbol tables, where recurring substrings within a database are substituted with short codes. A corresponding table enables the smooth reconstruction of the original data. This meth…
Acronym: PHAROS
Project leader:
Prof. Dr. Richard Lenz
Professorship for Evolutionary Data Management
Der Zweck des Semantic Web ist es, den weltweiten Zugang zum Wissen der Menschheit in maschinenverarbeitbarer Form zu ermöglichen. Ein großes Hindernis dabei ist, dass Wissen oft entweder inkohärent repräsentiert oder gar nicht externalisiert und nur in den Köpfen von Menschen vorhanden ist. Der Aufbau eines Wissensgraphen und die manuelle Erstellung und Fortschreibung einer Ontologie durch einen Domänenexperten ist eine mühsame Arbeit, die einen großen initialen Aufwand erfordert, bis das Ergeb…
Finished research projects
Funding source: Siemens AG
Acronym: CATCH 2.0
Project leader:
Prof. Dr. Richard Lenz
Professorship for Evolutionary Data Management
Building on previous successes in change point analysis, this project advances scalable methods for analyzing large, heterogeneous industrial time series data from power plants. By combining data-driven algorithms with expert knowledge and a platform-based deployment close to the data (cloud deployment), the project enables faster insights, improved anomaly interpretation, and practical decision support for complex thermodynamic systems
Funding source: Siemens AG
Acronym: CATCH
Project leader:
Prof. Dr. Richard Lenz
Professorship for Evolutionary Data Management
This research project investigates the use of unsupervised change point analysis (CPA) methods for knowledge discovery in large-scale industrial time series datasets. Change point analysis offers a promising tool to mine large time series datasets by identifying abrupt and unexpected changes in time series data without requiring supervision. Relating the detected events between multiple signals offers valuable insight into the behavior of complex, dynamical systems enabling to mine events of int…
Funding source: Siemens AG
Acronym: DARTS
Project leader:
Prof. Dr. Richard Lenz
Professorship for Evolutionary Data Management
This research project aims to develop different efficient methods that enable knowledge mining in large time series datasets to uncover relationships and descriptive patterns within the dataset. A key focus is the identification of relationships, which are uncovered using the technique of changepoint correlation that we are actively developing within the project. As the project aims to support or even automate a manual process, visualization, and demonstration of the techniques in question also…
Funding source: Deutsche Forschungsgemeinschaft (DFG)
Acronym: ReProVide II INF6
Project leader:
Analysing petabytes of data in an affordable amount of time and energy requires massively parallel processing of data at their source. Active research is therefore directed towards emerging hardware architectures to reduce the volume of data close to their source and towards sound query analysis and optimisation techniques to exploit such novel architectures. The goal of the ReProVide project is to investigate FPGA-based solutions for smart storage and near-data processing together with novel qu…
Acronym: ANANIA
Project leader:
The compression of data has played a decisive role in data management for a long time. Compressed data can be permanently stored in a more space-saving manner and sent over the network more efficiently. However, the ever-increasing volumes of data mean that the importance of good compression methods is growing all the time.Within the scope of project Anania (Architecture of Non-Multiple Autoencoders for Non-Lossy Information Agglomeration), we are investigating to what extent classical compressi…
Acronym: SIML
Project leader:
Prof. Dr. Richard Lenz
Professorship for Evolutionary Data Management
Within the project SIML (Schema Inference and Machine Learning), methods of topological data analysis and unsupervised learning are combined, applied and further developed in order to derive a conceptual schema from unstructured, multivariant data.
Funding source: DFG / Schwerpunktprogramm (SPP)
Acronym: ReProVide
Project leader: , ,
This project is funded by the German Research Foundation (DFG) within the Priority Program SPP 2037 "Scalable Data Management for Future Hardware".The goal of this project is to provide novel hardware and optimisation techniques for scalable, high-performance processing of Big Data. We particularly target huge datasets with flexible schemas (row-oriented, column-oriented, document-oriented, irregular, and/or non-indexed) as well as data streams as found in click-stream analysis, enterprise sourc…
Funding source: Sonstige EU-Programme (z. B. RFCS, DG Health, IMI, Artemis), Bayerische Staatsministerien
Acronym: E|ASY-Opt INF6
Project leader:
Within the framework of the EFRE-E|ASY-Opt subproject, the potential of data mining methods in the area of manufacturing is being investigated. Especially the training of Deep-Learning models is a computationally intensive task, which may take hours or several days. The training time can be shortened considerably by using an already trained model, as long as the goal and source task are closely related. This connection is not yet fully understood.The aim of this research project is to implement…
Acronym: KYQ
Project leader:
"You should know your queries!" is the long version of the project title. It means that you should not just want tho have a database, but you should also think about the evaluations (which are written down as queries) that you actually would like to do with that database. The creation of a database is quite an effort, regarding not only the deployment of the software on a computer, but even more the capture of all the data to fill it. This effort should be spent with a goal in mind. The proj…
Acronym: SA4CM
Project leader:
Prof. Dr. Richard Lenz
Professorship for Evolutionary Data Management
Fallmanagementsysteme unterstützen Interaktionen zwischen kooperierenden Benutzern typischerweise, indem gemeinsam zu verwendende Dokumente in einem gemeinsamen Repositorium vorgehalten werden. Im vorliegenden Projekt wird untersucht, ob und wie diese Interaktionen durch Klassifikation als Sprechakte besser unterstützt werden können. Die Sprechakt-Theorie beschreibt die pragmatischen Aspekte kommunikativen Handelns. Dabei werden Äußerungen je nach der pragmatischen Intention des Sprechers in ver…
Acronym: DAMSEL
Project leader:
The world of data-management systems has become a bit confusing during the last years. Next to the well-established relational database systems, so-called NoSQL systems have been developed, which pretend to cope with much larger data volumes. At the same time, they can only offer limited functionality with respect to efficient data access and can only give reduced consistency guarantees. That raises the question when to stick to a relational database and when to move to a NoSQL system. This…
Acronym: OCEAN
Project leader:
Prof. Dr. Richard Lenz
Professorship for Evolutionary Data Management
Mehr und mehr Unternehmen sammeln möglichst alle anfallenden Daten in sogenannten "Data Lakes". Obwohl die Daten damit prinzipiell für beliebige Analysen zur Verfügung stehen, bleibt es dennoch unerlässlich für die Analyse, ein Verständnis für die Bedeutung und die Verknüpfungsoptionen der Daten zu entwickeln. Analysten, die diese Arbeit bereits geleistet haben, formulieren Anfragen, in denen solches Wissen implizit enthalten ist. Wenn dieses Wissen jedoch nicht mit anderen geteilt wird, bleiben…
Funding source: DFG / Forschungsgruppe (FOR)
Acronym: BATS-TP3
Project leader:
Animal observation can be improved significantly with the help of modern technology. Especially in the case of bats this has been quite difficult in the past, because they are active only at night, and they must not carry a transmitter heavier than 10% of their own body weight. The progress of micro electronics has made it possible to build complete computers that fulfill these requirements. They do not just send beacons, but data. The ground station receives these data and evaluates them. …
Funding source: BMFTR / Spitzencluster
Acronym: H-04
Project leader:
Prof. Dr. Richard Lenz
Professorship for Evolutionary Data Management
Die Integration von Medizinprodukten in die realen Abläufe und Arbeitsprozesse einer Produktivumgebung ist sowohl für Hersteller wie auch Betreiber eine schwierige, zeit- und kostenintensive Aufgabe. Trotz Standardisierung von DICOM und HL7 bereitet die Integration von Softwarekomponenten und Medizinprodukten in ein Krankenhausinformationssystem wegen fehlender geeigneter Validierungsumgebungen immer noch einen erheblichen Aufwand. Gegenstand des Projekts ist die Erstellung einer gener…
Funding source: Industrie
Acronym: DQ-Step
Project leader:
Prof. Dr. Richard Lenz
Professorship for Evolutionary Data Management
Der Einsatz IT-gestützter Prozesse im Kraftwerksbau in den Bereichen Engineering, Procurement and Construction (EPC) nimmt immer mehr zu, wodurch derQualität der Daten in den IMS (Information Management Systems) immer mehr Bedeutung zukommt. Unter IMS werden in diesem Zusammenhang im Wesentlichen die Software-Produkte Vantage Plant Engineering (VPE), Vantage Plant Design (VPD)und Vantage Project Resource Management (VPRM) sowie die angrenzenden Tools(z.B. MOM, PIS, DM, etc.) verstanden…
Acronym: DSAM
Project leader:
DSAM is a middleware for managing global data-stream queries. These queries are distributed to heterogeneous platforms including self-contained data-stream management systems and sensor networks. The project's main goal is to automatically distribute and deploy a platform-independent model, i.e. a global query, to heterogeneous and distributed stream-processing components. Queries are defined in a declarative abstract query language. They are partitioned according to cost models and topological…
- AnFACS (2007 – 2012)
Analyse von föderierten Zugriffskontrollsystemen - CoBRA DB (2005-2011)
komponentenbasiertes, zur Laufzeit anpassbares Datenbanksystem - Comaera (2005-2007)
Software-Komponenten mit quantitativen Eigenschaften und Performanzvorhersage - COMQUAD (2002-2005)
Software-Komponenten mit quantitativen Eigenschaften und Adaptivität - CubeStar (1996-2002)
Modellierung und Anfrageverarbeitung in Data-Warehouse-Systemen - dbprost (2007-2010)
Datenbankgestützte Prozessautomatisierung bei Software Tests - DQ-Step (2009-2012)
Verbesserung der Datenqualität bei einem Referenzunternehmen im Anlagenbau - fCMDB08(2008-2009)
Föderierte Configuration-Management-Datenbank für Siemens IT Solutions and Services - FlexWCM (2002-2005)
Flexible Konzepte für das Web-Content-Management - i6 M²EtIS (2009 – 2014)
i6 Massive Multiplayer EvenT Integration System - i6sdb (2006 – 2011)
Datenstrom- und Datenbanksysteme - iArch (2003-2007)
Integratives IT-Architekturmanagement - iRM (2001-2005)
Integration Repository Manager - Marrakesch (auf Englisch) (2000-2005)
Vertragsverhandlungen von komplex konfigurierbaren Produkten und Dienstleistungen - medITalk (2010-2016)
Horizontale Innovationen zur Produkt- und Prozessoptimierung - Prozessorientierte Informationssysteme im Krankenhaus und im Versorgungsnetz (2002-2005)
- Pixtract (2007-2012)
Effiziente objekterkennungsbasierte Annotation von Bildern - ProHTA (2010-2015)
Prospective Health Technology Assessment - ProMed (2007 – 2012)
Prozessunterstützung in der Medizin - PubScribe (1999-2002)
Untersuchung von Publish/Subscribe-Mechanismen - RETAVIC (auf Englisch) (2002-2008)
Audio- und Video-Konvertierung in Echtzeit für MMDBVS - SCINTRA (2001-2004)
Die Anwendung von Datenbanktechnologien im Grid fokussierte dieses Projekt. - SeMeOr (2005-2008)
Sicherheitsmetrik für Organisationen - SFB 539 (Glaukome einschließlich Pseudoexfoliationssyndrom (PEX)) (2003-2009)
Integration von IT-Systemen zu einem hochwertigen Gesamtregister für die klinische Forschung. - SKM (2002-2006)
Semantisches Knowledge Management - SUSHy (2011-2014)
Entwicklung eines neuartigen und übergeordneten Gesamtsystems für komplexe Anlagen - TDQMed (2011-2015)
Testdatenqualität für medizinische Geräte