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Auflistung nach Autor:in "Kiel, Alexander"

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  • Konferenzbeitrag
    Metadata Management for Data Integration in Medical Sciences
    (Datenbanksysteme für Business, Technologie und Web (BTW 2017), 2017) Kirsten, Toralf; Kiel, Alexander; Rühle, Mathias; Wagner, Jonas
    Clinical and epidemiological studies are commonly used in medical sciences. They typically collect data by using different input forms and information systems. Metadata describing input forms, database schemas and input systems are used for data integration but are typically distributed over different software tools; each uses portions of metadata, such as for loading (ETL), data presentation and analysis. In this paper, we describe an approach managing metadata centrally and consistently in a dedicated Metadata Repository (MDR). Metadata can be provided to different tools. Moreover, the MDR includes a matching component creating schema mappings as a prerequisite to integrate captured medical data. We describe the approach, the MDR infrastructure and provide algorithms for creating schema mappings. Finally, we show selected evaluation results. The MDR is fully operational and used to integrate data from a multitude of input forms and systems in the epidemiological study LIFE.
  • Konferenzbeitrag
    Ontology-based registration of entities for data integration in large biomedical research projects
    (INFORMATIK 2010. Service Science – Neue Perspektiven für die Informatik. Band 1, 2010) Kirsten, Toralf; Kiel, Alexander
    Large biomedical projects often include workflows running across institutional borders. In these workflows, data describing biomedical entities, such as patients, bio-materials but also processes itself, is typically produced, modified and analyzed at different locations and by several systems. Therefore, both tracking entities within inter-organizational workflows and data integration are often crucial steps. To address these problems, we centrally register entities and their relationships by using a multi-layered model. The model utilizes an ontology and a typed system graph to semantically describe and classify entities and their relationships but also to access entity data on demand in their original source. Moreover, this integration approach allows to centrally track entities along the project workflows and can be used in explorative data analyses as well as by other data integration approaches using the registered entity relationships. We describe the model, the utilized ontology, and a system implementing this approach, which is applied in a large biomedical research project.
  • Textdokument
    Selecting, Packaging, and Granting Access for Sharing Study Data
    (INFORMATIK 2017, 2017) Kirsten, Toralf; Kiel, Alexander; Wagner, Jonas; Rühle, Mathias; Löffler, Markus
    Data in medical studies and research projects are captured, curated and analyzed, often, with a substantial personal and financial effort. Such study data are typically managed by institutions and groups who are involved in these studies and projects. Often, they are refrained by these institutions and, thus, not shared with other scientists who are interested in similar medical topics or hypotheses. Open the data for other scientists will speed up medical insights, enable analyzes which currently lacks data amount either by enlarge the set size of study objects and by finding suitable controls, and allow to validate published results taking data from other studies into account. In this paper, we introduce the data sharing approach we use at the LIFE Research Center for Civilization Diseases, University Leipzig. Our approach is influenced by the OAIS reference model for archiving and distributing data to a designated community. We highlight several aspects of this approach, sketch the process and describe the supporting IT infrastructure. In particular, we outline the LIFE Data Portal and the LIFE Proposal Manager allowing to find, access, and reuse metadata and study data for dedicated analysis projects.