@inproceedings{reimer_deploying_2020,
	title = {Deploying a molecular tumor board on an open platform},
	series = {Student Conference Proceedings},
	pages = {139--142},
	publisher = {Infinite Science Publishing},
	author = {Reimer, Niklas and Busch, Hauke and Ingenerf, Josef},
	year = {2020},
}

@article{ablas_konzeption_2020,
	title = {Konzeption und {Implementierung} einer {Geräteschnittstelle} des {TECAN} {EVO} {Aliquotierroboter} im {Biobankkontext}},
	journal = {GMS Medizinische Informatik, Biometrie und Epidemiologie},
	author = {Ablaß, Torge and Ulrich, Hannes and Kock-Schoppenhauer, Ann-Kristin and Simon, Friedrich and Wagenzink, Stefanie and Maushagen, Regina and Habermann, Jens K. and Ingenerf, Josef},
	year = {2020},
}

@inproceedings{kath_connecting_2020,
	series = {Student {Conference} {Proceedings}},
	title = {Connecting {Old} {Devices} {Safely} {To} {The} {Cloud}},
	isbn = {978-3-945954-62-1},
	publisher = {Infinite Science Publishing},
	author = {Kath, Niclas and Seidel, Arne and Ingenerf, Josef},
	year = {2020},
	pages = {277--280}
}

@article{ulrich_analysis_2020,
	title = {Analysis of {ISO}/{TS} 21526 {Towards} the {Extension} of a {Standardized} {Query} {API}},
	volume = {275},
	issn = {1879-8365},
	doi = {10.3233/SHTI200723},
	abstract = {Metadata is often used for different tasks in the field of medical informatics: semantic description of data, quality validation, data integration, or information retrieval. Metadata definitions are captured and curated in time-consuming tasks and stored in metadata repositories that manage and preserve the metadata. Due to technical and legal restrictions, metadata is rarely as easily accessible and interoperable as it is necessary for modern information systems. In a previous study, a uniform interface based on the widely used ISO/IEC 11179 and the Facebook data retrieval language GraphQL was introduced as a solution to these technical obstacles. In the meantime, the ISO standard 21526 has been published, a recent version designed with a strong focus on health informatics. While it is conceptually oriented on the metamodel in ISO 11179, a number of extensions but also restructurings have been introduced. In this study, the authors investigated the difference between ISO 11179 and ISO 21526 and extended the unified metadata query interface to be future-proof and in particular, to support the semantic extensions of ISO 21526.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Ulrich, Hannes and Kock-Schoppenhauer, Ann-Kristin and Drenkhahn, Cora and Löbe, Matthias and Ingenerf, Josef},
	month = nov,
	year = {2020},
	pmid = {33227769},
	keywords = {GraphQL, ISO 11179, ISO 21526, Metadata, Metadata Repository},
	pages = {202--206},
}

@inproceedings{barkow_analysis_2020,
	series = {Student {Conference} {Proceedings}},
	title = {Analysis of {Data} {Loss} when using the {Archiving} and {Exchange} {Interface} for {Practice} {Management} {Systems}},
	isbn = {978-3-945954-62-1},
	publisher = {Infinite Science Publishing},
	author = {Barkow, Linus and Meincke, Oliver and Ulrich, Hannes and Ingenerf, Josef},
	year = {2020},
	pages = {123--126}
}

@article{ulrich_smart_2020,
	title = {A Smart Mapping Editor for Standardised Data Transformation},
	volume = {270},
	issn = {1879-8365},
	doi = {10.3233/SHTI200354},
	abstract = {The integration of heterogeneous healthcare data sources is a necessary process to enable the secondary use valuable information in clinical research. Data integration is time-consuming for data stewards. The transformation using predefined rules for data harmonization can reduce the time-consuming and error-prone work and ease the data integration at various sites. In our study, we examined various script(ing) languages to find the most suitable candidate for definition of transformation rules and implement a smart editor which supports the data stewards in selecting rules reusing them. Thereby, it also provides an automatic and seamless documentation to strengthen the reliability of the defined transformation rules.},
	pages = {1185--1186},
	journaltitle = {Studies in Health Technology and Informatics},
	shortjournal = {Stud Health Technol Inform},
	author = {Ulrich, Hannes and Germer, Sebastian and Kock-Schoppenhauer, Ann-Kristin and Kern, Jori and Lablans, Martin and Ingenerf, Josef},
	date = {2020-06-16},
	pmid = {32570571},
	keywords = {Data Warehousing, Delivery of Health Care, Documentation, Electronic Health Records, {HL}7 {FHIR}, Health Information Interoperability, Health Level Seven, Reproducibility of Results},
}

@article {ulrich_ql4mdr,
	title = {QL4MDR: a GraphQL query language for ISO 11179-based metadata repositories},
        url = {https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-019-0794-z},
	journal = {BMC Medical Informatics and Decision Making},
	volume = {19},
	year = {2019},
	month = {03/2019},
	pages = {45},
	abstract = {Heterogeneous healthcare instance data can hardly be integrated without harmonizing its schema-level metadata. Many medical research projects and organizations use metadata repositories to edit, store and reuse data elements. However, existing metadata repositories differ regarding software implementation and have shortcomings when it comes to exchanging metadata. This work aims to define a uniform interface with a technical interlingua between the different MDR implementations in order to enable and facilitate the exchange of metadata, to query over distributed systems and to promote cooperation. To design a unified interface for multiple existing MDRs, a standardized data model must be agreed on. The ISO 11179 is an international standard for the representation of metadata, and since most MDR systems claim to be at least partially compliant, it is suitable for defining an interface thereupon. Therefore, each repository must be able to define which parts can be served and the interface must be able to handle highly linked data. GraphQL is a data access layer and defines query techniques designed to navigate easily through complex data structures.},
	issn = {1472-6947},
	doi = {10.1186/s12911-019-0794-z},
		author = {Ulrich, Hannes and Kern, Jori and Tas, Deniz and Kock-Schoppenhauer, Ann-Kristen and Ückert, Frank and Ingenerf, Josef and Lablans, Martin},

}

@article{ulrich_towards_2019,
	title = {Towards a {Federation} of {Metadata} {Repositories}: {Addressing} {Technical} {Interoperability}},
	volume = {253},
	issn = {0926-9630},
	abstract = {Secondary use of routinely collected data is more and more promoted by the utilization of metadata repositories. However, this has not yet solved the problem of data exchange across organizational boundaries. The local description of a metadata set must also be exchangeable for flawless data exchange. In previous work a metadata exchange language QL4MDR was developed. The aim of this work was to examine the applicability of this exchange language. For this purpose, existing MDR implementations were identified and systematically inspected. Roughly divided into two categories to distinguish between data integration and query integration. It has been shown that all the implementations can be adapted to QL4MDR. The integration of metadata is an important first step; it enables the exchange of information, which is so urgently needed for the further processing of instance data, from the metadata mappings to the transformation regulations.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Ulrich, Hannes and Kern, Jori and Kock-Schoppenhauer, Ann-Kristin and Lablans, Martin and Ingenerf, Josef},
	year = {2019},
	pmid = {30147040},
	keywords = {Algorithms, Databases, Factual, Federation, GraphQL, Metadata, Metadata repository, Neo4j, QL4MDR, Statistics as Topic, graph database},
	pages = {55--59}
}

@article{andersen_service-oriented_2019,
	title = {Service-{Oriented} {Device} {Connectivity}: {Device} {Specialisations} for {Interoperability}},
	volume = {264},
	issn = {1879-8365},
	shorttitle = {Service-{Oriented} {Device} {Connectivity}},
	doi = {10.3233/SHTI190274},
	abstract = {There are IEEE 11073 standards for foundational, structural, and semantic point-of-care medical device interoperability, but the first devices with this interface have yet to enter the market. One of the missing pieces for implementation and approval are Device Specialisations that specify how to use information and service models to represent a specific type of device on the network. Required and optional metrics need to be standardised as well as nomenclature terms, units of measure, and extension points. Finally, device-to-device interaction at runtime has to be defined for automatic verification during testing and approval. Applications include C-arm fluoroscopes used in different clinical settings.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Andersen, Björn and Baumhof, Simon and Ingenerf, Josef},
	year = {2019},
	pmid = {31437975},
	keywords = {Computer Communication Networks, Health Information Interoperability, Reference Standards},
	pages = {509--511}
}

@article{kock-schoppenhauer_scientific_2019,
	title = {Scientific {Challenge} in {eHealth}: {MAPPATHON}, a {Metadata} {Mapping} {Challenge}},
	volume = {264},
	issn = {1879-8365},
	shorttitle = {Scientific {Challenge} in {eHealth}},
	doi = {10.3233/SHTI190512},
	abstract = {Scientific challenges based on benchmark data enable the comparison and evaluation of different algorithms and take place regularly in scientific disciplines like medical image processing, text mining or genetics. The idea of a challenge is rarely applied within the eHealth community. Mappathon is a metadata mapping challenge that asks for methods to find corresponding data elements within similar datasets and to correlate data elements among each other.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Kock-Schoppenhauer, Ann-Kristin and Bruland, Philipp and Kadioglu, Dennis and Brammen, Dominik and Ulrich, Hannes and Kulbe, Kerstin and Duhm-Harbeck, Petra and Ingenerf, Josef},
	year = {2019},
	pmid = {31438209},
	keywords = {Algorithms, Benchmarking, Data Mining, Image Processing, Computer-Assisted, Metadata, Telemedicine},
	pages = {1516--1517}
}

@misc{klaucke_b._medical_2019,
	address = {Luebeck},
	type = {Poster},
	title = {Medical {Informatics} in {Biobanks}: {Experiences} from an {Interdisciplinary} {Internship} from the {Student}'s {Side}},
	shorttitle = {Medical {Informatics} in {Biobanks}: {Experiences} from an {Interdisciplinary} {Internship} from the {Student}'s {Side}},
	url = {http://europebiobankweek.eu/wp-content/uploads/2019/10/EBW-2019-Abstract-Book-Poster-Presentations-20191007.pdf},
	abstract = {Background
Students choose to study Medical Informatics because it is scientifically oriented and at the same time practicerelated. The tasks in the research field between medicine and computer science serve to further improve medical care and patient treatment in the future.
Methods
The practical course in the master's program can be done in research institutions or companies in Germany
or abroad. This internship lasts six months and is carried out at the IT Center for Clinical Research, Lübeck in close cooperation with the Interdisciplinary Center for Biobanking-Lübeck at the campus.
Results
During the internship two main areas of the clinical infrastructure, biobanking and study administration can
be explored. In the laboratory of ICB-L collecting, processing and storage of samples are demonstrated,
especially the different automated storage systems. Regarding the samples, the cut of tissue samples is
examined in the pathology. Getting to know these biobank relevant processes is particularly instructive to
transfer them to mobile sample documentation. In the field of study management different approaches for
automated study recruitment on the basis of inclusion and exclusion criteria were evaluated.
Discussion
The practical course had a positive influence on my professional and personal development. In particular, the interaction with other international interns of other disciplines was very educational. I think the internship is a good preparation for my future professional life. The wideranging ethical and data protection requirements were both a challenge and an opportunity.},
	language = {English},
	author = {{Klaucke, B.}},
	collaborator = {{Kock-Schoppenhauer, A.K.} and {Simon, F.} and {Wagenzink, S.} and {Fkiri, H.} and {Maushagen, R.} and {Figge, L.} and {Flügge,F.} and {Habermann, J.K.} and {Ingenerf, J.} and {DuhmHarbeck, P.}},
	month = oct,
	year = {2019},
	keywords = {EBW}
}

@misc{simon_f._illustrating_2019,
	address = {Luebeck},
	type = {Poster},
	title = {Illustrating the {Sample} {Life} {Cycle} at an {Hospital} {Integrated} {Biobank}},
	shorttitle = {Illustrating the {Sample} {Life} {Cycle} at an {Hospital} {Integrated} {Biobank}},
	url = {http://europebiobankweek.eu/wp-content/uploads/2019/10/EBW-2019-Abstract-Book-Poster-Presentations-20191007.pdf},
	abstract = {Background
Biobanks collect high-quality biological material, donorspecific data, and sociodemographic information about the donor. Sample-specific data such as sampling time, processing conditions or sample location should all be documented in a Biobank Management System. The hospital-integrated biobank ICB-L uses the software CentraXX from KAIROS ® to enable sample and data management.
Methods
To proof the quality of processing and storage, we developed a sample-life-cycle BIRT-report (Business
Intelligence and Reporting Tools) and made it available in CentraXX. This analysis contains information about donors, medical-conditions, acquisition and storage. With the distribution of the sample the monitoring process ends. results All information is processed at the individual sample level from sampling to storage. Temperature has a major influence on sample quality, which is why the analysis of sample storage has a special focus. Taking into account the temperature logs supplied by the trackers, a temperature curve is drawn on the box/rack level. Special events such as the opening of the box, e.g. for the storage of new samples or removal of samples, are projected. Repositioning of the box within the nitrogen tank is timed as well as the position inside the box. discussion The quality can only
be guaranteed over a long period if the samples are stored properly. Freezing and thawing cycles,
unintentional temperature changes and exposure to air and other substances can have unintentional
consequences. The report is a tool to visualize and summarize all available data. The data was queried and
analyzed from two databases and more than 50 tables.},
	language = {English},
	author = {{Simon, F.}},
	collaborator = {{Kock-Schoppenhauer, A.K.} and {Wagenzink, S.} and {Maushagen, R.} and {Figge, L.} and {Flügge, F.} and {Habermann, J.K.} and {Duhm-Harbeck, P.}},
	month = oct,
	year = {2019},
	keywords = {EBW}
}

@article{deppenwiese_mdrcupid:_2019,
	title = {{MDRCupid}: {A} {Configurable} {Metadata} {Matching} {Toolbox}.},
	volume = {264},
	journal = {Studies in health technology and informatics},
	author = {Deppenwiese, Noemi and Duhm-Harbeck, Petra and Ingenerf, Josef and Ulrich, Hannes},
	year = {2019},
	keywords = {Algorithms, Data Curation, Delivery of Health Care, Health Information Interoperability, Metadata},
	pages = {88--92}
}

@misc{kock-schoppenhauer_generic_2019,
	address = {Lübeck},
	type = {Vortrag},
	title = {Generic {Test} {Protocol} for the {Integration} {Test} of {Automated} {Storage} {Systems} on {Rack} or {Tube} {Level}},
	author = {Kock-Schoppenhauer, Ann-Kristin},
	collaborator = {Wagenzink, Stefanie and Stüdemann, Maj Kristin and Figge, Lena and Flügge, Friedemann and Simon, Friedrich and Maushagen, Regina and Habermann, Jens K. and Duhm-Harbeck, Petra},
	year = {2019}
}

@article{kasparick_enabling_2019,
	title = {Enabling artificial intelligence in high acuity medical environments},
	volume = {28},
	issn = {1365-2931},
	doi = {10.1080/13645706.2019.1599957},
	abstract = {Acute patient treatment can heavily profit from AI-based assistive and decision support systems, in terms of improved patient outcome as well as increased efficiency. Yet, only very few applications have been reported because of the limited accessibility of device data due to the lack of adoption of open standards, and the complexity of regulatory/approval requirements for AI-based systems. The fragmentation of data, still being stored in isolated silos, results in limited accessibility for AI in healthcare and machine learning is complicated by the loss of semantics in data conversions. We outline a reference model that addresses the requirements of innovative AI-based research systems as well as the clinical reality. The integration of networked medical devices and Clinical Repositories based on open standards, such as IEEE 11073 SDC and HL7 FHIR, will foster novel assistance and decision support. The reference model will make point-of-care device data available for AI-based approaches. Semantic interoperability between Clinical and Research Repositories will allow correlating patient data, device data, and the patient outcome. Thus, complete workflows in high acuity environments can be analysed. Open semantic interoperability will enable the improvement of patient outcome and the increase of efficiency on a large scale and across clinical applications.},
	language = {eng},
	number = {2},
	journal = {Minimally invasive therapy \& allied technologies: MITAT: official journal of the Society for Minimally Invasive Therapy},
	author = {Kasparick, Martin and Andersen, Björn and Franke, Stefan and Rockstroh, Max and Golatowski, Frank and Timmermann, Dirk and Ingenerf, Josef and Neumuth, Thomas},
	year = {2019},
	pmid = {30950665},
	keywords = {Artificial Intelligence, Context-aware medical technology, Critical Care, Decision Support Systems, Clinical, Efficiency, Organizational, HL7 FHIR, Humans, IEEE 11073 SDC, Surgical Procedures, Operative, Workflow, big data, surgery},
	pages = {120--126}
}

@misc{wagenzink_s._central_2019,
	address = {Luebeck},
	type = {Poster},
	title = {Central {Acquisition} and {Visualization} of {Temperature} {Logs} of {Various} {Biobank} {Storage} {Systems}},
	shorttitle = {Central {Acquisition} and {Visualization} of {Temperature} {Logs} of {Various} {Biobank} {Storage} {Systems}},
	url = {http://europebiobankweek.eu/wp-content/uploads/2019/10/EBW-2019-Abstract-Book-Poster-Presentations-20191007.pdf},
	abstract = {Background
Quality-assured biobanks are obliged to keep a complete sample documentation. The appropriate storage temperature is particularly responsible for the sample quality. Storage systems either have internal temperature recording or are equipped with such systems. Having this information available in a uniform format and in one place facilitates overview and access.
Methods
In this project, the -80°C Thermo Fisher freezers, the automated storage systems HS200 from Askion and BIO Store III from Brooks and the conventional tanks using TTracker are taken into account by ICB-L. This selection results in four different temperature measurement systems and different formats, which need to be harmonized.
Results
Not all storage systems have a direct connection to the network of the biobank software, they have to be read and transferred manually. We have developed an interface that reads the formats and transfers the specific xml format. All temperature logs of these devices are then stored as measurement series in the BIMS and can be used for further analysis. Errors and other logging system specific events are stored and considered separately. An automated analysis of the temperature data, over the different systems becomes now even possible.
Discussion
We can continuously retrieve and use the logs of the automated systems to identify deviations and promote an early reaction. But also the non-automated storage systems can be better controlled by automatic instead of manual verification. This specific information can then be used to calculate curves on single tube level.},
	language = {English},
	author = {{Wagenzink, S.}},
	collaborator = {{Kock-Schoppenhauer, A.K.} and {Simon, F.} and {Maushagen, R.} and {Figge, L.} and {Flügge, F.} and {Habermann, J.K.} and {Duhm-Harbeck, P.}},
	month = oct,
	year = {2019},
	keywords = {EBW}
}

@article{drenkhahn_aggregation_2019,
	title = {Aggregation and {Visualization} of {Laboratory} {Data} by {Using} {Ontological} {Tools} {Based} on {LOINC} and {SNOMED} {CT}},
	volume = {264},
	issn = {1879-8365},
	doi = {10.3233/SHTI190193},
	abstract = {With the proliferation of digital communication in healthcare, the reuse of laboratory test data entails valuable insights into clinical and scientific issues, basically enabled by semantic standardization using the LOINC coding system. In order to extend the currently limited potential for analysis, which is mainly caused by structural peculiarities of LOINC, an algorithmic transformation of relevant content into an OWL ontology was performed, which includes LOINC Terms, Parts and Hierarchies. For extending analysis capabilities, the comprehensive SNOMED CT ontology is added by transferring its contents and the recently published LOINC-related mapping data into OWL ontologies. These formalizations offer rich, computer-processable content and allow to infer additional structures and relationships, especially when used together. Consequently, various reutilizations are facilitated; an application demonstrating the dynamic visualization of fractional hierarchy structures for user-supplied laboratory data was already implemented. By providing element-wise aggregation via superclasses, an adaptable, graph representation is obtained for studying categorizations.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Drenkhahn, Cora and Duhm-Harbeck, Petra and Ingenerf, Josef},
	year = {2019},
	pmid = {31437895},
	keywords = {Biomedical Ontologies, Computers, LOINC, Logical Observation Identifiers Names and Codes, SNOMED CT, Semantics, Systematized Nomenclature of Medicine},
	pages = {108--112}
}

@inproceedings{wiedekopf_human_2019,
	address = {Lübeck},
	title = {Human {Readable} {Data} {Export} of {Medical} {Documentation}},
	isbn = {978-3-945954-57-7},
	booktitle = {Student {Conference} 2019, {Medical} {Engineering} {Science}, {Medical} {Informatics}, {Biomedical} {Engineering} and {Auditory} {Technology}},
	publisher = {Infinite Science Publishing},
	author = {Wiedekopf, Joshua and Becker, Tim and Ingenerf, Josef},
	editor = {Buzug, Thorsten M. and Handels, Heinz and Klein, Stephan and Mertins, Alfred},
	year = {2019},
	note = {Backup Publisher: Infinite Science Publishing},
	pages = {277--280},
}

@techreport{kock-schoppenhauer_integrating_nodate,
	address = {MIE 2018, Gothenburg},
	type = {accepted as {Poster}},
	title = {Integrating {Instance}- and {Systemlevel} {Provenance} {Data} for {Supporting} {Secondary} {Use} of {Healthcare} {Data}},
	author = {Kock-Schoppenhauer, Ann-Kristin and Hartung, Lisa and Ulrich, Hannes and Duhm-Harbeck, Petra and Ingenerf, Josef}
}

@article{ulrich_using_2018,
	title = {Using {Graph} {Tools} on {Metadata} {Repositories}},
	volume = {253},
	issn = {1879-8365},
	abstract = {To exchange data across several sites or to interpret it at a later point in time, it is necessary to create a general understanding of the data. As a standard practice, this understanding is achieved through metadata. These metadata are usually stored in relational databases, so-called metadata repositories (MDR). Typical functions of such an MDR include pure storage, administration and other specific metadata functionalities such as finding relations among data elements. This results in a multitude of connections between the data elements, which can be described as highly interconnected graphs. To use alternative databases such as graph databases for modelling and visualisation it has already been proven to be beneficial in previous studies. The objective of this work is to evaluate how on-board techniques rely on matching and mapping using a graph database. Different datasets relating to cancer were entered, and algorithms for metadata management were applied.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Ulrich, Hannes and Kock-Schoppenhauer, Ann-Kristin and Duhm-Harbeck, Petra and Ingenerf, Josef},
	year = {2018},
	pmid = {30147040},
	keywords = {Algorithms, Databases, Factual, graph database, Metadata, Metadata repository, Neo4j, Statistics as Topic},
	pages = {55--59}
}

@techreport{bruland_secondary_nodate,
	address = {MIE 2018, Gothenburg},
	type = {accepted as {Workshop}},
	title = {Secondary use of {Routinely} {Collected} {Healthcare} {Data} for {Multiple} {Purposes} – {Experiences} and {Obstacles}},
	author = {Bruland, Philipp and Kock-Schoppenhauer, Ann-Kristin and Kadioglu, Dennis}
}

@article{kock-schoppenhauer_practical_2018,
	title = {Practical {Extension} of {Provenance} to {Healthcare} {Data} {Based} on the {W}3C {PROV} {Standard}},
	volume = {253},
	issn = {0926-9630},
	abstract = {Secondary use of healthcare data is dependent on the availability of provenance data for assessing its quality, reliability or trustworthiness. Usually, instance-level data that might be communicated by HL7 interfaces entail limited metadata about involved software systems, persons or organizations bearing responsibility for those systems. This paper proposes a strategy for capturing interoperable provenance data needed by data stewards for assessing healthcare data that are reused in a research context. Aimed at a realistic level of granularity even system-level metadata will support a data steward trying to trace the origins or provenance of healthcare data that have been transferred to the research context. Those metadata are extracted from the 3LGM2-system, used for modelling hospital information systems. Based on the W3C provenance specification interrelated activities, entities and agents can be integrated and stored in RDF triple stores and therefore queried and visualized.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Kock-Schoppenhauer, Ann-Kristin and Hartung, Lina and Ulrich, Hannes and Duhm-Harbeck, Petra and Ingenerf, Josef},
	year = {2018},
	pmid = {30147034},
	keywords = {Metadata, Software, Delivery of Health Care, Reproducibility of Results, interoperable provenance data, Secondary use of EHR data, Statistics as Topic},
	pages = {28--32}
}

@techreport{ulrich_modelling_nodate,
	address = {MIE 2018, Gothenburg},
	type = {accepted as {Short} {Communication}},
	title = {Modelling a {Metadata} {Repository} in a {Graph} {Database} using {Neo}4j},
	author = {Ulrich, Hannes and Kock-Schoppenhauer, Ann-Kristin and Duhm-Harbeck, Petra and Ingenerf, Josef}
}

@inproceedings{drenkhahn_mapping_2018,
	series = {Student {Conference} {Proceedings}},
	title = {Mapping of {Laboratory} {Services} included in an {Internal} {Catalog} to {SNOMED} {CT} using the {UMLS}},
	isbn = {978-3-945954-47-8},
	abstract = {The contributions to this proceedings book show how new approaches and methods in medical engineering and medical informatics can advance medicine, health and health care. The papers focus on the following topics: Medical Image Processing, Medical Imaging, Signal Processing, Biomedical Optics, Biochemical Physics, Safety and Quality, E-Health.},
	language = {English},
	booktitle = {Student {Conference} {Proceedings} 2018: 7th {Conference} on {Medical} {Engineering} {Science} and 3rd {Conference} on {Medical} {Informatics} and 1st {Conference} on {Biomediacal} {Engineering}},
	publisher = {Infinite Science Publishing},
	author = {Drenkhahn, Cora and Ulrich, Hannes and Ingenerf, Josef and Duhm-Harbeck, Petra},
	editor = {Buzug, Thorsten and Handels, Heinz and Klein, Stephan},
	year = {2018},
	pages = {337--340}
}

@article{ververs_konvertierung_2018,
	title = {Konvertierung von {MIMIC}-{III}-{Daten} zu {FHIR}},
	url = {http://www.egms.de/en/meetings/gmds2018/18gmds018.shtml},
	doi = {10.3205/18gmds018},
	abstract = {Einleitung: Die Medical Information Mart for Intensive Care (MIMIC-III) [ref:1] ist eine für akademische Zwecke frei verfügbare Datenbank mit klinischen Patientendaten aus vorwiegend intensivmedizinischen Fällen und umfasst ca. 59000 Aufenthalte von ca. 46000 Patienten. Zu diesen[zum vollständigen Text gelangen Sie über die oben angegebene URL]},
	language = {de},
	urldate = {2018-11-20},
	journal = {63. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)},
	author = {Ververs, Stefanie and Ulrich, Hannes and Kock, Ann-Kristin and Ingenerf, Josef},
	editor = {Deutsche Gesellschaft Für Medizinische Informatik, Biometrie Und Epidemiologie},
	month = aug,
	year = {2018}
}

@techreport{kock-schoppenhauer_mappathon_2018,
	address = {63. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)},
	title = {Mappathon – {A} {Metadata} {Mapping} {Challenge} for {Secondary} {Use}},
	url = {https://www.mappathon.de},
	author = {Kock-Schoppenhauer, Ann-Kristin and Bruland, Philipp and Kadioglu, Dennis},
	month = sep,
	year = {2018}
}

@article{neumann_entwicklung_2018,
	title = {Entwicklung eines generischen {Modells} zur {Abbildung} von {Studienzentralen} in {CentraXX}},
	url = {http://www.egms.de/en/meetings/gmds2018/18gmds003.shtml},
	doi = {10.3205/18gmds003},
	abstract = {Einleitung: Klinische Studien sind für den Fortschritt in der Medizin unabdingbar. Studien können beispielsweise Teil des Entwicklungsplans eines Arzneimittels (AMG-Studie) oder Medizinproduktes (MPG-Studie) sein oder untersuchen andere Therapien [ref:1]. Die Verwaltung und Durchführung[zum vollständigen Text gelangen Sie über die oben angegebene URL]},
	language = {de},
	urldate = {2018-11-20},
	journal = {63. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)},
	author = {Neumann, Anke and Kock, Ann-Kristin and Simon, Friedrich and Wagenzink, Stefanie and Nohr, Manuela and Jürgens, Martin and Milinski, Rita and Holler, Ursula and Habermann, Jens K. and Duhm-Harbeck, Petra and Ingenerf, Josef},
	editor = {Deutsche Gesellschaft Für Medizinische Informatik, Biometrie Und Epidemiologie},
	month = aug,
	year = {2018},
	keywords = {Medizinische Informatik},
	file = {Snapshot:C\:\\Users\\Ann-Kristin Kock\\Zotero\\storage\\B34VPNQ5\\18gmds003.html:text/html}
}

@techreport{kock-schoppenhauer_new_2018,
	address = {Global Biobank Week 2018, Antwerpen},
	title = {New {Data} {Quality} {BIRT}-{Reports} for {Biobanks}},
	author = {Kock-Schoppenhauer, Ann-Kristin and Simon, Friedrich and Wagenzink, Stefanie and Maushagen, Regina and Oberländer, Martina and Figge, Lena and Duhm-Harbeck, Petra and Habermann, Jens K.},
	year = {2018}
}

@article{andersen_connecting_2018,
	title = {Connecting the clinical {IT} infrastructure to a service-oriented architecture of medical devices},
	volume = {63},
	issn = {0013-5585},
	doi = {10.1515/bmt-2017-0021},
	abstract = {The new medical device communication protocol known as IEEE 11073 SDC is well-suited for the integration of (surgical) point-of-care devices, so are the established Health Level Seven (HL7) V2 and Digital Imaging and Communications in Medicine (DICOM) standards for the communication of systems in the clinical IT infrastructure (CITI). An integrated operating room (OR) and other integrated clinical environments, however, need interoperability between both domains to fully unfold their potential for improving the quality of care as well as clinical workflows. This work thus presents concepts for the propagation of clinical and administrative data to medical devices, physiologic measurements and device parameters to clinical IT systems, as well as image and multimedia content in both directions. Prototypical implementations of the derived components have proven to integrate well with systems of networked medical devices and with the CITI, effectively connecting these heterogeneous domains. Our qualitative evaluation indicates that the interoperability concepts are suitable to be integrated into clinical workflows and are expected to benefit patients and clinicians alike. The upcoming HL7 Fast Healthcare Interoperability Resources (FHIR) communication standard will likely change the domain of clinical IT significantly. A straightforward mapping to its resource model thus ensures the tenability of these concepts despite a foreseeable change in demand and requirements.},
	language = {English},
	number = {1},
	journal = {Biomedizinische Technik},
	author = {Andersen, Björn and Kasparick, Martin and Ulrich, Hannes and Franke, Stefan and Schlamelcher, Jan and Rockstroh, Max and Ingenerf, Josef},
	year = {2018},
	pages = {57--68}
}

@article{kock-schoppenhauer_compatibility_2018,
	title = {Compatibility {Between} {Metadata} {Standards}: {Import} {Pipeline} of {CDISC} {ODM} to the {Samply}.{MDR}},
	volume = {247},
	issn = {0926-9630},
	abstract = {The establishment of a digital healthcare system is a national and community task. The Federal Ministry of Education and Research in Germany is providing funding for consortia consisting of university hospitals among others participating in the "Medical Informatics Initiative". Exchange of medical data between research institutions necessitates a place where meta information for this data is made accessible. Within these consortia different metadata registry solutions were chosen. To promote interoperability between these solutions, we have examined whether the portal of Medical Data Models is eligible for managing and communicating metadata and relevant information across different data integration centres of the Medical Informatics Initiative and beyond. Apart from the MDM-portal, some ISO 11179-based systems such as Samply.MDR as well as openEHR-based solutions are going to be applyed. In this paper, we have focused on the creation of a mapping model between the CDISC ODM standard and the Samply.MDR import format. In summary, it can be stated that the mapping model is feasible and promote the exchangeability between different metadata registry approaches.},
	language = {eng},
	journal = {Studies in health technology and informatics},
	author = {Kock-Schoppenhauer, Ann-Kristin and Ulrich, Hannes and Wagenzink, Stefanie and Duhm-Harbeck, Petra and Ingenerf, Josef and Neuhaus, Philipp and Dugas, Martin and Bruland, Philipp},
	year = {2018},
	keywords = {Metadata, Humans, Biomedical Research, Germany, Metadata/standards, Reference Standards, Registries, CDISC ODM, data elements, mapping, MDR, metadata registry},
	pages = {221--225}
}

@techreport{kock-schoppenhauer_ccdc_2018,
	address = {Global Biobank Week 2018, Antwerpen},
	title = {{CCDC} {Data} {Provision} in the {Context} of {BBMRI}-{ERIC} {ADOPT} {CRC}-{Cohort}},
	author = {Kock-Schoppenhauer, Ann-Kristin and Wagenzink, Stefanie and Böckmann, Lars and Krampitz, Anna and Simon, Friedrich and Duhm-Harbeck, Petra and Habermann, Jens K.},
	year = {2018}
}

@article{simon_aufbau_2018,
	title = {Aufbau eines campusweiten {Studienregisters} harmonisiert aus {DRKS}, {ClinicalTrails}.gov und {EU} {Clinical} {Trials} {Register}},
	url = {http://www.egms.de/en/meetings/gmds2018/18gmds001.shtml},
	doi = {10.3205/18gmds001},
	abstract = {Einleitung: Ein Studienregister ermöglicht einen aktuellen und nutzerorientierten Überblick über laufende und abgeschlossene Studien. Die frei verfügbaren Informationen in den nationalen und internationalen Studienregistern unterstützen die Transparenz in der medizinischen Forschung.[zum vollständigen Text gelangen Sie über die oben angegebene URL]},
	language = {de},
	urldate = {2018-11-20},
	journal = {63. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)},
	author = {Simon, Friedrich and Kock, Ann-Kristin and Neumann, Anke and Wagenzink, Stefanie and Nohr, Manuela and Jürgens, Martin and Milinski, Rita and Holler, Ursula and Habermann, Jens K. and Ingenerf, Josef and Duhm-Harbeck, Petra},
	editor = {Deutsche Gesellschaft Für Medizinische Informatik, Biometrie Und Epidemiologie},
	month = aug,
	year = {2018}
}

@article{kern_method_2018,
	title = {A {Method} to use {Metadata} in legacy {Web} {Applications}: {The} {Samply}.{MDR}.{Injector}},
	abstract = {Whenever medical data is integrated from multiple sources, it is regarded good practice to separate data from information about its meaning, such as designations, definitions or permissible values (in short: metadata). However, the ways in which applications work with metadata are imperfect: Many applications do not support fetching metadata from externalized sources such as metadata repositories. In order to display human-readable metadata in any application, we propose not to change the application, but to provide a library that makes a change to the user interface. The goal of this work is to provide a way to “inject” the meaning of metadata keys into the web-based frontend of an application to make it “metadata aware”.},
	journal = {Stud Health Technol Inform},
	author = {Kern, Jori and Tas, Deniz and Ulrich, Hannes and Schmidt, Esther Erika and Ingenerf, Josef and Ückert, Frank and Lablans, Martin},
	year = {2018}
}

@techreport{kock-schoppenhauer_data_2018,
	address = {Nationales Biobanken-Symposium Moderne Biobanken – fit for purpose!},
	title = {Data {Quality} {Analysis} for {Biobanks}},
	author = {Kock-Schoppenhauer, Ann-Kristin and Simon, Friedrich and Maushagen, Regina and Oberländer, Martina and Figge, Lena and Habermann, Jens K. and Duhm-Harbeck, Petra},
	year = {2018}
}

@techreport{kock-schoppenhauer_increasing_2017,
	address = {Stockholm},
	type = {poster},
	title = {Increasing {Standardization} of {Biobank} {Data} through {HL}7 {FHIR} {Mapping}},
	author = {Kock-Schoppenhauer, Ann-Kristen and Ulrich, Hannes and Duhm-Harbeck, Petra and Habermann, Jens K. and Ingenerf, Josef},
	year = {2017}
}

@techreport{neumann_it_nodate,
	title = {The {IT} {Architecture} of the {German} {Biobank} {Alliance} ({GBA})},
	author = {Neumann and Lablans and Döllinger and Duhm-Harbeck and Ebert and Habermann and Hummel and Illig and Ingenerf and Kadioglu and Kern and Kiel and Knell and Kock and Linde and Maier and Mate and Popp and Proynova and Rambow and Rufenach and Sahr and Schmidt and Schüttler and Ulrich and Prokosch and Ückert}
}

@article{kock-schoppenhauer_linked_2017,
	title = {Linked {Data} {Applications} {Through} {Ontology} {Based} {Data} {Access} in {Clinical} {Research}},
	volume = {235},
	issn = {0926-9630},
	abstract = {Clinical care and research data are widely dispersed in isolated systems based on heterogeneous data models. Biomedicine predominantly makes use of connected datasets based on the Semantic Web paradigm. Initiatives like Bio2RDF created Resource Description Framework (RDF) versions of Omics resources, enabling sophisticated Linked Data applications. In contrast, electronic healthcare records (EHR) data are generated and processed in diverse clinical subsystems within hospital information systems (HIS). Usually, each of them utilizes a relational database system with a different proprietary schema. Semantic integration and access to the data is hardly possible. This paper describes ways of using Ontology Based Data Access (OBDA) for bridging the semantic gap between existing raw data and user-oriented views supported by ontology-based queries. Based on mappings between entities of data schemas and ontologies data can be made available as materialized or virtualized RDF triples ready for querying and processing. Our experiments based on CentraXX for biobank and study management demonstrate the advantages of abstracting away from low level details and semantic mediation. Furthermore, it becomes clear that using a professional platform for Linked Data applications is recommended due to the inherent complexity, the inconvenience to confront end users with SPARQL, and scalability and performance issues.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Kock-Schoppenhauer, Ann-Kristin and Kamann, Christian and Ulrich, Hannes and Duhm-Harbeck, Petra and Ingenerf, Josef},
	year = {2017},
	pmid = {28423769},
	keywords = {Electronic Health Records, Internet, Semantics, Biomedical Research, Biological Ontologies, Information Storage and Retrieval, Linked Data, Semantic Querying and Data Integration, Semantic Web},
	pages = {131--135}
}

@techreport{neumann_konzept_nodate,
	address = {Berlin},
	type = {Poster},
	title = {Konzept eines lokalen regelbasierten {Antwortsystems} zur automatischen {Anfrage}-{Prüfung} in {Biobanken}},
	author = {Neumann and Ulrich, Hannes and Linde, John and Lablans, Martin and Döllinger, Christoph and Duhm-Harbeck, Petra and Ebert, Lars and Habermann, Jens K. and Illig, Thomas and Ingenerf, Josef and Kern, Jori and Kiel, Alexander and Knell, Christian and Kock, Ann-Kristin and Maier and Mate, Sebastian and Popp and Proynova and Rambow, Matt and Rufenach and Sahr and Schmidt and Schüttler, Christina and Seelke and Prokosch, Ulrich and Ückert and Hummel, Michael}
}

@article{ulrich_analysis_2017,
	title = {Analysis of {Annotated} {Data} {Models} for {Improving} {Data} {Quality}},
	volume = {243},
	issn = {0926-9630},
	abstract = {The public Medical Data Models (MDM) portal with more than 9.000 annotated forms from clinical trials and other sources provides many research opportunities for the medical informatics community. It is mainly used to address the problem of heterogeneity by searching, mediating, reusing, and assessing data models, e. g. the semi-interactive curation of core data records in a special domain. Furthermore, it can be used as a benchmark for evaluating algorithms that create, transform, annotate, and analyse structured patient data. Using CDISC ODM for syntactically representing all data models in the MDM portal, there are semi-automatically added UMLS CUIs at several ODM levels like ItemGroupDef, ItemDef, or CodeList item. This can improve the interpretability and processability of the received information, but only if the coded information is correct and reliable. This raises the question how to assure that semantically similar datasets are also processed and classified similarly. In this work, a (semi-)automatic approach to analyse and assess items, questions, and data elements in clinical studies is described. The approach uses a hybrid evaluation process to rate and propose semantic annotations for under-specified trial items. The evaluation algorithm operates with the commonly used NLM MetaMap to provide UMLS support and corpus-based proposal algorithms to link datasets from the provided CDISC ODM item pool.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Ulrich, Hannes and Kock-Schoppenhauer, Ann-Kristin and Andersen, Björn and Ingenerf, Josef},
	year = {2017},
	pmid = {28883198},
	keywords = {Humans, Electronic Health Records, Semantics, Algorithms, CDISC ODM, Data Accuracy, Medical Informatics, Natural Language Processing, Semantic Interoperability, UMLS},
	pages = {190--194}
}

@inproceedings{deppenwiese_entwicklung_2017,
	address = {Oldenburg},
	title = {Entwicklung eines {Tools} zum {Konvertieren} von {HL}7 {FHIR} {Questionnaires} in das {MOLGENIS} {EMX} {Format}},
	url = {https://www.egms.de/static/en/meetings/gmds2017/17gmds148.shtml},
	doi = {10.3205/17gmds148},
	booktitle = {62. {Jahrestagung} der {Deutschen} {Gesellschaft} für {Medizinische} {Informatik}, {Biometrie} und {Epidemiologie} e.{V}. ({GMDS})},
	publisher = {German Medical Science GMS Publishing House},
	author = {Deppenwiese, Noemi and Hannes, Ulrich and Wrage, Jan-Hinrich and Kock, Ann-Kristin and Ingenerf, Josef},
	year = {2017}
}

@article{maushagen_cross-border_2017,
	title = {Cross-border biobanking: {The} {German}-{Danish} {Interreg} project {BONEBANK}},
	shorttitle = {Cross-border biobanking},
	url = {https://portal.findresearcher.sdu.dk/en/publications/cross-border-biobanking-the-german-danish-interreg-project-boneba},
	language = {English},
	urldate = {2019-02-13},
	author = {Maushagen, Regina and Gemoll, Timo and Oberlaender, Martina and Faccinetti, Giulia and Figge, Lena and Kock-Schoppenhauer, Ann-Kristin and Duhm-Harbeck, Petra and Niessen, Lina and Unger, Andreas and Waizner, Klaus and Wendlandt, Robert and Zweig, Wiebke and Kowal, Justyna M. and Haakonsson, Anders and Bober, Christina and Diercks, Kai and Nassutt, Roman and Buescher, Robin and Reimers, Nils and Schmal, Hagen and Duckert, Ralf and Kroeger, Ines and Stueck, Gesine and Kessel, Stefanie and Hecht, Mirjam and Frahm, Thomas and Eckers, Anna and Brilling, Julia and Barington, Torben and Kassem, Moustapha and Schulz, Arndt-Peter and Habermann, Jens K.},
	year = {2017},
	file = {Snapshot:C\:\\Users\\Ann-Kristin Kock\\Zotero\\storage\\D95Z922L\\cross-border-biobanking-the-german-danish-interreg-project-boneba.html:text/html}
}

@misc{baake_creating_2017,
	title = {Creating {Reports} with {BIRT} to support the {Development} {Process} of {Medical} {Software}},
	author = {Baake, Merle},
	year = {2017},
	file = {Publikationen | Institute of Medical Informatics:C\:\\Users\\Ann-Kristin Kock\\Zotero\\storage\\GNQU4WSC\\biblio.html:text/html}
}

@techreport{lablans_it_nodate,
	address = {Stockholm},
	type = {Poster},
	title = {An {IT} {Architecture} for {Federated} {Biobanking} in {Germany}},
	author = {Lablans, Martin and Döllinger, Christoph and Duhm-Harbeck, Petra and Ebert, Lars and Habermann, Jens K. and Illig, Thomas and Ingenerf, Josef and Kadioglu, Dennis and Kern, Jori and Kiel, Alexander}
}

@article{ulrich_metadata_2016,
	title = {Metadata {Repository} for {Improved} {Data} {Sharing} and {Reuse} {Based} on {HL}7 {FHIR}},
	volume = {228},
	issn = {0926-9630},
	abstract = {Unreconciled data structures and formats are a common obstacle to the urgently required sharing and reuse of data within healthcare and medical research. Within the North German Tumor Bank of Colorectal Cancer, clinical and sample data, based on a harmonized data set, is collected and can be pooled by using a hospital-integrated Research Data Management System supporting biobank and study management. Adding further partners who are not using the core data set requires manual adaptations and mapping of data elements. Facing this manual intervention and focusing the reuse of heterogeneous healthcare instance data (value level) and data elements (metadata level), a metadata repository has been developed. The metadata repository is an ISO 11179-3 conformant server application built for annotating and mediating data elements. The implemented architecture includes the translation of metadata information about data elements into the FHIR standard using the FHIR Data Element resource with the ISO 11179 Data Element Extensions. The FHIR-based processing allows exchange of data elements with clinical and research IT systems as well as with other metadata systems. With increasingly annotated and harmonized data elements, data quality and integration can be improved for successfully enabling data analytics and decision support.},
	language = {eng},
	journal = {Studies in Health Technology and Informatics},
	author = {Ulrich, Hannes and Kock, Ann-Kristin and Duhm-Harbeck, Petra and Habermann, Jens K. and Ingenerf, Josef},
	year = {2016},
	pmid = {27577363},
	keywords = {},
	pages = {162--166}
}