Wolfgang Müller adminproject_administratorasset_housekeeper

Projects: Playground, Scientific Databases and Visualisation

Institutions: Heidelberg Institute for Theoretical Studies

https://orcid.org/0000-0002-4980-3512
Hadas Leonov

Projects: Playground, Scientific Databases and Visualisation

Institutions: Heidelberg Institute for Theoretical Studies

Olga Krebs

Projects: Scientific Databases and Visualisation

Institutions: Heidelberg Institute for Theoretical Studies

Ulrike Wittig

Projects: Scientific Databases and Visualisation

Institutions: Heidelberg Institute for Theoretical Studies

https://orcid.org/0000-0002-9077-5664
ISO 20691:2022 Biotechnology — Requirements for data formatting and description in the life sciences
Scientific Databases and Visualisation

Abstract (Expand)

This document specifies requirements for the consistent formatting and documentation of data and corresponding metadata (i.e. data describing the data and its context) in the life sciences, including … biotechnology, and biomedical, as well as non-human biological research and development. It provides guidance on rendering data in the life sciences findable, accessible, interoperable and reusable (F-A-I-R). This document is applicable to manual or computational workflows that systematically capture, record or integrate data and corresponding metadata in the life sciences for other purposes. This document provides formatting requirements for both primary experimental or procedural data obtained manually and machine derived data. This document also describes requirements for storing, sharing, accessing, interoperability and reuse of data and corresponding metadata in the life sciences. This document specifies requirements for large quantities of data systematically obtained from automated high throughput workflows in the life sciences, as well as requirements for large-scale and small-scale data sets obtained by other life science technologies and manual data capture. This document is applicable to many domains in biotechnology and the life sciences including, but not limited to: basic/applied research in all domains of the life sciences, and industrial, medical, agricultural, or environmental biotechnology (excluding for diagnostic or therapeutic purposes), as well as methodology-driven domains, such as genomics (including massive parallel sequencing, metagenomics, epigenomics and functional genomics), transcriptomics, translatomics, proteomics, metabolomics, lipidomics, glycomics, enzymology, immunochemistry, synthetic biology, systems biology, systems medicine and related fields.

Author: Martin Golebiewski

Date Published: 4th Nov 2022

Publication Type: Misc

COVID-19-Forschungsdaten leichter zugänglich machen – Aufbau einer bundesweiten Informationsinfrastruktur
Scientific Databases and Visualisation

Abstract (Expand)

Public health research and epidemiological and clinical studies are necessary to understand the COVID-19 pandemic and to take appropriate action. Therefore, since early 2020, numerous research projects … have also been initiated in Germany. However, due to the large amount of information, it is currently difficult to get an overview of the diverse research activities and their results. Based on the "Federated research data infrastructure for personal health data" (NFDI4Health) initiative, the "COVID-19 task force" is able to create easier access to SARS-CoV-2- and COVID-19-related clinical, epidemiological, and public health research data. Therefore, the so-called FAIR data principles (findable, accessible, interoperable, reusable) are taken into account and should allow an expedited communication of results. The most essential work of the task force includes the generation of a study portal with metadata, selected instruments, other study documents, and study results as well as a search engine for preprint publications. Additional contents include a concept for the linkage between research and routine data, a service for an enhanced practice of image data, and the application of a standardized analysis routine for harmonized quality assessment. This infrastructure, currently being established, will facilitate the findability and handling of German COVID-19 research. The developments initiated in the context of the NFDI4Health COVID-19 task force are reusable for further research topics, as the challenges addressed are generic for the findability of and the handling with research data.

Authors: Carsten Oliver Schmidt, Juliane Fluck, Martin Golebiewski, Linus Grabenhenrich, Horst Hahn, Toralf Kirsten, Sebastian Klammt, Matthias Löbe, Ulrich Sax, Sylvia Thun, Iris Pigeot, Wolfgang Ahrens, Johannes Darms, Jörg Henke, Xiaoming Hu, Sophie Klopfenstein, Lisa Langnickel, Bianca Lassen-Schmidt, Hermann Pohlabeln, Michael Lieser, Anatol-Fiete Näher, Markus Scholz, Carina Vorisek, Dagmar Waltemath, Hannes Wünsche

Date Published: 23rd Jul 2021

Publication Type: Journal

Facilitating Study and Item Level Browsing for Clinical and Epidemiological COVID-19 Studies.
Scientific Databases and Visualisation

Abstract (Expand)

COVID-19 poses a major challenge to individuals and societies around the world. Yet, it is difficult to obtain a good overview of studies across different medical fields of research such as clinical … trials, epidemiology, and public health. Here, we describe a consensus metadata model to facilitate structured searches of COVID-19 studies and resources along with its implementation in three linked complementary web-based platforms. A relational database serves as central study metadata hub that secures compatibilities with common trials registries (e.g. ICTRP and standards like HL7 FHIR, CDISC ODM, and DataCite). The Central Search Hub was developed as a single-page application, the other two components with additional frontends are based on the SEEK platform and MICA, respectively. These platforms have different features concerning cohort browsing, item browsing, and access to documents and other study resources to meet divergent user needs. By this we want to promote transparent and harmonized COVID-19 research.

Authors: C. O. Schmidt, J. Darms, A. Shutsko, M. Lobe, R. Nagrani, B. Seifert, B. Lindstadt, M. Golebiewski, S. Koleva, T. Bender, C. R. Bauer, U. Sax, X. Hu, M. Lieser, V. Junker, S. Klopfenstein, A. Zeleke, D. Waltemath, I. Pigeot, J. Fluck

Date Published: 27th May 2021

Publication Type: Journal

Towards standardization guidelines for in silico approaches in personalized medicine
Scientific Databases and Visualisation

Abstract (Expand)

Despite the ever-progressing technological advances in producing data in health and clinical research, the generation of new knowledge for medical benefits through advanced analytics still lags behind … its full potential. Reasons for this obstacle are the inherent heterogeneity of data sources and the lack of broadly accepted standards. Further hurdles are associated with legal and ethical issues surrounding the use of personal/patient data across disciplines and borders. Consequently, there is a need for broadly applicable standards compliant with legal and ethical regulations that allow interpretation of heterogeneous health data through in silico methodologies to advance personalized medicine. To tackle these standardization challenges, the Horizon2020 Coordinating and Support Action EU-STANDS4PM initiated an EU-wide mapping process to evaluate strategies for data integration and data-driven in silico modelling approaches to develop standards, recommendations and guidelines for personalized medicine. A first step towards this goal is a broad stakeholder consultation process initiated by an EU-STANDS4PM workshop at the annual COMBINE meeting (COMBINE 2019 workshop report in same issue). This forum analysed the status quo of data and model standards and reflected on possibilities as well as challenges for cross-domain data integration to facilitate in silico modelling approaches for personalized medicine.

Authors: Søren Brunak, Catherine Bjerre Collin, Katharina Eva Ó Cathaoir, Martin Golebiewski, Marc Kirschner, Ingrid Kockum, Heike Moser, Dagmar Waltemath

Date Published: 24th Jul 2020

Publication Type: Journal

SEEK: a systems biology data and model management platform.
Scientific Databases and Visualisation

Abstract (Expand)

BACKGROUND: Systems biology research typically involves the integration and analysis of heterogeneous data types in order to model and predict biological processes. Researchers therefore require tools … and resources to facilitate the sharing and integration of data, and for linking of data to systems biology models. There are a large number of public repositories for storing biological data of a particular type, for example transcriptomics or proteomics, and there are several model repositories. However, this silo-type storage of data and models is not conducive to systems biology investigations. Interdependencies between multiple omics datasets and between datasets and models are essential. Researchers require an environment that will allow the management and sharing of heterogeneous data and models in the context of the experiments which created them. RESULTS: The SEEK is a suite of tools to support the management, sharing and exploration of data and models in systems biology. The SEEK platform provides an access-controlled, web-based environment for scientists to share and exchange data and models for day-to-day collaboration and for public dissemination. A plug-in architecture allows the linking of experiments, their protocols, data, models and results in a configurable system that is available 'off the shelf'. Tools to run model simulations, plot experimental data and assist with data annotation and standardisation combine to produce a collection of resources that support analysis as well as sharing. Underlying semantic web resources additionally extract and serve SEEK metadata in RDF (Resource Description Format). SEEK RDF enables rich semantic queries, both within SEEK and between related resources in the web of Linked Open Data. CONCLUSION: The SEEK platform has been adopted by many systems biology consortia across Europe. It is a data management environment that has a low barrier of uptake and provides rich resources for collaboration. This paper provides an update on the functions and features of the SEEK software, and describes the use of the SEEK in the SysMO consortium (Systems biology for Micro-organisms), and the VLN (virtual Liver Network), two large systems biology initiatives with different research aims and different scientific communities.

Authors: K. Wolstencroft, S. Owen, O. Krebs, Q. Nguyen, N. J. Stanford, M. Golebiewski, A. Weidemann, M. Bittkowski, L. An, D. Shockley, J. L. Snoep, W. Mueller, C. Goble

Date Published: 15th Jul 2015

Publication Type: Journal

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