Martin Golebiewski

A test project for EDITH, under which the models for testing the SEEK-EDITH integration are located.

FAIRDOM will establish a support and service network for European Systems Biology. We will serve projects in standardising, managing and disseminating data and models in a FAIR manner: Findable, Accessible, Interoperable and Reusable.

Collection of training material for SEEK/FAIRDOMHub

Good data and model management improves the longevity and impact of your interdisciplinary research. FAIRDOM offers software and expertise to support you in better managing your interdisciplinary life-science projects, particularly in systems and synthetic biology. If you have never heard of data and model management, or are curious about it, or you are an expert keen to exchange ideas, our user meeting is the place for you!

At our users meeting you can:

• Learn why data and model management is ...

nfdi4health aims to create the most comprehensive inventory of German epidemiological, public health and clinical trial data to date. It builds a centralised data catalogue with elaborate search functionalities, sophisticated data access management, and a data analysis toolbox, while respecting stringent requirements for privacy concerning personal health data. Standardisation services ensure a high degree of interoperability. Use cases covering prototypical study types and areas of research show ...

SDBV group using Hub

This project bundles information about COVID-19 related studies and tools in Germany. It intends to provide an information hub for the different initiatives, their aims, their processes, standards and study protocols, as well as their available data and metadata. It is initiated by the German National Research Data Infrastructure for Personal Health Data (nfdi4health), a consortium that plans to establish a concept for a federated research data infrastructure for personal health data in Germany. ...

The GMDS project group bundles activities for health-related FAIR data infrastructures in the fields of biomedical research, clinical data management and medical informatics in Germany. It aims at providing a platform for information exchange about best practice for and implementation of FAIR data management in these fields and constructing a network of FAIR data managements providers in these fields. Through bridging between providers and potential users of such data management platforms within ...

We will contribute to the LiSyM Research Network an open source, freely available and reproducible multiscale model of the human liver from single cell metabolism to whole liver function. The model will be available in existing standards of systems biology, provide standardized interfaces for data integration and be fully annotated to available biological, medical and computational ontologies. All data, models and source code will be shared within the LiSyM Research Network and made available to ...

The workshop focuses on the publication, curation, retrieval, and usage of kinetic data from the reaction kinetics database SABIO-RK and on the use of data in modeling. There will be experience reports from scientists who successfully used experimental data to formulate or verify biological hypotheses with the computer, and you will experience how experimental data can be used with computational models.

Here we share resources and best practices to develop a disease map for COVID-19. The project is progressing as a broad community-driven effort. We aim to establish a knowledge repository on virus-host interaction mechanisms specific to the SARS-CoV-2. The COVID-19 Disease Map is an assembly of molecular interaction diagrams established based on literature evidence.

TA3 focusses on the services, service enabling tools, and software that NFDI4Health will provide to the user community. Most services and tools will be based on open source software that has already been developed by the (co-)applicants or by the broader scientific developer community. In close cooperation with TA4 and TA5, use case requirements and community feedback will help to further develop these tools and to foster interoperability of currently fragmented IT solutions for storage of metadata, ...

nfdi4health Dokumente und (interne) Daten, SOPs, etc., die relevant für das gesamte Konsortium sind

Key activities of TA1 concern the establishment of functional bodies and of the project governance for NFDI4Health.

NFDI4Health task area 2 targets core deficits in medical sciences, i.e. the lack of harmonised standards for data and data quality management in clinical trials, public health surveys, and epidemiological cohorts, as well as the lack of information on and access to relevant standards. By making standards available, TA2 will improve the findability, accessibility and interoperability of existing and novel data bodies. For this purpose, guidelines, standards and policies on data management and ...

With its focus on interaction, networking and exchange, task area 4 addresses the overall NFDI4Health Key Objective to support cooperation between clinical research, epidemiological and public health communities. It also provides training and education for the health research community and beyond, focusing on FAIR data principles.

Shared Space on OneDrive: https://onedrive.live.com/?id=4E57D2DCFD31954C%213715&cid=4E57D2DCFD31954C

The main objective of task area 5 of NFDI4Health is to implement or to at least explore the possibilities to implement these infrastructure components in specific use cases which reflect core needs of the scientific community related to health data research. The use cases will address a range of areas which will lay the ground for future expansion for full coverage of the broad range of data collected in health research.

Data protection regulations have to be taken into account on many levels of the infrastructure developed by NFDI4Health. Moreover, the health data managed by NFDI4Health belong to the so-called special categories of personal data, the processing of which is subject to particularly strict data protection requirements. But nevertheless, data protection law contains a variety of regulatory approaches of data processing for scientific research purposes, which are all aimed at a privileged treatment ...

To achieve data “FAIRification by standardisation” and enable the user community to integrate heterogeneous and complex data, recommendations and guidelines will be developed for the consistent use of domain-specific standards for data formats, as well as for consistent data descriptions based on established metadata standards and terminologies. This standardisation concept will be based on existing standards, such as ISO 20691 and will include the definition of a minimal metadata set for ...

This task T2.3 will target data quality as the “degree to which a set of inherent characteristics of data fulfils requirements” and provide consented standards and metrics to assess the data quality at different stages of the scientific data lifecycle. (1) It will first consider FAIR standards in collaboration with the FAIRMetrics group, FAIRsharing, and RDA FAIR Data Maturity Model group. (2) The second focus will be on adherence to defined data and metadata standards as recommended by nfdi4health ...

T2.4 will define standardisation requirements and develop guidelines, as well as standard-based solutions for data access and interoperability in the defined use cases. To ensure compatibility with existing efforts aiming to improve data interoperability in medicine and healthcare, T2.4 also will coordinate its work closely with the same standardisation initiatives and technical committees of standardisation organisations as T2.2. To enable a seamless access and exchange of health data within the ...

This task aims for policies for data management and publication in order to make data of public health studies findable and interoperable. To find information about studies and (meta-)data and to ensure their interoperability, it is necessary to document the descriptive core elements in a structured way already when planning projects. This applies both to data management and to the subsequent publication of research results and data and is particularly important for research projects handling ...

The NFDI4Health Task Force COVID-19 Metadata Schema Mapping (Metadata Schema Mapping) contains a list of properties describing a resource being registered in the Study Hub of the NFDI4Health Task Force COVID-19 (Study Hub) and how those properties align with other standards (FHIRE, CDISK, DRKS, ITRCP)

The NFDI4Health Task Force COVID-19 Metadata Schema (Metadata Schema) contains a list of properties describing a resource being registered in the Study Hub of the NFDI4Health Task Force COVID-19 (Study Hub).

In response to the COVID-19 pandemic, the Allen Institute for AI has partnered with leading research groups to prepare and distribute the COVID-19 Open Research Dataset (CORD-19), a free resource of over 45,000 scholarly articles, including over 33,000 with full text, about COVID-19 and the coronavirus family of viruses for use by the global research community.

This dataset is intended to mobilize researchers to apply recent advances in natural language processing to generate new insights in ...

The novel coronavirus (SARS-CoV-2) currently spreads worldwide, causing the disease COVID-19. The number of infections increases daily, without any approved antiviral therapy. The recently released viral nucleotide sequence enables the identification of therapeutic targets, e.g., by analyzing integrated human-virus metabolic models. Investigations of changed metabolic processes after virus infections and the effect of knock-outs on the host and the virus can reveal new potential targets. Results: ...

This workshop will be organized by the GMDS project group "FAIRe Dateninfrastrukturen für die Biomedizinische Informatik", established in early 2019. The aim of this project group is to present the activities in various projects and at different German research locations with regard to infrastructures for FAIRes (Finadable, Accessible, Interoperable, Reusable) data management. To this end, a joint exchange of experience will take place in order to plan joint concepts (e.g. dissemination of FAIR, ...

The overarching integrating power of computational modelling, from systems biology to systems medicine

Participants will learn how to structure and share complex data in a Findable, Accessible, Interoperable and Reusable (FAIR) manner. Hands-on sessions, lectures and software demonstrations will provide attendees with the necessary skills to apply components of the FAIRDOM infrastructure in their daily work for interrelating and exchanging data, models and corresponding information.

FAIRDOM is a research infrastructure offering data management support. The SEEK software is designed as registry and ...

Target audience: Wet-lab scientists and people dealing with experimental and/or clinical data for research

Topics include:

• Best practice data structuring (spreadsheets) for experimental and (clinical) samples data
• Comprehensive and unambiguous data description and annotation
• Standard formats and terminologies for data and metadata
• Guidelines for reporting data (Minimum information standards)
• Annotation tools (e.g. RightField: http://www.rightfield.org.uk)
• Using SEEK & FAIRDOMhub ...

The meeting will provide a great opportunity for discussion between modellers, experimentalists and clinicians and to organize and harmonize our future work within the LiSyM network on the grassroot level.

All PhD students as well as all PostDocs of the LiSyM network are kindly requested to register by February 1st

This event is a jointly organized Data Management PALs Meeting that involves PALs from the German LiSyM (Liver Systems Medicine) network and from the ERASysAPP (ERA-Net for Systems Biology Applications) initiative. PALs (Project Area Liaisons) are the front line experts of the data management teams of these projects. They act as data management advocates and help gathering user requirements and testing potential data management solutions. An important part of the meeting will be to gather the ...

This document helps to harmonise the curation efforts for the COVID-19 Disease Map.

The Research Data Alliance (RDA) is a volunteer community of over 10,500 professionals from 145 countries across the globe. In less than two months, the community responded to an urgent call for action and defined much needed, comprehensive recommendations and guidelines for data sharing under the present COVID-19 circumstances.

This is the fifth and final draft of the Recommendations and Guidelines from the RDA COVID-19 working group, and is open for public comment until 8th of June 2020. Following the open period, feedback will be considered and then the WG will seek endorsement of the document from the RDA governance bodies prior to final publication.

Draft guidelines and recommendations; fourth release, 15 May 2020, version for public review

Open listing of contributors to the COVID-19 disease maps