As part of the research process, hypotheses are formulated and tested by collecting and analyzing data, possibly from many different technologies and sources. With measurement technologies moving at a very fast pace, it is now easy for a single lab to generate several TBs of data in a short time.

Research groups invest a lot of time, money and effort into collecting and analyzing these data, and to publish new discoveries. However, it is common that less attention is given to preserving the data at the heart of a discovery and to ensuring that the published results can be reproduced at a later time. Reproducibility of results, however, is a prerequisite for sound scientific progress.

Data management is the process of safeguarding the data and of annotating it with enough meaningful information, so called metadata, to allow anyone in the field to make sense of it at a later point in time. Data management platforms allow users to annotate the data and store it in a single place, accessible by anybody with sufficent permissions and easily searchable.

How can SIS help you with Research Data Management?

We provide consulting, services and software solutions for scientific facilities, groups and research projects to safely and reproducibly manage their research data. As handling of research data is highly dependent on the research domain, there are no general solutions for this problem. However, there are best practices and concepts that can be applied to many domains for organizing their data.

Data Management Consulting

We can provide advice on how to best manage the data produced in your lab. We usually arrange a meeting to discuss the work done in the lab or facility, understand the workflows and then make suggestions on how to best manage the data. Funding agencies tend to more and more require data management plans from applicants as part of a project proposal (e.g. in the EU Horizon2020 program). We can work jointly with you on the data management plan, combining your expertise on your data with our experience on research data management and best practices.

This data management checklist (pdf file) created by the ETH and EPFL libraries can also assist you in your planning.

Data Management Services

We provide data management systems based on the platform openBIS as a service for scientific facilities, groups and research projects to manage their research data. In addition, we also provide an extension of openBIS that combines the powerful data management capabilities of this software with an Electronic Laboratory Notebook (ELN) and a Laboratory Information Management System (LIMS) for life science research: openBIS ELN-LIMS.

Our services include:

  • software installation and maintenance on ETH Informatikdienste infrastructure
  • software customization
  • training
  • continuous support
  • writing scripts for heavy data import
  • integration of openBIS with measurement instruments for direct data import
  • migration of legacy databases to openBIS

Some examples of our services are:

  • ELN-LIMS. A growing number of labs in D-BIOL, D-BSSE and D-USYS are using openBIS ELN-LIMS. We support different usage scenarios:

    1. LIMS only. Samples and/or protocols are stored in the database.
    2. LIMS + DM simple use-case. (1) + Experiments are created but not documented, files concerning experiments (pictures of gels, excel files, etc.) are uploaded from the browser.
    3. LIMS + ELN + DM simple use-case. (1) + Experiments are documented with links to the LIMS and small files concerning experiments (pictures of gels, excel files, etc.) are uploaded from the browser.
    4. LIMS + DM complex use-case. (2) + Measurement instruments are integrated, so raw data can be directly imported into the database.
    5. LIMS + ELN + DM complex use-case. (3) + Measurement instruments are integrated, so raw data can be directly imported into the database.
  • Management of high throughput sequencing data. The Genomics Facility Basel gives researchers of the life science community in Basel and at ETH Zurich direct access to next generation sequencing (NGS) and complementary genomics technologies. We assisted them and developed software to manage and track sequencing data. Read about our work for the Genomics Facility Basel.

  • Management of other high-throughput OMICS data.

    1. The Aebersold Lab at the Institute of Molecular Systems Biology develops and applies novel methods in quantitative mass spectrometry to accurately measure protein analytes in complex samples. This requires the management and analysis of massive amounts of data. The lab is using a system built on openBIS and iPortal for this: SWATH mass spec workflow.
    2. The Sauer and Zamboni Labs pursue a strongly data-driven research approach largely based on mass spectrometry and fluorescent microscopy running several hundreds of experiments and > 100’000 mass spectrometry runs per year. We provide the High-Throughput Metabolomics data management solution to the labs.

Data Management Plans

Users of openBIS at ETH can download a DMP template for SNSF grant applications with pre-filled answers related to data storage, backup and preservation.

Personalized Health

With the Personalized Health Data Services, SIS commits to support the biomedical and personalized health research community of the ETH Domain with large volume data management, analysis, interoperability, sharing and security solutions for data driven biomedical research.