An overview of the user meeting, plus links to the talks from the user meeting can be found on our blog post http://fair-dom.org/2016/09/22/our-first-user-meeting/
Research Data Manager at the London School of Hygiene and Tropical Medicine
Rewarding open science practice in funded research
This talk will explore the key drivers for encouraging open science practices and steps being taken to build incentives into the research process. It will provide an overview of a Wellcome-commissioned study to investigate current attitudes and actual practices of Wellcome-funded researchers to open science, and barriers that inhibit or prevent them from sharing data.
Senior Lecturer in Bioinformatics, Queen Mary University London, UK
Professor of Biochemistry at the University of Stellenbosch, South Africa
Publishing a FAIR study with citable research assets
The four basic cornerstones of a FAIR research project are that data, methods and models should be Findable, Accessible, Interoperable and Reusable. This functionality can be provided via a good Data Management Platform, such as the SEEK. In addition to making research assets available, for a study to be published, a peer review process must take place, to test formulated hypotheses against the provided results. Using a case study from my research group I will illustrate: 1) the strength of ISA structures to organize research assets and make individual assets citable via DOIs; 2) the versatility of Combine archives to reproduce publication figures running model simulation scripts; and 3) how the SEEK platform facilitates the peer review process and the final publication of a research study.
Star Use Cases
SynthSys, University of Edinburgh, UK
Evaluation of SEEK and OpenBIS for data management on a centre-wide level
21st century science is governed by Data-Intensive Scientific Discovery in which data allows integration and reinforcement between theory, experimentation and simulation. The value of data depends strongly on its comprehensive description: the existence of metadata. However, the annotation process is a laborious one, it is an extra burden for scientists and the main limiting factor which prevents wide-spread data deposition in suitable repositories.
We typically address this problem by adding extra value to data management systems (for example data visualization or pre-processing) in order to provide benefits for the data producers and not only for the data consumers. For centre/institution scale, the data management systems cannot live on their own but they need to be integrated with the existing software infrastructure.
The SEEK and OpenBIS platforms are based on different philosophies and have complementary strengths suitable for the diverse needs of the SynthSyS centre. However, both systems have their limitations which could impact their wide scale application. In this talk, I will present our experience with adoption and integration of SEEK and OpenBIS within our Centre for Synthetic and Systems Biology.
Troup, E, Clark, I, Swain, P, Millar, A & Zielinski, T 2015, Practical evaluation of SEEK and OpenBIS for biological data management in SynthSys
Jon Olav Vik
Digital Salmon, Norwegian University of Life Sciences, Norway
The Digital Salmon – a knowledge base of salmon physiology, data and models
Salmon farming in the future must navigate conflicting and shifting demands of sustainability, shifting feed prices, disease, and product quality. The industry needs to develop a flexible, integrated basis of knowledge for rapid response to new challenges. The Digital Salmon will be an ensemble of mathematical descriptions of salmon physiology, combining mathematics, high-dimensional data analysis, computer science and measurement technology with genomics and experimental biology into a concerted whole. FAIRDOM supports DigiSal in making their data and models findable, accessible, interoperable and reusable. Efficient organization among experiments, measurements, bioinformatics, statistics, and modelling is crucial for the success of the interdisciplinary systems biology approach in DigiSal. Initially we focus on metabolic reaction networks, in particular omega-3 fatty acids and other lipids. I will briefly review the key biological processes and their governing parameters, then outline the key data types and modelling frameworks, sharing the joys and frustrations of adapting the SEEK to our needs.
IMOMESIC, Systems Biology of Signal Transduction, DKFZ, Heidelberg, Germany
Use of OpenBIS within the IMOMESIC Project
Our group is focusing on cancer research applying the system biology approach. That means we combine quantitative experimental data with mathematical modelling in order to increase the gain of information. We are studying function and diseases of lung and liver on different scales and we measure material from patients as well as from model organisms like mice and cell lines. So for us it became more and more important to have a convenient data management to cope with the increasing amount, speed and variety of our generated data.
Here we want to give an overview about our present data management solutions which we use to centralize important information as well as share and store our data. We established in cooperation with the HITS Institute (Heidelberg) a database enabling to handle our antibodies much more efficiently. Additionally, we use a specific database data tool for Immunoblotting experiments (Excemplify). For large scale data storage and analysis, we are implementing the more generic openBIS database. All of these tools enable data submission to the FAIRDOM Hub.
LiSyM, Charite´ – Universitätsmediz Berlin, Germany
Management of data, models and analyses for reproducible computational research: Present and Future
Our group develops computational models of the liver within the German systems biology projects VLN (Virtual Liver Network) and LiSyM (Systems Medicine of the Liver). In this talk we present our experiences in data and model management in recent years and show future directions towards reproducible computational research we plan to implement.
We give an overview over the role of Fairdom and SEEK within our data management solution and how this integrates with and complements other approaches such as code repositories, COMBINE archives, and Research Objects. We present challenges in data management within the typical workflows in model building, the integration of data with models and the preparation of results from computational analysis for publications.
MOSES, ZucAt and ExtremoPharm, Hohenheim University, Stuttgart, Germany
PAL activity in promoting of FAIRDOM projects
PALs are project representatives who are delegated to set and promote a Systems Biology project at FAIRDOM database. Recent practice has shown that PALs become important starters of the project initiation and implementation because their guidance and passion allows finally to achieve required publicity of the project. I am going to exemplify the role of PAL in some finalized (e.g. MOSES), running (e.g. ExtremoPharm) and planned (e.g. GlyCon) projects in field of Systems Biology. Also, I’ll present how the FAIRDOM database helps to set up a new collaborative project.
Federal Research Center Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia
Siberian SEEK: Multiscale modeling of microbial communities
Nowadays, while modern experimental technologies in biology generate colossal amounts of data, reliable data management tools are not only convenient tools for orientation in Data Ocean, but also a dire necessity. The term “big data problems” is often concerned with only experimental data, primarily the next generation. However, there is another source of Big Data in systems biology – computer simulations and modeling, which is especially true in case of multiscale models. Simulations may also generate large amount of data, as well as “raw” data from stochastic models and/or from series of calculations under varying parameter(s), and “dry” resultant data (after statistical analysis etc.).
In our use case we are using the SEEK software and tools for a purpose of data management in simulation of microbial communities evolution. We use Haploid Evolutionary Constructor  – a simulation tool that builds and calculates multiscale models having dozens of parameters to be varied and supports a wide range of stochastic simulations as well. The “phage – bacterial community” model  was chosen as a sample. We are eager to share our experience of using SEEK out of a modeller’s perspective and propose several improvements.
1. Lashin S.A., Matushkin Y.G. Haploid evolutionary constructor: new features and further challenges. // In Silico Biol. 2012. V. 11. N 3-4. P. 125–35.
2. Klimenko A.I. e. Bacteriophages affect evolution of bacterial communities in spatially distributed habitats: a simulation study // BMC Microbiol. 2016. V. 16. N S1. P. 10.