EMBL-SciLifeLab Data Science workshop
We would like to cordially invite members of the SciLifeLab and EMBL Communities to this workshop! This event will bring together researchers, scientific and technical staff at the EMBL and SciLifeLab, to make new acquaintances and collaborations and to learn and be inspired by each other.
The workshop program starts at 09:00 on May 15 and ends after lunch on May 16.
The workshop will be a hybrid event enabling participation to the wider community at all EMBL and SciLifeLab sites.
Looking forward to meeting you in Uppsala in May!
- Internal and external training and support
- Provision of public data services – computational tools
- Artificial intelligence
- Integrated data management and Scientific workflow sharing
- Technical infrastructure – computational solutions
- Biological theme – Imaging
- Biological theme – Human data
Participation by invitation only. Target audience: SciLifeLab and EMBL staff.
- Johan Rung, SciLifeLab
- Carolina Wählby, SciLifeLab
- Jan Korbel, EMBL
- Rupert Lueck, EMBL
- Rolf Apweiler, EMBL
Monday May 15
|Time slot||Monday, May 15|
|09:00||Welcome and introduction|
Olli Kallioniemi, SciLifeLab and DDLS Director, and Jan Korbel, Head of Data Science EMBL
|09:15||Session 1: Internal & external training & support|
Themes: what is training at EMBL, Data Science training work stream -SciLifeLab training hub -Areas for synergies
Moderator: Cath Brooksbank, EMBL-EBI
|EMBL Data Science Training: the story so far|
Lisanna Paladin, EMBL-Heidelberg
|SciLifeLab Training Hub: the story starts now – what are the goals?|
Nina Norgren, SciLifeLab
|Panel discussion and questions on stimulating exchange & collaboration|
Mounting of posters
|10:50||Session 2: Provision of public data services – computational tools|
Moderator: Johanna McEntyre
|Successfully managing a portfolio of data services|
Johanna McEntyre, Associate Director for Service, EMBL-EBI
Sameer Velankar (PDB Europe)
|Panel discussion: the future challenges and opportunities for public data services|
|13:15||Session 3: Artificial Intelligence|
Moderator: Carolina Wählby
|AI in Image Analysis|
Anna Kreshuk, EMBL
|AI in Cancer genomics, prediction of treatment|
Isidro Cortes-Ciriano, EMBL
|AI in spatial omics|
Carolina Wählby, SciLifeLab
|Serving AI models|
Ola Spjuth, SciLifeLab
|14:50||Session 4: Integrated data management & Scientific workflow sharing|
Moderator: Henning Hermjakob
Irene Papatheodorou, EMBL
Mats Nilsson, SciLifeLab
|16:00||Session 5: Technical infrastructure – computational solutions|
|Cloud – Beyond the hype|
Andy Cafferkey, EMBL
|The IT role in empowering advanced research data management|
Rupert Lück, EMBL
|The great datawanderung – how sensitive data is reshaping research infrastructures. Data transfer, Compute moving to data|
Johan Viklund, SciLifeLab
|Needs and requirements to provide next generation of compute services (notebooks, containerization, GPUs, etc) – energy, carbon issues|
Ola Spjuth, SciLifeLab
|17:05||Wrap-up, discussion and poster session with refreshments|
Tuesday May 16
|Time slot||Tuesday, May 16|
|09:00||Session 6: Biological theme: imaging|
Moderator: Anna Klemm, SciLifeLab
|Project management, data management, including image data publication|
|10:35||Session 7: Biological theme – Human data|
Moderator: Helen Parkinson, EMBL-EBI
|Integrated FEGA/FDA-components/Federated Analysis|
Oliver Stegle, EMBL
|Developments from Human Data Services|
Bengt Persson, NBIS/SciLifeLab
|Afternoon:||Self-organized break-out tech workshops, Site visits, etc|
EMBL and SciLifeLab recently launched data science training initiatives. In this session we will share our approaches to developing data science training – our plans, our successes and our greatest challenges. An open discussion will explore areas for future collaboration and how we might work together to recognise those who dedicate their time, usually on a volunteer basis, to advanced scientific training.
Explore how to manage a portfolio of public computational tools and data services, with real-world examples from both emerging and established resources, and a panel discussion on the future challenges and opportunities for public data services
In this workshop:
- A keynote talk introduces key points of successfully managing a portfolio of data services
- One emerging and one established data service summarize their management approach
- A panel discussion including other data service leads from EMBL-EBI and SciLifeLab discuss the future challenges and opportunities for public data services
In this session we will focus on how to foster AI further (within EMBL-EBI and SciLifeLab) – What are the lessons learned during the last decade of incorporating learning-based methods using neural networks in biomedical research? Where lies the power, and what are the limitations? How do we handle bottle-necks such as lack of reliably annotated training data, and how do we avoid biases introduced by factors such as sample preparation and data collection? How can we include ‘the human in the loop’, and how can we share models?
Modern, data-intensive science requires complex and ideally reproducible workflows. Based on two opening presentations, one from a complex “research” workflow background, one from a repeatable “service” background, and a subsequent panel discussion, we want to explore
- What are the scientific demands and requirements for computational workflows?
- How to strike the right balance between reproducibility and flexibility?
- What is the current status and future aspirations for technical support of computational workflows?
- What are the opportunities for coordination / integration of internal /external workflows between SciLifeLab and EMBL?
The technical infrastructures and computational solutions provided by teams across EMBL and SciLifeLab are at the heart and the critical foundation of data science activities in both institutions. In this session, we aim to initiate a cross-organizational dialogue and to set the stage for further networking among interested stakeholders to explore key IT and technical challenges and learn more about potential solutions being explored on both sides.
The session will start with four short presentations to stimulate the open discussion that will follow. Our input from the presentations will cover a wide range of technical topics and challenges:
i) key aspects of using cloud services,
ii) opportunities to improve scientific data management via dedicated IT solutions,
iii) the challenges associated with shared analysis and transfer of (sensitive) data across centres, and
iv) exploring the needs for next-gen computational, data analytics, and management services for data science in the life sciences.