In today's society, sensors, computers, communication platforms and storage technologies give us access to previously unmanageable volumes of data, so-called Big Data. The conversion of data into actionable knowledge creates new opportunities and significant economic values. Big Data has revolutionised both the commercial world and research in many areas, and has opened up for new interdisciplinary collaborations.
The Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) addresses data-driven methods to gain deeper knowledge and understanding in a variety of applications in engineering, science and humanities. Research in computer science, media technology, signal processing and statistics represents the technical core of the center. Combined with research from application fields, such as astrophysics, engineering, linguistics, social science and e-health, we create a unique dynamics.
Exploiting data to gain manageable information and useful knowledge is not a research venture alone. There is also a large collaboration interest in the industry and the public sector. DISA works closely with several clusters, networks and individual companies representing the IT and heavy vehicle industries, the health sector and municipalities and agencies. These partnerships combine excellent research with practical solutions to specific challenges in society, for the mutual benefit of researchers from different scientific disciplines and of external partners.
At DISA, we encourage and support seed projects. Seed projects are intended to promote and nurture excellence research, development, and innovation in data intensive sciences and applications with cross-discipline collaboration. The seed project should belong to one of the research areas within DISA. Please define which core DISA research area/group the seed project belongs to in the proposal, and make sure that the research coordinator of the area is aware of the proposal.
DISA can finance up to SEK 100 000 to initiate research cooperation with a connection to data intensive sciences and applications. External partners can, if required, be funded up to a maximum level of 50 % of DISA’s project funding. They need to co-finance the project with the same amount.
During 2021, there is SEK 700 000 in total available to apply for seed funding.
Objectives for seed projects
The seed project should increase the chances of applications for external funding and/or of publications in top tier journals. Seed project proposals should argue that the planned activities are decisive for achieving the(se) objective(s). Activities may include, but are not limited to:
- Building new cross-disciplinary teams of researchers and/or with industry, aiming for a long-term collaboration.
- Exploring novel research questions in a pre-study.
- Collecting large amounts of data and running initial experiments and analyses.
- Implementing research demonstrators or infrastructure.
Prerequisites and evaluation criteria
The project consortium should consist of one or more researches from DISA. The researchers in the consortium should come from different research disciplines, in order to build a strong cross-discipline collaboration. It is important that all members in the consortium have an active role in the seed project. Please describe the different roles in the proposal. Industry/public sector collaboration is a plus. Please define clearly the added value that the seed project will give to the consortium.
If any member of the consortium is active in another ongoing seed project, please explain the relation between the projects/research.
The evaluation criteria include relevance of the proposal for the operational and strategic goals of DISA, feasibility of the project activity, and chances to eventually succeed with an application for external funding and/or of publications in top tier journals.
Read about the application process in this pdf file. Applications should be submitted no later than the last day in each month to be handled during the following DISA coordinator meeting.
For more information about the seed project concept, please contact Diana Unander.
Ongoing seed projects
- Data intensive analysis for identification and prediction of risk medications and side effects in Kalmar region (DIIPRIM)
Applicants: Tora Hammar, Olof Björneld, Alisa Lincke, Rafael Messias Martins, Thomas Holgersson, Linnaeus University; Björn Wettermark, Uppsala University; Ylva Askfors, Hanna Justad, Region Stockholm
- IoT for ships – an untapped data resource
Applicants: Fredrik Ahlgren, Björn Pundars, Håkan Lundström (external)
- A platform to collect and analyze canoe/kayak training data, and produce motivational feedback to athletes
Applicants: Giangiacomo Bravo, Åsa Eklund, Anders Gerestrand, Ilir Jusufi, Susanne Linner, Anna Melin, Haris Pojskic
- User performance data from a video-based application/platform to enhance mobility and integrated learning in physical activities of daily living amongst older adults
Applicants: Sofia Backåberg, Larry Katz, Mirjam Ekstedt, Welf Löwe, Niklas Backåberg
Previous seed projects
- Analyzing state-of-the-practice for self-adaptive systems in industry using data analytics
Applicants: Nadeem Abbas, Danny Weyns, Ilir Jusufi and Bengt Larsson
- Digitized ancient remains detection using computer vision and artificial intelligence
Applicants: Peter Skoglund, Ludvig Papmehl-Dufay, Welf Löwe
- Vibration-based strength grading of sawn timber using piezoceramic transducers and one-dimensional convolutional neural networks
Applicants: Osama Abdeljaber, Anders Olsson and Welf Löwe
- Towards a data-driven approach to ground-fault location
Applicants: Mauro Caporuscio, Pieternella Cijvat, Hans Ottosson
- European spruce bark beetles; advanced predictive forecasting by means of machine learning
Applicants: Johan Bergh, Johan Hagelbäck, Björn Lundsten (Softwerk AB)
- Data-intensive tools for effective carbon mitigation in forestry
Applicants: Jorge Zapico, Rafael Martins, Johan Bergh
- Developing the Skeleton Avatar camera Technique (SAT) as a rapid, valid and sensitive measurement of mobility in elderly persons
Applicants: Cecilia Fagerström, Anders Halling, Linda Askenäs, Olof Björneld, Amanda Hellström, Mirjam Ekstedt
- Exploring data and establishing routines for collaboration on energy experiments
Applicants: Mike Farjam, Krushna Mahapatra, Giangiacomo Bravo
- An Exploration of the Challenges and Possibilities of Multidimensional Visualization in the Context of Visual Learning Analytics
Applicants: Rafael Martins, Marcelo Milrad, Italo Masiello
- Smart-Troubleshooting in the Connected Society
Applicants: Francesco Flammini, Welf Löwe, Shiyan Hu, Mauro Caporuscio, Morgan Ericsson, Narges Khakpour, Diego Perez-Palacin
- ODXVR x NTS: Exploring the Nordic Tweet Stream in Virtual Reality
Applicants: Aris Alissandrakis, Mikko Laitinen, Jukka Tyrkkö
The Linnaeus University Centre for Data Intensive Sciences and Applications embraces the following research groups.
AdaptWise The AdaptWise research group conducts research on the foundations and engineering of self-adaptive software systems. The primary focus is on: i) dynamic architectures and runtime mechanisms…
Computational Social Sciences The research in the area Computational Social Sciences within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) is about producing and…
Data Intensive Astroparticle Physics The research area Data Intensive Astroparticle Physics within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) works with the…
Data Intensive Digital Humanities The research area Data Intensive Digital Humanities within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) is a network that brings…
Data Intensive Software Technologies and Applications (DISTA) The research group Data Intensive Software Technologies and Applications studies data-driven approaches, such as machine learning,…
Deterministic and Stochastic Modelling The research field Deterministic and Stochastic Modelling within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) brings together…
E-health – Improved Data to and from Patients The research in the e-health area within Linnaeus University Centre for Data Intensive Sciences and Applications (DISA) will result in novel ways for…
Forestry, Wood and Building Technologies Within the research area Forestry, Wood and Building Technologies, the objective of Linnaeus University Centre for Data Intensive Sciences and Applications…
High-Performance Computing Center (HPCC) The High-Performance Computing Center (HPCC) offers computational and storage resources to help researchers to solve big computing and big data problems.…
Information and Software Visualization (ISOVIS) The research group Information and Software Visualization mainly focuses on the explorative analysis and visualization of large and complex information…
Smart Industry Group Smart Industry Group (SIG) is an interdisciplinary research group featuring expertise from computer science and mechanical engineering. SIG's focus is making production and…
Within DISA, several doctoral students are connected to our research groups. The doctoral students either focus on the foundational technologies or have a more thematic aim.
There is also a graduate school for industrial doctoral students in computer science connected to DISA: Data Intensive Applications (DIA). DIA focuses on applied research, addressing the big data and artificial intelligence challenges of our industry partners. The industry graduate school is funded by the Knowledge Foundation, Linnaeus University and the participating companies.
- Project on visualization awarded at international conference News
- Researchers create new calculation models for a more evidence-based debate about sustainability News
- New doctoral thesis on how to engineer intelligent, AI-based systems News
- Aladino presented at the Swedish Manufacturing R&D Cluster’s annual Cluster Conference News
Around thirty researchers from different disciplines at Linnaeus University constitute the critical mass within DISA. The scientists are divided into seven groups led by the following researchers.
- Andreas Kerren Professor
- +46 470-76 75 02
- Christian Engström Professor
- +46 470-70 84 61
- +46 70-216 99 42
- Danny Weyns Professor
- +46 470-76 75 48
- Evalill Nilsson Senior lecture and operational manager
- +46 480-44 60 01
- +46 73-037 79 13
- Giangiacomo Bravo Professor
- +46 470-70 87 82
- Johan Bergh Professor
- +46 470-76 75 42
- +46 70-292 25 25
- Lars Håkansson professor, head of department
- +46 470-70 83 50
- +46 73-338 57 12
- Mikko Laitinen Professor
- Morgan Ericsson Associate professor, head of department
- +46 470-76 78 72
- +46 72-594 17 48
- Welf Löwe Professor
- +46 470-70 84 95
- +46 76-760 36 62
- Yvonne Becherini Associate Professor
- +46 470-70 85 91
- +46 72-594 14 26