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 eHealth, 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. The seed-project must lead to an application for external funding.
During 2020, there is SEK 800 000 in total available for seed funding.
Prerequisites and evaluation criteria
The project consortium should consist of one or more researches from DISA collaborating closely with other researchers, 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 succeed with an application for external funding within the project time.
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
- Vibration-based strength grading of sawn timber using piezoceramic transducers and one-dimensional convolutional neural networks
Applicants: Osama Abdeljaber, Anders Olsson and Welf Löwe
- 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
- 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.
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-driven Software and Information Quality Within the research area Data-driven Software and Information Quality, the objective of Linnaeus University Centre for Data Intensive Sciences and…
eHealth – Improved Data to and from Patients The research in the eHealth 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.…
Visual Analytics for Engineering Smarter Systems (VAESS) Visual Analytics for Engineering Smarter Systems (VAESS) is a research area within the Linnaeus University Centre for Data Intensive Sciences…
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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
- Giangiacomo Bravo Professor
- Johan Bergh Professor, pro-dean
- Marcelo Milrad Professor
- Mikko Laitinen Professor
- Morgan Ericsson Associate professor
- Sabri Pllana Universitetslektor
- Tora Hammar Universitetslektor
- Welf Löwe Professor
- Yvonne Becherini Associate Professor