Big Data 2020
Welcome to the 6th annual Big Data Conference at Linnaeus University, in Växjö, Sweden.
The host will of course be Linnaeus University Centre for Data Intensive Sciences and Applications (DISA), but please note that this year's conference will - of course! - be an entirely digital event held online! During the conference days you will meet invited speakers from other universities and industry, learn about results and ongoing research within DISA.
Most of the lectures and presentations were recorded - use this link to see them again!
Conference speakers
Anders Arpteg: How will the recent AI-revolution change our society?
Abstract
Something extraordinary has happened within AI in recent years. Companies are starting to talk about moving into an AI-first future, but what does that mean? Not only are we seeing significant scientific advances in AI, but we are also seeing companies and politicians starting to invest heavily in AI. In order to stay one step ahead, we must be prepared for what is coming next. What has really happened in recent years, and what are the next steps and trends in machine learning? What should companies know to be prepared for the rapid development that is happening with ML and AI? This talk will give a glimpse into the future of AI, what possibilities it holds, and describe concrete real-world examples of how companies such as Spotify, Peltarion, and more are using the latest AI techniques.
Bio
Anders Arpteg (Ph.D., Head of Research at Peltarion) has been working with AI for 20 years in both academia and industry, with a Ph.D. in AI from Linköping University. Worked at Spotify for many years making use of big data and machine learning techniques to optimize the user experience. Now heading up a research team at Peltarion, operationalizing the latest and greatest AI techniques. At Peltarion, we have the ambitious goal of making deep learning and the latest AI techniques available for all companies, not just the large technology organizations. Also a member of AI Innovation of Sweden's steering committee, AI adviser for the Swedish government, member of the Swedish AI Agenda, member of the European AI Alliance, founder of the Machine Learning Stockholm meetup group, and member of several advisory boards.
Anna-Lena Axelsson: The Forest Data Lab – data factory and platform for co-creation and data-driven innovation
Abstract
The National Forest Data Lab is an open platform that promotes co-creation and data-driven innovation within the forest sector. The platform builds upon existing data, infrastructure and collaboration between two strong players within management, analysis and curation of forest related data; the Swedish Forest Agency and the Swedish University of Agricultural Sciences (SLU). The main users and collaborators are companies and public authorities but also academia and research institutes. The presentation will focus on a number of use cases that demonstrate the value of open data and services for data-driven innovation in the forest sector. The Lab also arrange seminars, networking and training events. Currently The Forest Data Lab participate in the new version of Hack for Sweden 365, which is an innovation competition related to public open data.
Bio
Anna-Lena Axelsson works with development of external collaboration and coordinates the forest environmental monitoring and assessment program at the Swedish University of Agricultural Sciences. She is one of the initiators of the National Forest Data Lab.
Virginia Dignum: Responsible AI: from principles to action
Abstract
Every day we see news about advances and the societal impact of AI. AI is changing the way we work, live and solve challenges but concerns about fairness, transparency or privacy are also growing. Ensuring an ethically aligned purpose is more than designing systems whose result can be trusted. It is about the way we design them, why we design them, and who is involved in designing them. If we are to produce responsible trustworthy AI, we need to work towards technical and socio-legal initiatives and solutions which provide concretise instructions, tools, and other means of dictating, helping, and educating AI practitioners at aligning their systems with our societies’ principles and values.
Bio
Virginia Dignum is Professor of Responsible Artificial Intelligence at Umeå University, Sweden and associated with the TU Delft in the Netherlands. She is the director of WASP-HS, the Wallenberg Program on Humanities and Society for AI, Autonomous Systems and Software. She is a Fellow of the European Artificial Intelligence Association (EURAI), a member of the European Commission High Level Expert Group on Artificial Intelligence, of the working group on Responsible AI of the Global Partnership on AI (GPAI), of the World Economic Forum’s Global Artificial Intelligence Council, of the Executive Committee of the IEEE Initiative on Ethically Alligned Design, and a founding member of ALLAI-NL, the Dutch AI Alliance. Her book “Responsible Artificial Intelligence: developing and using AI in a responsible way” was published by Springer-Nature in 2019.
Håkan Olsson: Remote Sensing provides Big Data for assessment of our forest resources
Abstract
There is an increasing stream of remote sensing data that together with digital techniques can be used for assessment of forest resources. Satellites provides frequent images that can be compared and used for forest damage assessment. Airborne laser scanners provide 3D point clouds that in combination with field surveyed reference data are used operationally for producing nationwide and accurate maps with data about the forest on raster cell level. The sensors develops rapidly and provides data with higher resolution, making assessments of single trees realistic. Among the current research frontiers are: combining single tree data from airborne sensors with stem shape data from sensors carried by man or vehicles; automated classification of tree species; assessment of forest growth from repeated sensor data acquisitions. The ultimate goal is to assimilate all new data into a continuously updated model of the forest resources.
Bio
Håkan Olsson is professor in forest remote sensing at the Swedish University of Agricultural sciences. He leads the data acquisition work package in the research programme Mistra Digital Forest. He is also a member in the steering group for the ongoing national laser scanning for forest resource assessment, and a member of the national council for geodata (Geodatarådet).
Johan Thor: Identifying bark beetle infested spruces from space
Abstract
Johan Thor will talk about how the small European bark beetle, less than half a centimetre long, gets visible from space via satellite images, or rather; its effects. The bark beetle infests and kills large amounts of spruces, not only in Sweden, to large economic amounts. Today, we have limited possible actions to take in order to prevent further infestation and he will describe how Södra teamed up with a Dutch startup in order to explore a new way to fight back!
Bio
Johan Thor is currently working as Head of data science at Södra. He has been for Södra for over 14 years where he have had several different focuses and positions. He has a master of science in applied physics from The Institute of Technology at Linköping University. At Södra Johan is involved in collaborations with academia, consultants and other partners and is a great inspiration for the students he meets.
Erik Willén: Big Data applications in Forestry
Abstract
Swedish forestry is using and producing vast amount of data for planning, during operations and transportation to the industry. The presentation focus on the enablers for digitalization in Swedish forestry and their current status. The most important data collection and processing as well as several applications in operational use and in applied R&D will be presented.
Bio
Erik Willén, is Process Manager at Skogforsk, Uppsala, Sweden
2020 DISA PhD Talks:
Interdisciplinary Exploration of Forestry Data Using Machine Learning and Immersive Visualization
Abstract:
The analysis of large multivariate data sets is a complex process, often requiring the involvement of expertise from diverse research areas in order to support decision-making. In this talk, we present and reflect upon early efforts toward an interdisciplinary collaboration with the aim of exploring forestry data using machine learning and immersive data exploration practices. We are particularly interested in analyzing standing volume from the Swedish National Forest Inventory (NFI) from a spatiotemporal perspective (per county in Sweden from 1955 to 2017).
On one hand, applying machine learning techniques allows us to predict future trends and developments. Additionally, error analysis goes beyond the data and provides further insights into the problem. On the other hand, immersive visualization enables an explorative analysis of the data, thus, empowering the analyst to discover patterns in an engaging and natural way. Identifying insights based on machine learning may guide the exploratory data analysis activity in the immersive environment, and vice versa. Consequently, a coherent workflow combining the strengths of different tools and practices can be valuable to both data analysts and domain experts.
Presenters
Magnus Persson
Angelos Chatzimparmpas
Nico Reski
Previous Big Data Events
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Big Data 2022
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Conference Big Data 2017
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Big Data Conferences The Big Data Conference is an annual event at Linnaeus University, arranged by the Linnaeus University Centre for Data Intensive Sciences and Applications (DISA).
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Conference Big Data 2016
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Conference Big Data Conference 2024All day
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Livestream and 12-Hour IoT & AI Adventure Dive into the Future: 12-Hour IoT & AI Adventure at Linnaeus University!