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.
About the conference
During the two days longer talks with an academic or an industry focus will be mixed with poster mingles. We invite everyone who has an interest in Big Data and data intensive applications to attend the BigData 2020! Just as previous years, all the presentations will be held in English.
You can read more about the speakers and their presentations under "Conference Speakers".
09:00 Login and Testing
09:30 Welcome! Conference Introduction
09:45 Keynote 1: Erik Willén: Big Data applications in Forestry
11:00 Johan Thor, Södra: Identifying bark beetle infested spruces from space
11:30 Magnus Persson, Angelos Chatzimparmpas, and Nico Reski (The DISA PhD Talks): Interdisciplinary Exploration of Forestry Data Using Machine Learning and Immersive Visualization
13:30 Keynote 2: Håkan Olsson: Remote Sensing provides Big Data for assessment of our forest resources
14:15 Anna-Lena Axelsson: The Forest Data Lab – data factory and platform for co-creation and data-driven innovation
Fast forward session
15.00 Presentation of the session by the moderator
15.10 (New ideas)
- Applying deep learning on the complex geometry of the ALTO/COMET observatory by Gasper Kukec Mezek and Tomas Bylund, PhD-student
- Multiple Embeddings for Multivariate Network Analysis by Daniel Witschard PhD student
- Securely managing dataflows in an enterprise context by Lars Magnusson, PhD
- Research information effectivity measure by Olle Björneld, PhD
- Xtreaming: an incremental multidimensional projection technique and its application to streaming data by Rafael Messias Martins, Senior lecturer
- An experiment on the effect of polls and partisan-motivated reasoning on votes and the determination to vote by Mike Farjam, assistant senior lecturer
- Metrics for Anti-Pattern Detection in Time Series using Dynamic Time Warping by Sebastian Hönel, PhD
- Signal Extraction using Machine Learning for the ALTO observatory by Mohanraj Senniappan, PhD
- Progressive Multidimensional Projections: A Process Model based on Vector Quantization by Rafael Messias Martins, Senior lecturer
- Using community evolution tracking and word2vector techniques to analyse polarisation in dynamic discussion networks by Victoria Yantseva PhD, Elizaveta Kopacheva, PhD
16.40 Wrap up of the session
16.50 Closing Remarks
08:30 Login and Testing
09:00 Welcome Conference Introduction and Practical Info
09:15 Keynote 3: Anders Arpteg: How will the recent AI-revolution change our society?
10:25 Presentation of the DISA group session
10.30-12.30 DISA group presentations (10' per group):
- 10.30 Computational Social Sciences @DISA 2020: highlights of the year
Giangiacomo Bravo, Professor Social Sciences (https://lnu.se/en/research/searchresearch/computational-social-sciences/)
- 10.40 Gamma-Ray Astronomy at DISA. Yvonne Becherini, Associate Professor Astrophysics
- 10.50 DISA Digital Humanities – new answers to old questions. Mikko Laitinen, Professor of English Linguistics. (https://lnu.se/en/staff/mikko.laitinen/)
Short break (5-10 min)
- 11.10 Aims, Progress, and Preliminary Results of Visual Analytics Research at DISA. Andreas Kerren, Professor Computer Science
- 11.20 Research on eHealth at Linnaeus University – improving data to and from patients. Tora Hammar, Senior Lecturer eHealth or Evalill Nilsson, Senior Lecturer (https://lnu.se/en/research/searchresearch/ehealth--improved-data-to-and-from-patients/)
- 11.30 Advances with forestry, wood and building technology. Johan Bergh, Professor, Forestry and Wood Technology
- 11.40 Data-driven software quality - Year in review. Morgan Ericsson, Associate Professor Computer Science (https://lnu.se/en/research/searchresearch/data-driven-software-and-information-quality/)
Short break (5-10 min)
- 12.00 Adaptwise. Danny Weyns, Professor Computer Science
- 12.10 Deterministic and Stochastic Modelling. Christian Engström, Professor Mathematics
- 12.20 Smart Industry Group. Mauro Caporuscio, Associate Professor Computer Science
13:30 Keynote 4: Virginia Digum: Responsible AI: from principles to action
14:15 DIA Industry Graduate School Welf Löwe
14:30 Presentation of Student Papers
- Towards a Data-Driven Approach to Ground-Fault Location in Distribution Power System, Antoine Dupuis, student in the Renewable Electrical Master Program
14.45 Closing Remarks Welf Löwe
Anders Arpteg: How will the recent AI-revolution change our society?
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.
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
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.
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
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.
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
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.
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
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!
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
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.
Erik Willén, is Process Manager at Skogforsk, Uppsala, Sweden
2020 DISA PhD Talks:
Interdisciplinary Exploration of Forestry Data Using Machine Learning and Immersive Visualization
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.
Call for presentations!
A fast-forward (FF) + virtual poster (VP) sessions will be organized as part of the Big Data Conference 2020. In the FF presentations, each participant gets to show a 3-minute video to briefly summarize her/his research. Directly after the FF, (a few at the time) participants will be redirected to breakout rooms where it will be possible to present their VP and interact with the interested public. There will be a few rounds with set-up during the first conference day (December 3).
The FF+VP presentations can focus on either ongoing research or new ideas:
1) Ongoing research will focus on research recently published or at an advanced stage of elaboration. The main goal here is to present research results of general interest for the public of the conference and eventually receive feedback on ongoing work.
2) New ideas will focus on future research, plans, or simply new ideas. The goal here is to share with the public their own plans, receive feedback, find partners and possibly find synergies to develop future research together.
To submit to the FF+VP session, participants should submit a 500-word abstract briefly presenting the research by November 9th, 2020 to Diana Unander, firstname.lastname@example.org Each participant can submit at most two abstracts.
Acceptance information will be sent out by November 13th, 2020.
If accepted, a video (in videos in 720p and mp4 format) of maximum 3 minutes should be sent by November 24th, 2020.
For more information or questions, please contact:
- Ilir Jusufi – email@example.com
- Rafael Messias Martins – firstname.lastname@example.org
- Johan Bergh – email@example.com
- Romain Herault – firstname.lastname@example.org (related to the video)
The Big Data Conference is free of charge!
Last day to register was December 1st!
A "digital conference" - how does that work?
A "digital conference" - how does that work?
The entire conference will use the e-meeting platform Zoom. In order to participate, please read the following and see further below for instructions of how to connect and install the Zoom client - we strongly recommend everybody to do that because it will give you much better technical quality.
Links to the sessions will be provided to all registered participants shortly before the conference starts.
Connecting to Zoom
If you do not already have the Zoom client installed on your computer, you will need to make the following steps to install and configure Zoom:
- Download the Zoom.us software on the device which you will use for the video conference (Windows, macOS, Android or iOS)
- Test the internet connection and the audio system (microphone + headphones/ speakers) and video (webcam). You can click here to test a Zoom conference meeting.
Steps for the actual video conference:
- Accessing the video conferencing link, in the form of https://zoom.us/j/xxxxxxxxxx, which you will find for each session. This will open the already installed application.
- The authentication in the video conference is done with the email and password previously received from the conference administration.
General recommendations for using Zoom
- Write your name and institution - eg. John Doe - University of Everywhere. In order to see how to do this please read this.
- Keep the microphone turned off when you are not speaking, since background noise can be very distracting.
- In order to talk with the moderators and other speakers try using the chat. Find instructions here.
- In order to share your screen watch this short tutorial.
- During a zoom conference you can give more non-verbal feedback - by raising your hand to ask for permission to speak, or by answering yes / no, etc. To see where you can access them, look at the explanatory images here.
For presenters (papers/key notes) - some tips for better technical quality in recordings
- Set your video resolution to 1920x1080. If you use a mobile phone to record, record in landscape (horizontal) format.
- Use a neutral background and record in good light.
- Place yourself slightly to the left or right of the centre of the frame, and make sure not to have too much air above your head.
- Place your camera at the same level as your head.
- Preferably, use a wired lavalier microphone plugged into your computer or phone. In case you do not have access to a lavalier, use a high-quality USB microphone or a high-quality phone headset. Try to avoid large headsets, as these do not look good on video.
- Avoid using a room witch echo or other disturbing sounds.
- Preferably, do not use a virtual background. In case you record in Zoom with a lit green screen behind you, it is ok to use a virtual background.
- Choose mp4 as your file format
Previous Big Data Events
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).