Big Data Conference

Welcome to our 3rd annual Big Data Conference at Linnaeus University.

The conference this year's host for the conference is Linnaeus University Centre for Data Intensive Sciences and Applications (DISA). We have invited researchers from our own Centre to present some of the work that has taken place within DISA this past year and Keynote and invited talks from other universities and partners.

When? Friday December 1st 2017 9.30-16.15

Where? Linnaeus University, Building: N, Room: IKEA, Växjö

About the conference

About the conference

On Friday December 1st the conference opens with Coffee and registration, poster mingle in the open area of building N. During the day longer talks with an academic focus will be mixed with poster mingles during meals. We invite everyone that has an interest in Big Data and data intensive applications. The presentations during the conference will be held in English.

The conference is free of charge, but if you register and don't show up you will be charged a fee that covers food etc.



9.30 – 10.00 Coffee and registration, poster mingle in the open area of building N

10.00 -10.10 Welcome and practical information, Mikko Laitinen

10.10 – 10.30 Opening speech

10.30 – 11.30 Invited talk: When a Few Data Points are Not Enough: On the Emergence of Analytics in Culture Research Kristoffer Laigaard Nielbo, University of Southern Denmark, Denmark.

11.30 – 12.30 Showcasing DISA - results Chair: Andreas Kerren

12.30 – 14.00 Lunch and poster mingle.

14.00 – 15.00 "BigData@BTH - Establishing a Data Science Research Environment" Håkan Grahn, Professor of Computer Engineering at Blekinge Institute of Technology

15.00-16.00 Invited talk:

16.00 – 16.10 Closing remark – future plans for DISA – Welf Löwe.

16.10 -> Grab and go coffee and chance to mingle

Conference speakers

Conference speakers

Kristoffer Laigaard Nielbo, datakuben @ Department of History, University of Southern Denmark, Denmark.

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"When a Few Data Points are Not Enough: On the Emergence of Analytics in Culture Research"

Digitization and digital media have generated a rapid proliferation of data that is unprecedented in the history of man. This data deluge is transforming knowledge discovery and understanding in every domain of human inquiry. Large-scale computing and data-intensive methods have therefore gained acceptence in most research domains. With a preference for myopic and qualitative approaches to cultural heritage, culture researchers do in many ways represent the anti-thesis of this development. We insist on manually scrutinizing small sets of cultural expressions and mentally synthesizing our results. A \Culture Analytics" is however emerging as domain experts in history, language, and literature are starting to utilize computation and digital data to test well-established theories and nd new cultural patterns. While the need for high performancing computing is still quite limited, culture analytics is changing the scale and scope of multiple disciplines in the social sciences and humanities. This talk will outline the emerging research eld of culture analytics with examples from historical, literary and ethnographic research. For culture analytics to prosper, it is necessary to establish lasting collaborations between culture researchers and the computational sciences grounded in mutual interest and understanding. We argue that culture analytics can contribute with valuable domain expertise and a human perspective in data-driven research.

Biography KLN is associate professor of humanities computing with specialization in tools for analysis and interpretation of cultural data. He has participated in a range of collaborative and interdisciplinary research projects involving researchers from the humanities, social sciences, health science, and natural sciences. His research covers two broad areas: automated text analysis and modeling of cultural behavior. Both areas explore the cultural information space in new and innovative ways by combining cultural data and humanities theories with statistics, computer algorithms, and visualization.

Andreas Kerren, professor, Department of Computer Science, Linnaeus University

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"Initial research findings of the LNUC DISA"

Description: In this session, academically outstanding, previously published work of the various DISA research areas will be presented. For this, four selected talks will pinpoint recent scientific contributions in the fields of data-intensive sciences and applications. 


Håkan Grahn, Professor of Computer Engineering at Blekinge Institute of Technology Data

"Establishing a Data Science Research Environment"

Håkan Grahn will be generated at an ever-increasing rate for the foreseeable future. Added value and cost savings can be obtained by analyzing big data streams. The analysis of large data sets requires scalable and high-performance computer systems. In order to stay competitive and to reduce consumption of energy and other resources, the next generation systems for scalable big data analytics need to be more resource-efficient. The research project BigData@BTH - Scalable resource-efficient systems for big data analytics, combines expertise in machine learning, data mining, and computer engineering to advance the knowledge in the domain. The goal is to establish a long-term sustainable research environment, and the value of it will be demonstrated and evaluated mainly in two application areas (decision support systems and image processing).

For more information about Big Data.

The research interests by Prof. Grahn are in the intersection of parallel computing and data science. Traditionally has accuracy been the main objective in machine learning, but we address also aspects such as execution time and energy consumption. Most of our research is done in close collaboration with industrial partners. Currently, he is heading a 6-year research effort on big data analytics, BigData@BTH.

Fabrice Rossi, Professor of applied mathematics at University Paris 1 Panthéon Sorbonne



Fabrice Rossi is a member of the SAMM laboratory. He leads a research team on statistical learning, statistics and networks, with nine permanent researchers and seven PhD students. He specializes on exploratory data analysis with a special interest in graph data, change detection and visual data exploration. More generally, his research covers numerous important themes of machine learning including large scale data processing, feature selection, learning theory and clustering.

Fabrice Rossi works frequently with researchers from other fields, especially from the humanities, including archaeology, history and sociology. In 2017, he was guest editor of a special issue on humanities and statistics of the main French statistics journal. He has (co)-authored more than 150 articles in journals and conference proceedings.



The conference is free of charge, but if you register and don't show up you will be charged a fee that covers food etc.

You can now register for the conference by clicking on the registration link below. Register here.



We have pre-booked rooms at the hotels listed below. Please, call or email the hotel directly and mention the booking code "DISA2017" when you book to get our special price. Note: The pre-booked rooms can not be reserved on-line on the hotels own website or through an on-line third party wholesaler.

Elite Stadshotellet Växjö (Single room from 936 SEK/night)

Kungsgatan 6, Box 198 SE-352 33 VÄXJÖ

Book this hotel via or tele +46/470–134 00


Elite Park Hotel (single room from 913 SEK/night)

Västra Esplanaden 10-14 Box 434 SE-351 06 VÄXJÖ

Book this hotel via or tele +46/470–70 22 00


Clarion Collection Hotel Cardinal (single room from 1110 SEK/night) Bäckgatan 10 SE-352 30 VÄXJÖ

Book this hotel via email or tele +46/470–72 28 00


Quality Hotel Royal Corner (single room from 845 SEK/night)

Liedbergsgatan 11 SE-352 32 VÄXJÖ

Book this hotel via: or tele +46/470–70 10 00


Teleborg Castle (single room from 940 SEK/night)

Slottsallén SE-351 96 VÄXJÖ

Book this hotel via: or tele +46/470–34 89 80

Finding your way to the conference

Finding your way to the conference

 The conference will be held in buildings N on campus, which is located roughly 3 km from Växjö's city centre.

To get to the university, you can either walk along the lakes or travel by bus. On the links below you will find a map of Växjö, for those who prefer to walk, and a bus timetable, for those who wish to travel by bus. Bus number 3 departs from Resecentrum to Linnaeus University every tenth minute during daytime. You will also find a map of campus.

Map of Växjö

Map of campus (page 2 in English)

There are regular departures between Småland Airport and Bromma Airport in Stockholm. The airport is located roughly 4 km from the city centre, which is reached either by taxi or the airport bus that leaves every 20 minutes.

Växjö has good train connections. The train station is located in the city centre.




Questions concerning the content of the conference should be sent to Diana Unander Nordle, Linnaeus University.

For practical questions concerning hotel, transport, etc., email