2017 welf disa@lnu-intro v1 - gxu.edu.cn...disa a calculus of culture | circumventing the black box...
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DISA
A Calculus of Culture | Circumventing the Black Box of Culture Analytics, Nanning, 21-22 March 2017
Koraljka Golub, [email protected] on presentation by Welf Löwe, [email protected]
Linnaeus University Center of Excellence for Data Intensive Sciences and Applications
https://lnu.se/disa
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Big Data, Information, and Knowledge
Big Data: Analyzing data sets and streams to gain knowledge about technical, scientific, sociological or economical phenomena.
• Data: symbols, signals, bits & bytes, words, numbers, tokens…
• Information: data interpreted in a context, i.e. meaning
• Knowledge: actionable information, i.e. insights allow for controlling processes and giving predictions
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Creating knowledge from data: Collaborative effortCredit: EU CROS portal
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What is “Big” today and tomorrow?
• Challenging quantities that go beyond the capability of humans and commonly used software tools • A constantly moving target• Ranging from a few dozen terabytes (1012) to many petabytes (1015)
today
• Challenging qualities, as data come in varying and complex formats, consisting of all types of structured and unstructured data
• My computer has ½ terabyte = 512 gigabytes of disk space= 1 year of music, 20 days of video, 150,000 photos, 10 days of movies
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Turn data into knowledge to create value Credit: PLOS Biology, 7 July 2015Projection for 2025, 1 petabyte = 1024 terabytes
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Big Data – profile of LNU
• DISA@LNU:- Multidisciplinary fundamental and applied Big Data research - Linnaeus University Center (ca 70 MSEK from LNU alone until 2021)
• DISA@IEC: - Applied Big Data research and innovation with industry- IEC is an ICT cluster organizing collaborations of academia and industry
(ca 6 MSEK from EU, LNU, Regions of Kalmar and Kronoberg, Tungafordon, TEC until 2018)
• iSchools: - Effort in Big Data related courses and education programs
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IT Core – Foundations and Technologies
Transforming Big Data to Information to Knowledge• Signal processing: signal analysis and theories with application to direct and
inverse problems• Statistical analysis: collection, analysis, interpretation, presentation, and
organization of (sparse, high-dimensional) data• Machine learning: classification, estimation, prediction based on data• Visual analytics: analytical reasoning about data facilitated by interactive visual
interfaces
Coping with variety, velocity, and volume of Big Data • Composition, adaptation: building systems from (adapted) components• Self-adaptation: let systems adapt based on observations in its state and
environment• Future Internet: the Internet as a distributed, mobile data collection and
computing platform (Cloud Computing, Internet of Things)• Parallel & high-performance computing: scale with data processing and storage
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Big Data Application Areas
1. Astrophysics
2. Wood and Building Technologies
3. Engineering of Smarter Systems
4. Software and Information Quality
5. Digital Humanities: English Linguistics, Media & Journalism, Library and Information Science
6. Computational Social Sciences
7. eHealth
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eHealth: Improving our health systems
What if we could gain actionable knowledge from all European health registers?
Credit: BigApple Horizon 2020 proposal.
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Accelerating DNA analysis
What if we could …• Reduce time for pediatricians to scan and analyze
the entire genome of a critically ill infant? • Explore differences and similarities of all
organisms and their evolutionary relationship?
GenBank dataset• 188’372’017 DNA sequences (Oct 2015)• One human DNA sequence ~3 gigabytes
Our DNA sequence analysis application* • Finds patterns in large-scale DNA sequences• Speedup 10x compared to baseline on regular PC
Credit: http://www.biol.unt.edu/
* Suejb Memeti, Sabri Pllana: Accelerating DNA Sequence Analysis using Intel Xeon Phi, ISPA 2015 IEEE.
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What if we could… • Analyze for instance what people in Sweden talk about in public?• Explore the relationship between language and thought – public sentiment,
consumer trends, opinions, …• Look in real-time through a window to the world
The Nordic Twitter Stream initiative• A robot to monitor geocoded Tweet stream in five Nordic countries• Strict ethical guidelines: focus on macro-level patterns – not individuals• Text and data mining tools to analyze big and complex data sets• User-generated content – what do we talk about on a really big scale?• A consortium of linguists and computer scientists
The Nordic Tweet Stream initiative (NTS)
Understanding language
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Applications inEngineering,
Sciences & Humanities
IT Core
Self-adaptationVisual analytics
Distributed ComputingFuture Internet
Parallel & high-performance computingSignal processingStatistical analysisMachine learning
Composition & adaptation
Astrophysics
Wood/BuildingTechnologies
Software& InfoQuality
Media &Journalism
EnglishLinguistics
eHealth
Comput.Social
Sciences
Library &Info Science
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Ongoing Big Data collaborations
Collaboration with industry• Common research projects Atlas Copco, Ericsson, IBM, Intel, Meltwater,
NVIDIA, Sigma Technology, Telia, Vattenfall, Yaskawa, …• Interests across industriesCollaboration with branch organization • IT industry: IEC, SwedSoft• Building and construction: Smart Housing Småland, GodaHus• Heavy vehicle industry: Tunga fordon• Manufacturing: LTC, TECCollaboration with public sector • Active project involvement of and financial support from the regional municipalities• eHälsomyndigheten established in Kalmar much due to the activities at the eHealth
Institute• Collaboration with Stralsakerhetsmyndigheten
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New Big Data collaborations
• Offer towards industry, the public sector, and interested LNU researches• Various research competences that we can contribute with • Many ways of collaboration
- High-Performance Computing Center- Data and Text Streaming Platform (social media and web data) - Thesis and seed projects- Digitalization courses and seminars for industry (with IKEA)- Development of and contribution to educational programs - Workshops for developing realistic research and innovation projects with
external funding- Research and innovation projects together with LNU- …
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High-Performance Computing Center (HPCC)
• The HPCC will be a high- performance computing platform providing advanced computing and storage infrastructure and knowledgeable scientific and technical staff.
• It will provide services to scientists and to the regional industry.• The platform complements the large-scale computing and storage
infrastructures that are available at the national level, e.g., the Swedish National Infrastructure for Computing (SNIC).
• Core exists: cluster with 20 servers, two accelerated single-node systems; suitable for experimentation with limited-size problems.
• DISA invests ca. 3 MSEK, but more funding will be needed
• Contact [email protected]
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Thesis and Seed projects
• Collaborative innovation and research in Big Data with Master’s and PhD students and senior researchers involved
• Explore ideas and jump start collaboration projects• Multidisciplinary collaboration between industry, the public sector and LNU• Short start up time, 3-6 month activities, budget of max 200 KSEK• Why
– Idea testing and prototyping– Explorative study– Get in contact with students as (future) customers – Get in contact with teachers as part of the marketing strategy– Assessment of students for hiring– IT support for internal development and innovation- Pilot for a larger research project
• Contact [email protected]
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Research and innovation projects together with LNU • Requirements as for seed projects (multidisciplinary or/and industry-academia)• Longer planning and decision time (ca. 1 year) • Longer project time (3-5 years), • Higher funding (3-30 MSEK) but usually in-kind contributions required• Why
- LNU: keep or get back control over your research subject when there is a paradise shift towards data-driven scientific approaches
- Industry: do not miss benefitting from the data you have access to and getting necessary R&D resources for free
• Contact [email protected]