iot 2014 value creation workshop: sdil

KIT – University of the State of Baden-Wuerttemberg and National Research Center of the Helmholtz Association www.kit.edu

Dr. Till Riedel, Prof. Dr.-Ing. Michael Beigl – Department of Informatics

can data be smart?Accelerating Data driven Innovation with a Smart Data Innovation Lab (SDIL)

2

Karlsruhe Institute of Technology

Employees

364Professors

Students

789Annual Budget in Million Euros

9,261 23,836A merger of the University of Karlsruhe (est. 1825) and the Karlsruhe Research Center

3Nobel Laureates

3

Computer Science at KIT

Scientific Staff

41

Professors gained statusfrom KIT‘s CS faculty

Students

19721st CS department in Germany

250 2700Computer Science and applied CS

#1Computer Science Ratings, DFG Funds

190

Professors

> 900 PhDs

4 Smart Data Innovation Lab. Michael Beigl. teco.kit.edu

Why Big Data Matters:Dimension of Convergence

Location Uncertainty vs. GPS Sampling RatePaek, J., Kim, J., Govindan, R.: Energy-efficient rate-adaptive GPS-based positioning for smartphones. In: Proc. of the 8th Intl. Conf. on Mobile systems applications and services MobiSys 10, MobiSys ’10, p. 299ff. ACM, ACM Press (2010)

Krijger, J. M., van Weele, M., Aben, I., and Frey, R.: Technical Note: The effect of sensor resolution on the number of cloud-free observations from space, Atmos. Chem. Phys., 7, 2881-2891

Information

Reality

TimeFrequencyDelay

Location

Perception# PhenomenaResolutionError


Internet of Things and Services

/Services

CRM PLMSRM

/Things

SCM EHMPLMERPLeg-acy

A2A

People

collaboration

B2B

roles embeddedanalytics

alerts

roles

SmartItems

Middleware

Internetof Things

MeaningfulPresentation

Information

Reality


Smart Economy: Data, the “new oil”

What are the ramifications for Germany and Europe? Traditionally home of engineers.Engineering needs to be extended to also accommodate “Digital Data Engineering”.

real-time processing of large data quantities (“Big Data”). Structuring Big Data results in information (“Smart Data”)

leads to knowledge advantages can be used to support decision-making processes.


The Smart Data Innovation Lab(throwing oil onto the fire)

Data SourcesIndustrial, Research,

Government, Open Data

Smart Data Innovation Lab

Knowledge and Innovation(Analysis results, prognosis,Online-Analysis Systems)

(Fast) Research and

Development

Systems,Analytics,Researchbased on

open, proprietary

SDIL internalKnowledge

Generated Data

Code Artefacts

SelectedResults

„new oil“


Our Goals

A Smart Data Centre and a Smart Data CommunityPrompt Co-Working on valuable Problems with valuable „Big Data“ Requires Structure (SDIL Orga) and Trust (SDIL Contract)Knowledge Transfer from Research to Industry and vice versaExploration of

Smart Data Potential / Innovation PotentialBest Practice and Standards

Research in Analytics, Systems, Application Domain specificSmart Data Tools, Support, Management, Privacy, Legal and CurationHCI and Usability

First focus: short term high impact projects


Smart Data: From Data to Wisdom

Information makes data meaningful for audiences because it requires the creation of relationships and patterns between data.

Source: Nathan Shedroff, nathan.com

Transforming data into information is accomplished by organizing it into a meaningful form, presenting it in meaningful and appropriate ways, and communicating the context around it.


Context Sensitive Systems w/ Predictive AnalyticsPlanning, Control, Real Time Reaction

Massive Ad-hoc Deployment of CPS-Systems,

Recognition of Process related

parameters

Automatic Correlation to

find novel insights

Use of the data for planning, controlling processes


Meaningful Data in Context: Realtime Smart Data in Maintenance

L1A10 Temp

L1B22 Temp

L1B20 Temp

L3A10 Temp

L1A10 Temp

teco.kit.edu


SDIL Project Phases

Phase: Information• Industry and research partners search partners and their competence focus

through the SDIL database

Phase: Project Definition• Data Access / Result Model Selection, Funding & Contract Model• Research and Innovation Question and Results (Data, Algorithm, System)• Technical Details including Data and Service Interfaces

Project Proposal Phase• Proposal handed into SDIL Community• In case of go: Preparing Operation

Phase: Analysis• Prepare Data, Compute, Interpret Data and/or develop analytical method or

system• Publish Results according to Data Model

Continuation Phase• Prepare for follow up actions or development of a run time system• Care of Data Life Cycle according to contract


3 Data Access / Data Results Models (planned)

Open DataOpen to the public

SDIL community open dataOpen to organisations who signed the contract and agreed to the terms and conditions of the contractRequired for restricted access data (IP-Knowledge, data protection)

SDIL P2P dataOpen to two or more partners in SDIL bound to a general NDA which includes handling rules for ethics and privacy

Mixed dataFair share: Same amount of input (e.g. percentage of Open Data Input) and output (e.g. same amount of Open Data Output)

Same approach for algorithms


Governance & Communities

Strategy Board

Operational Board

SDIL-Coordinator and Deputy (Michael Beigl, Laure Le Bars)

Innovation CommunitiesP

rojects

Repo

sito

ry

Central Storage

RemoteData Source Catalogue, Broker

HANATerra-cotta Azure ? 9000

…HAL

Generic Tools, Data CurationSupp

ort

Data Curation(Lead:DFKI, FhG) SDIL Platform

Industry 4.0 (Lead: Bosch, DFKI)

Energy (Lead:EnBW, KIT)

Smart Cities (Lead:Siemens, FhG)

Medicine (Lead:Bayer, FZJ)


Further Activities and Services of SDIL (soon)

Community ForumsWorkshops, CompetitionConsulting & SupportToolsEducation

Contact us:http://www.sdil.de/en/contact/Prof. Michael Beigl ([email protected]) (SDIL Coordinator)


Bytecode

Till Riedel, Big With Data, Paris, 2014-06-12

?

iot 2014 value creation workshop: sdil

Science

results data

data meaningful

meaningful data

data andor

realtime smart data

com9 smart data innovation

goalsa smart data centre

big data matters