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Know-Center GmbH Know-Center GmbH - Österreichs Forschungszentrum für Data-driven Business und Big Data Analytics

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Contact Data

Coordinator

Independent legal entity

Year Established

2000

Location

Inffeldgasse 13/6, 8010, Graz (Austria)

Website

http://www.know-center.tugraz.at/

Social Media

Contact information

Paul Czech
pczech@know-center.at
+436642886298

Description

Description

Know-Center is Austria's leading research centre for data-driven business and big data analytics. As a connecting link between science and industry, Know-Center conducts application-oriented research in cooperation with other academic institutions and with companies. Within Know-Center, we pursue a wider perspective and approach data driven business as a cognitive computing challenge. Our scientific strategy is to integrate approaches from (big) data analytics with human-centred computing to create cognitive computing systems that will enable humans to utilise massive amounts of data. Therefore, our motto is “from data to intelligence”. Know Center is recognized Big Data European Innovation Space by the Big Data Value Association. Our data-driven methods and technologies contribute to value creation and benefits for customers in a sustainable way among various industries and use cases. Through our Cognitive Computing-based approach, which combines the strength of man and machine (=software), we are setting standards within both the local and the international research community. The best example for this is the area “Industry 4.0” (also known as “Smart Production”) where our approach makes companies more successful. Here, for instance, our Cognitive Computing Systems consist of integrated sensors in the production facilities, intelligent algorithms for data analysis and interactive systems that allow users to derive action-relevant knowledge and work more efficiently. Our customers benefit from this specific know-how in the form of competitive advantages and innovations directly at the value-creation chain. To support Austrian industry using Big Data methods and tools we established the Big Data Lab. The Big Data Lab is Austria’s first point of contact for all questions around Big Data Analytics and Big Data Management. The Big Data Lab enables companies to quickly and efficiently test data-driven methods as well as to assess the potential and possibilities for a data-driven business. Our offer includes consultations, data analysis and trainings.

Know-Center ist Österreichs führendes Forschungszentrum für data-driven busines und Big Data analytics. Als Verbindung zwischen Wissenschaft und Industrie führt das Know-Center in Zusammenarbeit mit anderen akademischen Institutionen und mit Unternehmen anwendungsorientierte Forschung durch. Innerhalb des Know-Centers verfolgen wir zukunftsweisende Perspektive und sehen data-driven Business als eine Herausfdorderung des Cognitive Computing. Unsere wissenschaftliche Strategie besteht darin, Ansätze von (großen) Datenanalysen mit Mensch-zentriertem Analysen zu integrieren, um kognitive Rechensysteme zu schaffen, die es Menschen ermöglichen, massive Datenmengen zu nutzen. Deshalb ist unser Motto "von Daten zu Intelligenz". Know Center ist von der Big Data Value Association alsBig Data European Innovation Space anerkannt. Unsere datengetriebenen Methoden und Technologien tragen in verschiedenen Branchen und Anwendungsfällen nachhaltig zur Wertschöpfung und zum Kundennutzen bei. Durch unseren Cognitive Computing Ansatz, der die Stärken von Mensch und Maschine (= Software) kombiniert, setzen wir in der lokalen sowie internationalen Forschungslandschaft Maßstäbe. Bestes Beispiel ist der Bereich Industrie 4.0 oder auf steirisch „smart production“, wo es uns darum geht, Unternehmen durch unseren neuen Ansatz erfolgreicher zu machen. Unsere Cognitive Computing Systeme bestehen hier zum Beispiel aus integrierter Sensorik in den produzierenden Anlagen, aus intelligenten Datenanalyse-Algorithmen und aus interaktiven Systemen die es BenutzerInnen ermöglichen, handlungsrelevantes Wissen abzuleiten und effizienter zu arbeiten. Unsere Kunden profitieren von diesem spezifischem Know-how in Form von Wettbewerbsvorteilen und Innovationen direkt an der Wertschöpfungskette. Zusätzlich bieten wir das Big Data Lab als Service an. Das Big Data Lab ist Österreichs erste Anlaufstelle für alle Fragestellungen rund um Big Data Analytics und Big Data Management. Das Big Data Lab ermöglicht Unternehmen die rasche und effiziente Erprobung datengetriebener Methoden und die Einschätzung der Potentiale und Möglichkeiten für ein Data-driven Business. Unser Angebot dazu umfasst Beratungen, die Durchführung von Datenanalysen und die Abhaltung von Trainings.

Link to national or regional initiatives for digitising industry

Our four research areas (Knowledge Discovery, Knowledge Visualization, Social Computing and Ubiquitous Personal Computing) are closely linked with our business areas (Industrial Data Analytics, Data-Driven Markets, Strategic Intelligence, Data-driven Process and Decision Support, Learning 4.0, Digital Life Science). Therefore, our services for industry are always linked to state of the art research. We are linked to the Austrian Industrie 4.0 initiative (http://plattformindustrie40.at/) and are part of production of the future ( http://www.ffg.at/produktion). We are also connected to the german stakeholders (http://lni40.de/).

Our Big Data competences around the cognitive computing approach together with our big internationals industrial networks supports companies of all sizes with digital industrial solutions.

Market and Services

Market sectors

  • Electricity, gas and water supply
  • Wholesale and retail trade
  • Transport, storage and communication
  • Real estate, renting and business activities
  • Public administration and defence
  • Education
  • Health and social work
  • Manufacture of textiles and textile products
  • Manufacture of wood and wood products
  • Manufacture of chemicals, chemical products and man-made fibres
  • Manufacture of rubber and plastic products
  • Manufacture of machinery and equipment
  • Manufacture of electrical and optical equipment
  • Manufacture of transport equipment
  • Financial intermediation

TRL Focus

  • TRL1 - Basic principles observed and reported
  • TRL2 - Technology concept and/or application formulated
  • TRL3 - Analytical and experimental critical function and/or characteristic proof of concept
  • TRL4 - Component and/or breadboard validation in laboratory environment
  • TRL5 - Component and/or breadboard validation in relevant environment
  • TRL6 - System/subsystem model or prototype demonstration in a relevant environment
  • TRL7 - System prototype demonstration in an operational environment
  • TRL8 - Actual system completed and qualified through test and demonstration

Services provided

  • Awareness creation
  • Ecosystem building, scouting, brokerage, networking
  • Collaborative Researchs
  • Concept validation and prototyping
  • Testing and validation
  • Commercial infrastructure
  • Incubator/accelerator support
  • Education and skills development

Service Examples

Ifolor AG is an online service provider, which offers personalized photo-products for customers
across Europe. Consumers upload their digital images to the Ifolor platform where
they create and order personalized photo-products like photo-books, photo-calenders or
other gifts. That platform has been designed for web and mobile devices and is developed
by Ifolor. The platform processes around 300 million digital images annually.
Ifolor is interested in understanding the users behaviour when creating photo-calenders in
order to create new services that support the consumer in pre-selecting photos or even
fully automatically design personalized photo-calenders.
For this purpose a pipeline was created that processes purchases and the contained images.
The pipeline automatically extracts all relevant information from a purchase and extracts
image metadata (EXIF) and basic image features like colour layout and edge histogram.
The automatic assignment of digital images to a month of a photo-calendar yielded an accuracy
of approximately 27% while a quarterly assignment resulted in an accuracy of approx.
60%. Both were much better results than a random assignment. A web based prototype was
implemented using the Naive Bayes algorithm due to its fast computation time.

Christoph Funke
christoph.funke@ifolor.ch
+41 71 686 59 66


Detego (formely Enso Detego) develops and distributes highly innovative software products
for the fashion retail industry. The company was founded in 2011 and is headquartered in
Graz/Austria, with offices in London/UK. Detego’s software suite provides real-time analytics
and merchandise visibility on item-level, enabling fashion retailers a digital transformation
without the need to replace their existing technology stack.
Detego supports fashion retailers in optimizing store processes and daily operations. In cooperation
with the Know-Center, a new component has been developed to create actionable
insights based on inventory movement and item sales. Target group of these recommendations
are both, sales stuff and store managers, but also managers in supply-chain
and procurement, e.g. Head of Retail or Merchandise Managers.

Michael Goller
m.goller@detego.com
+43 316 71 11 11 327


Porsche Holding Salzburg is the largest and most successful automotive distributor in Europe.
The Salzburg-based company was founded in 1947 and operates today in 22 countries
in Western and South-eastern Europe, as well as in China, Colombia and Chile. Its subsidiary
Porsche Austria GmbH is importing and distributing cars to dealers and customers
across Austria.
Together with the Know-Center, Porsche Austria is interested in analyzing the quality of data
from the market introduction and the market performance of new car models in the past
in order to create a forecast. These models are then used to forecast upcoming market performance
in terms of new car registrations or sales. This is of interest for current car models,
but even more for upcoming new models.
The project aimed at forecasting the demand on the number of cars of a specific brand
overall or within a dedicated segment. A predictive model forecasts the demand for a period
of a month up to one year. The decision on the model is based on an evaluation of a
non-linear approach from the research field of Deep Learning and a linear approach (Seasonal
Autoregressive Integrated Moving Average, SARIMA). The linear model yielded the
most promising results that hold true for both short-term and long-term demand forecasts.

Ing. Bernhard Friedl
bernhard.friedl@porsche.co.at
Louise-Piech-Strasse 2
Salzburg 5020
Austria

Organization

Organizational form

(part of) Public organization (part of RTO, or university)

Turnover

>5.000.000

Number of employees

50-100

Evolutionary Stage

Fully operational

Geographical Scope

National

Funding

  • Horizon 2020
  • National basic research funding
  • National specific innovation funding
  • Regional funding

Customers

Number of customers annually

26-50

Type of customers

  • Start-up companies
  • SMEs (<250 employees)
  • MidCaps (between €2-10 billion turnover)
  • Large companies, multi-nationals

Partners

MeisterLabs


BDVA


HumanTechnology


University Passau


University Graz (Karl-Franzens-Universität Graz)

Partner Type

University

Website

http://www.uni-graz.at/


Unycom


BMWFW


SFG


DND


Magna


Technical University Graz


Knapp


BMVIT


University Vienna


Bosch


ZBW


Siemens AG

Partner Type

Large enterprise


AutoCluster


ITC


ADV


PlattformIndustrie4.0

Technological competences

  • Micro and nano electronics, smart system integration
  • Sensors, actuators, MEMS, NEMS, RF
  • Photonics, electronic and optical functional materials
  • Cyber physical systems (e.g. embedded systems)
  • Robotics and autonomous systems
  • Internet of Things (e.g. connected devices, sensors and actuators networks)
  • Artificial Intelligence and cognitive systems
  • Location based technologies (e.g. GPS, GIS, in-house localization)
  • Interaction technologies (e.g. human-machine Interaction, motion recognition and language technologies)
  • Cyber security (including biometrics)
  • Data mining, big data, database management
  • Augmented and virtual reality, visualization
  • Simulation and modelling
  • Software as a service and service architectures
  • ICT management, logistics and business systems
Last updated: 03/09/18 07:55