Was macht Big Data smart? Wie profitiert professionelles Daten Management von semantischen Technologien? Wie baut man auf einen Wissensgraphen ein Data Warehouse auf, das bessere Ergebnisse erzielt? Beispiele und Methoden werden erklärt.
Data Analytics und Machine Learning bei der SparkassengruppeADTELLIGENCE GmbH
Bei der Digital Konferenz The Future of AI & Big Data Analytics gibt Christian Damaschke, Geschäftsführer der Sparkasse Rating & Risikosysteme GmbH, einen Einblick über den Einsatz von Data Analytics und Machine Learning bei der Sparkassengruppe.
Christian Damaschke ist seit 2018 Mitglied in der Geschäftsführung der Sparkassen Rating und Risikosysteme GmbH.
Hier startete er 2009 Bereich Scoring und besetzte anschließend verschiedene Führungspositionen für die Bereiche Rating-Verfahren, Individualprojekte sowie Data Analytics. Anfang 2018 wurde er in die
Geschäftsführung berufen.
Die Aufzeichnung dieses Webinars steht demnächst hier zur Verfügung: http://aws.amazon.com/de/recorded-webinar/
Big Data ist eines der großen Schlagworte der letzten Jahre. Aber was ist das? In vielen Unternehmen gibt es heute große Datenbestände, die nicht oder nicht ausreichend genutzt werden. Das können Logfiles eines Webservers, Bon-Daten eines Einzelhandelsunternehmens oder Sensordaten einer Produktionsstraße sein. In diesem Webinar geben wir einen Überblick über Big Data und die benutzten Technologien.
Data Analytics und Machine Learning bei der SparkassengruppeADTELLIGENCE GmbH
Bei der Digital Konferenz The Future of AI & Big Data Analytics gibt Christian Damaschke, Geschäftsführer der Sparkasse Rating & Risikosysteme GmbH, einen Einblick über den Einsatz von Data Analytics und Machine Learning bei der Sparkassengruppe.
Christian Damaschke ist seit 2018 Mitglied in der Geschäftsführung der Sparkassen Rating und Risikosysteme GmbH.
Hier startete er 2009 Bereich Scoring und besetzte anschließend verschiedene Führungspositionen für die Bereiche Rating-Verfahren, Individualprojekte sowie Data Analytics. Anfang 2018 wurde er in die
Geschäftsführung berufen.
Die Aufzeichnung dieses Webinars steht demnächst hier zur Verfügung: http://aws.amazon.com/de/recorded-webinar/
Big Data ist eines der großen Schlagworte der letzten Jahre. Aber was ist das? In vielen Unternehmen gibt es heute große Datenbestände, die nicht oder nicht ausreichend genutzt werden. Das können Logfiles eines Webservers, Bon-Daten eines Einzelhandelsunternehmens oder Sensordaten einer Produktionsstraße sein. In diesem Webinar geben wir einen Überblick über Big Data und die benutzten Technologien.
Erfolgsgeschichte aus dem Smart Data Solution Center (SDSC-BW);
Dr. Andreas Wierse, Geschäftsführer SICOS BW GmbH;
1st Smart Data Innovation Conference (SDIC'16)
Internet of things - 2/4. The Challenges AheadSumanth Bhat
This document discusses seven key design challenges for cyberphysical systems (CPS):
1. Abstraction issues due to many abstraction layers that reduce predictability and reliability.
2. Timing issues because programming languages lack timing semantics and addition of network layers introduces more timing problems.
3. Architecture models need to be scalable and inspired by social and biological models.
4. Miniaturization and energy efficiency are critical for applications like smart dust that require small, long-lasting embedded systems.
5. Precision needs for CPS are unprecedented and new computation methods may be needed for greater accuracy than binary floating point.
6. Security and privacy concerns with interconnected heterogeneous devices.
7. Standardization is important for
Sichere Cloud: Sicherheit in Cloud-Computing-Systemen (Umfrage des Fraunhofer...Sabrina Lamberth-Cocca
Cloud Computing gilt als eine der wichtigsten Innovationen in der (IKT-) Wirtschaft der vergangenen Jahre. Die
Idee ist, dass Speicherplatz, Rechenleistung und konkrete Software-Anwendungen nicht mehr beim Anwender
selbst vorgehalten, sondern extern als Dienstleistung eingekauft werden.
Vielversprechend sind die Möglichkeiten, die sich durch das Outsourcing von Rechen-, Speicher- und ITDienstleistungen
für Unternehmen ergeben. Bevor Unternehmen jedoch in die Wolke ziehen, müssen
grundlegende Fragestellungen geklärt werden; speziell die Frage nach der Sicherheit ist vorrangig.
Aus diesem Grund erforscht das Fraunhofer-Institut für Arbeitswirtschaft und Organisation IAO in Zusammenarbeit
mit der BITKOM, inwiefern Cloud-Anbieter auf die Sicherheitsanforderungen potenzieller Kunden vorbereitet sind.
In diesem Zusammenhang wurden ein Stimmungsbild und konkrete Unternehmensanforderungen erhoben.
In Germany 'Industrie 4.0' is the synonym for 'Industrial Internet'. I give an overview over the security features of the commonly used protocols. Sorry: In German language only.
Industrie 4.0 und die Auswirkungen auf die Instandhaltung (Vortrag auf den In...Georg Guentner
Instandhaltung 4.0
Wie wirkt sich der Trend zu Virtualisierung und Vernetzung auf die Prozesse, Methoden und Strategien der Instandhaltung aus? Welche Chancen, Gefahren und Möglichkeiten ergeben sich durch den Einsatz von Internet-Technologien für die Branche? Wie schützen wir uns vor unerwünschten Zugriffen auf die Daten unserer Maschinen und Sensoren? Was kommt auf die InstandhalterInnen zu?
Antworten auf diese Fragen sucht ein in Salzburg gestartetes Sondierungsprojekt mit der Bezeichnung „Instandhaltung 4.0“: Der Vortrag bei den Instandhaltungstagen 2014 am 10.04.2014 beschreibt den Weg zur Entwicklung eine Roadmap für den Forschungs- und Entwicklungsbedarf der Branche in der vierten industriellen Revolution und stellt erste Arbeitshypothesen vor.
3 Things to Learn About:
*The IoT ecosystem and data management considerations for IoT
*Top IoT use cases and data architecture strategies for managing the sheer volume and variety of IoT data
*Real-life case studies on how our customers are using Cloudera Enterprise to drive insights and analytics from all of their IoT data
Independent of the source of data, the integration of event streams into an Enterprise Architecture gets more and more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analysed, often with many consumers or systems interested in all or part of the events. Dependent on the size and quantity of such events, this can quickly be in the range of Big Data. How can we efficiently collect and transmit these events? How can we make sure that we can always report over historical events? How can these new events be integrated into traditional infrastructure and application landscape?
Starting with a product and technology neutral reference architecture, we will then present different solutions using Open Source frameworks and the Oracle Stack both for on premises as well as the cloud.
If you have somehow missed the hype, the Internet of Things (IoT) is a fast-growing constellation of internet-connected sensors attached to a wide variety of 'things'. Sensors can take a multitude of possible measurements, Internet connections can be wired or wireless, while 'things' can literally be any object to which you can attach or embed a sensor. If you carry a smartphone, for example, you become a multi-sensor IoT 'thing', and many of your day-to-day activities can be tracked, analysed and acted upon.
Many of the conversations taking place around the IoT are incomplete without a mention of big data. Big data is characterised by “4 V’s”: volume, variety, velocity and veracity. That is, big data comes in large amounts (volume), is a mixture of structured and unstructured information (variety), arrives at (often real-time) speed (velocity) and can be different levels of uncertainty (veracity).
As organizations step into IoT, they must understand the symbiotic relationship between IoT and big data. Just like with any big-data play, merely collecting the data isn't enough. The data must be processed and analyzed to derive meaningful insights, and those insights must drive actionable steps that can improve the business.
What that means is that, without Big Data, the IoT can offer an enterprise little more than noise. But wait…! On the other hand, without IoT, the Big Data is little more than any other software lying idle. Actually you need two to Tango. That’s when you get the perfect marriage!
Big Data Analytics for the Industrial Internet of ThingsAnthony Chen
This document summarizes a presentation about big data analytics for the industrial internet of things. The presentation introduces the concepts of the industrial internet and how machine-generated data from sensors can be analyzed at large scale. Examples are given of how sensor data from aircraft engines, wind turbines, medical devices, and other systems can provide insights to improve efficiency, predict maintenance needs, and enhance operations. The presentation argues that big data analytics applied to industrial internet sensor data can help eliminate up to $150 billion in waste across industries through optimizations.
The document discusses using Internet of Things (IoT) technology to address challenges facing modern cities. It notes that rapid urbanization, economic pressures, and environmental sustainability concerns are stressing city infrastructure and quality of life. The document then outlines how independent infrastructure investments by different city departments result in wasted resources and a lack of shared intelligence. It proposes that an integrated IoT platform allowing data sharing across departments could help optimize city management and operations.
The document presents an overview of Internet of Things (IoT) concepts and proposes a reference architecture for IoT. It discusses core IoT concerns like connectivity, device management, data handling and security. It describes common IoT device types like Arduino, Raspberry Pi and communication protocols like HTTP, MQTT, CoAP. The proposed reference architecture aims to provide a scalable and secure way to interact with billions of connected devices by addressing issues like management, data processing and disaster recovery. An example implementation of the architecture for an RFID attendance tracking system is also presented.
Proof of concepts and use cases with IoT technologiesHeikki Ailisto
Set of proof of concept and use cases with internet of things technologies are presented with one sliders. In each case, the IoT challenge, result, benefits and use case example are given.
This document discusses Internet of Things (IoT) use cases and how organizations can create business value from connecting devices and assets. It provides an overview of reports predicting massive growth in connected devices and trillions in economic value from the IoT. However, it notes that many organizations are still struggling to get started with IoT initiatives. It then outlines 26 specific IoT use cases organized by business function to help organizations identify opportunities to transform processes. Examples are provided of companies successfully applying IoT use cases in areas like operations, service, marketing and more. The document encourages organizations to identify which use cases are most relevant using a workshop and roadmap developed by PTC.
On December 9 & 10, Deloitte hosted over 20 business executives and thought leaders at the Internet of Things (IoT) Grand Challenge Workshop at the Tech Museum of Innovation in San Jose. The objective of the gathering was to work collectively to solve one of the more largely unexplored areas of IoT: revenue generating IoT use cases. The following report captures what was discussed during this extraordinary event where an open, collaborative dialogue focused on advancing the field of IoT.
Explore the key findings here or learn more at www2.deloitte.com/us/IoT-challenge.
Medien & Verlage im Zusammenspiel mit Open (Government) DataMartin Kaltenböck
Vortrag vom 14.7. 2011 im Rahmen der Semantics & Media Conference an der Johannes Gutenberg Universität Mainz von Martin Kaltenböck zu: Medien & Verlage im Zusammenspiel mit Open (Government) Data
Erfolgsgeschichte aus dem Smart Data Solution Center (SDSC-BW);
Dr. Andreas Wierse, Geschäftsführer SICOS BW GmbH;
1st Smart Data Innovation Conference (SDIC'16)
Internet of things - 2/4. The Challenges AheadSumanth Bhat
This document discusses seven key design challenges for cyberphysical systems (CPS):
1. Abstraction issues due to many abstraction layers that reduce predictability and reliability.
2. Timing issues because programming languages lack timing semantics and addition of network layers introduces more timing problems.
3. Architecture models need to be scalable and inspired by social and biological models.
4. Miniaturization and energy efficiency are critical for applications like smart dust that require small, long-lasting embedded systems.
5. Precision needs for CPS are unprecedented and new computation methods may be needed for greater accuracy than binary floating point.
6. Security and privacy concerns with interconnected heterogeneous devices.
7. Standardization is important for
Sichere Cloud: Sicherheit in Cloud-Computing-Systemen (Umfrage des Fraunhofer...Sabrina Lamberth-Cocca
Cloud Computing gilt als eine der wichtigsten Innovationen in der (IKT-) Wirtschaft der vergangenen Jahre. Die
Idee ist, dass Speicherplatz, Rechenleistung und konkrete Software-Anwendungen nicht mehr beim Anwender
selbst vorgehalten, sondern extern als Dienstleistung eingekauft werden.
Vielversprechend sind die Möglichkeiten, die sich durch das Outsourcing von Rechen-, Speicher- und ITDienstleistungen
für Unternehmen ergeben. Bevor Unternehmen jedoch in die Wolke ziehen, müssen
grundlegende Fragestellungen geklärt werden; speziell die Frage nach der Sicherheit ist vorrangig.
Aus diesem Grund erforscht das Fraunhofer-Institut für Arbeitswirtschaft und Organisation IAO in Zusammenarbeit
mit der BITKOM, inwiefern Cloud-Anbieter auf die Sicherheitsanforderungen potenzieller Kunden vorbereitet sind.
In diesem Zusammenhang wurden ein Stimmungsbild und konkrete Unternehmensanforderungen erhoben.
In Germany 'Industrie 4.0' is the synonym for 'Industrial Internet'. I give an overview over the security features of the commonly used protocols. Sorry: In German language only.
Industrie 4.0 und die Auswirkungen auf die Instandhaltung (Vortrag auf den In...Georg Guentner
Instandhaltung 4.0
Wie wirkt sich der Trend zu Virtualisierung und Vernetzung auf die Prozesse, Methoden und Strategien der Instandhaltung aus? Welche Chancen, Gefahren und Möglichkeiten ergeben sich durch den Einsatz von Internet-Technologien für die Branche? Wie schützen wir uns vor unerwünschten Zugriffen auf die Daten unserer Maschinen und Sensoren? Was kommt auf die InstandhalterInnen zu?
Antworten auf diese Fragen sucht ein in Salzburg gestartetes Sondierungsprojekt mit der Bezeichnung „Instandhaltung 4.0“: Der Vortrag bei den Instandhaltungstagen 2014 am 10.04.2014 beschreibt den Weg zur Entwicklung eine Roadmap für den Forschungs- und Entwicklungsbedarf der Branche in der vierten industriellen Revolution und stellt erste Arbeitshypothesen vor.
3 Things to Learn About:
*The IoT ecosystem and data management considerations for IoT
*Top IoT use cases and data architecture strategies for managing the sheer volume and variety of IoT data
*Real-life case studies on how our customers are using Cloudera Enterprise to drive insights and analytics from all of their IoT data
Independent of the source of data, the integration of event streams into an Enterprise Architecture gets more and more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analysed, often with many consumers or systems interested in all or part of the events. Dependent on the size and quantity of such events, this can quickly be in the range of Big Data. How can we efficiently collect and transmit these events? How can we make sure that we can always report over historical events? How can these new events be integrated into traditional infrastructure and application landscape?
Starting with a product and technology neutral reference architecture, we will then present different solutions using Open Source frameworks and the Oracle Stack both for on premises as well as the cloud.
If you have somehow missed the hype, the Internet of Things (IoT) is a fast-growing constellation of internet-connected sensors attached to a wide variety of 'things'. Sensors can take a multitude of possible measurements, Internet connections can be wired or wireless, while 'things' can literally be any object to which you can attach or embed a sensor. If you carry a smartphone, for example, you become a multi-sensor IoT 'thing', and many of your day-to-day activities can be tracked, analysed and acted upon.
Many of the conversations taking place around the IoT are incomplete without a mention of big data. Big data is characterised by “4 V’s”: volume, variety, velocity and veracity. That is, big data comes in large amounts (volume), is a mixture of structured and unstructured information (variety), arrives at (often real-time) speed (velocity) and can be different levels of uncertainty (veracity).
As organizations step into IoT, they must understand the symbiotic relationship between IoT and big data. Just like with any big-data play, merely collecting the data isn't enough. The data must be processed and analyzed to derive meaningful insights, and those insights must drive actionable steps that can improve the business.
What that means is that, without Big Data, the IoT can offer an enterprise little more than noise. But wait…! On the other hand, without IoT, the Big Data is little more than any other software lying idle. Actually you need two to Tango. That’s when you get the perfect marriage!
Big Data Analytics for the Industrial Internet of ThingsAnthony Chen
This document summarizes a presentation about big data analytics for the industrial internet of things. The presentation introduces the concepts of the industrial internet and how machine-generated data from sensors can be analyzed at large scale. Examples are given of how sensor data from aircraft engines, wind turbines, medical devices, and other systems can provide insights to improve efficiency, predict maintenance needs, and enhance operations. The presentation argues that big data analytics applied to industrial internet sensor data can help eliminate up to $150 billion in waste across industries through optimizations.
The document discusses using Internet of Things (IoT) technology to address challenges facing modern cities. It notes that rapid urbanization, economic pressures, and environmental sustainability concerns are stressing city infrastructure and quality of life. The document then outlines how independent infrastructure investments by different city departments result in wasted resources and a lack of shared intelligence. It proposes that an integrated IoT platform allowing data sharing across departments could help optimize city management and operations.
The document presents an overview of Internet of Things (IoT) concepts and proposes a reference architecture for IoT. It discusses core IoT concerns like connectivity, device management, data handling and security. It describes common IoT device types like Arduino, Raspberry Pi and communication protocols like HTTP, MQTT, CoAP. The proposed reference architecture aims to provide a scalable and secure way to interact with billions of connected devices by addressing issues like management, data processing and disaster recovery. An example implementation of the architecture for an RFID attendance tracking system is also presented.
Proof of concepts and use cases with IoT technologiesHeikki Ailisto
Set of proof of concept and use cases with internet of things technologies are presented with one sliders. In each case, the IoT challenge, result, benefits and use case example are given.
This document discusses Internet of Things (IoT) use cases and how organizations can create business value from connecting devices and assets. It provides an overview of reports predicting massive growth in connected devices and trillions in economic value from the IoT. However, it notes that many organizations are still struggling to get started with IoT initiatives. It then outlines 26 specific IoT use cases organized by business function to help organizations identify opportunities to transform processes. Examples are provided of companies successfully applying IoT use cases in areas like operations, service, marketing and more. The document encourages organizations to identify which use cases are most relevant using a workshop and roadmap developed by PTC.
On December 9 & 10, Deloitte hosted over 20 business executives and thought leaders at the Internet of Things (IoT) Grand Challenge Workshop at the Tech Museum of Innovation in San Jose. The objective of the gathering was to work collectively to solve one of the more largely unexplored areas of IoT: revenue generating IoT use cases. The following report captures what was discussed during this extraordinary event where an open, collaborative dialogue focused on advancing the field of IoT.
Explore the key findings here or learn more at www2.deloitte.com/us/IoT-challenge.
Medien & Verlage im Zusammenspiel mit Open (Government) DataMartin Kaltenböck
Vortrag vom 14.7. 2011 im Rahmen der Semantics & Media Conference an der Johannes Gutenberg Universität Mainz von Martin Kaltenböck zu: Medien & Verlage im Zusammenspiel mit Open (Government) Data
1) Open Government Überblick
- Transparenz
- Beteiligung & Zusammenarbeit
2) Open Innovation
3) Open Data Wirtschaftliche Aspekte
4) Open Data: Chancen, Nutzen, erausforderungen & Gefahren
Das Internet of Things, Cloud Computing und Big Data sind die Grundpfeiler der digitalen Transformation und werden Wirtschaft, Gesellschaft und Staat in den nächsten Jahren erheblich verändern. Die dabei entstehenden gigantischen Datenmengen erfordern die Bereitstellung entsprechender Technologien. Cloud-Computing wird dabei eine zentrale Rolle spielen.
„DATA SCIENTIST – DIE KARRIERE DER ZUKUNFT“ - WIE DIE ANALYSE VON DATEN DIE W...Euroforum Deutschland GmbH
Unternehmen haben in den vergangenen Jahren eine enorme Menge an Daten (Big Data) angesammelt. Daraus zukunftsentscheidende Schlüsse zu ziehen ist Gold wert. Doch die klassischen Informatiker und Statistiker sind mit Anfragen der Fachabteilung überfordert, beispielsweise mit dieser: „Nimm diese 300TB und hole mir 10 Kunden daraus, mit denen wir in den kommenden Jahren den meisten Umsatz machen.“ Analysen von Big Data vermitteln richtungsweisende und teilweise revolutionäre Erkenntnisse für Produktoptimierung, Kreierung neuer Produkte, Markenwahrnehmung oder Financial Forecasting.
Nur der Data Scientist ist in der Lage, Big Data effektiv zu verarbeiten. Er übernimmt das Organisieren der Daten und das Bauen analytischer Modelle im Rahmen eines Projektes. Unternehmen, die von den enorm großen Datenvolumina proitieren wollen, brauchen künftig speziisch ausgebildete Datenwissenschaftler. Laut dem IT-Analysten Gartner werden bis 2015 durch Big Data 4,4 Millionen neue Jobs entstehen.
Dieses EUROFORUM-Whitepaper mit Fallstudien aus IT (Microsoft) und Logistik (Fraport) sowie Automobilindustrie (Mercedes), Handel (OTTO), dem Gesundheitssektor (Charité Berlin) und weiteren Branchen beweist: Data Science ist DAS branchenübergreifende Zukunfts-Thema der Wirtschaft.
http://www.euroforum.de/veranstaltungen/data_science_november2014
Einführung in die semantische Suche in MassendatenMartin Voigt
German only!
Meine Folien des Einführungsvortrags für Nicht-Informatiker bei der BDK-Fachtagung "Auswertung von Massendaten" zum Thema semantische Suche an der Polizei Fachhochschule Brandenburg. Inhalte: 1) Probleme heutiger Suchtechnologien, 2) Überblick zu semantischen Technologien, 3) Verbesserung des Information Retrieval durch Semantik
https://www.bdk.de/der-bdk/aktuelles/bdk-fachtagung-auswertung-von-massendaten
Ist Ihr Unternehmen in der Lage auf Knopfdruck alle Dokumente zu einer Person zu lokalisieren, um dann die „Betroffenenrechte“ gemäß der DSGVO (Recht auf Auskunft, Berichtigung, Löschung, Einschränkung, Datenübertragbarkeit) erfüllen zu können?
Eines der Schlüsselelemente der DSGVO ist die Handhabung von personenbezogenen Daten im gesamten Unternehmen. Sie müssen in der Lage sein bestehende und neu erfasste Daten zu klassifizieren, Datensätze jederzeit zu finden und den Umgang mit personenbezogenen Daten nachvollziehbar zu dokumentieren.
Um diese große Herausforderung zu meistern, stellen wir Ihnen unseren Ansatz vor, der auf Enterprise Search Technologie aus dem Hause SINEQUA basiert, und der Sie bei der präzisen und effizienten Integration Ihrer künftigen Compliance-Strategie in die bestehende IT-Landschaft unterstützt.
Unser Geschäftsführer Klaus Reichenberger zeigte mit seinem Vortrag „Mit vernetzter Information näher am Kunden – Digitalisierung in deutschen Traditionsunternehmen“ bei der World Class Digital Transformation 2016, wie intelligent views Herausforderungen der Digitalisierung meistert.
Simple Knowledge Organisation System (SKOS) as the core of Enterprise Knowled...Andreas Blumauer
Enterprises use knowledge graphs for a more agile information management. Taxonomies build an essential part of knowledge graphs. When based on Semantic Web standards, parts of graphs can be reused more efficiently. SKOS as a standard for taxonomies plays a crucial role in this information architecture.
Linked data the next 5 years - From Hype to ActionAndreas Blumauer
How can we shape the future of Linked Data and the Semantic Web, to make it even more widely spread in enterprises and other organizations? Which developments around linked data technologies should we expect, and how can we implement various use cases successfully?
See how the widely used SKOS standard can be further extended by custom ontologies like FIBO, and SKOS-XL as part of the Semantic Web standards stack.
Learn about concrete use cases and see how PoolParty Semantic Suite can serve as a comfortable software tool to create and maintain knowledge models based on SKOS-XL.
111 Blumauer - A Five-Star Rating System for Semantic SearchAndreas Blumauer
The document presents a five-star rating system for semantic search. A five-star semantic search uses multilingual, interconnected knowledge organizations to interpret information needs based on multiple, real-time transformed data sources with an explicit, harmonized metadata layer accessible through a federated SPARQL endpoint. This provides more precise interpretation of queries, higher recall and precision, and enables new insights without extensive browsing.
Most information professionals already know: separation of content and presentation helps to manage and deliver complex information. This can only be done by using enriched structured content. Some call this intelligent content.
But why exactly is metadata per document (some call it "tagging") not enough?
Here is a very brief slide-deck, which explains the difference between the traditional approach and the graph-based approach to develop not only a metadata layer seperated from the content layer, but also a knowledge layer on top of it.
Von Dokumenten-zentrierten Intranet-Lösungen hin zu kollaborativen, themen-zentrierten Intranet-Plattformen. Was semantische Technologien dabei leisten. Wie das in Drupal, SharePoint, Confluence & Co. integriert werden kann.
Linked Data: Standards, Nutzen und Anwendungen. Text Mining profitiert von Wissensgraphen basierend auf Semantic Web Standards. Im Vortrag werden Funktionsweisen erklärt und nützliche Anwendungsbeispiele gebracht.
The document discusses how semantic technologies can help make customer support systems more intelligent by understanding customer needs better. It proposes using a knowledge model and controlled vocabulary to translate between technical terms used by suppliers and plain language used by customers. This helps provide a more user-friendly digital guidance system within the customer support system. The approach results in a semantic index of content, improved search and recommendation capabilities, and the ability to combine information from multiple knowledge bases automatically.
Semantic Web als Infrastruktur fuer die WissensgesellschaftAndreas Blumauer
Presentation (in German) held in Berlin, September 2012 at XINNOVATIONS 2012.
Deals with "Semantic Web and Linked data as Infrastructure in a Knowledge Society"
Open data is obviously socio-politically relevant and helps to reduce administrative costs. It is kind of an infrastructure which is „invisible“ for the business community
But to make it attractive for enterprises, open/external data obviously should be integrable with internal databases.
Are linked data and open semantic web standards the solution?
Linked data is a mature technology to integrate data from different sources. This slidedeck shows how to use linked data and semantic web technolgies in the enterprise context. Use cases are semantic search, business intelligence, text mining and 360 degrees views on data sources
PoolParty provides semantic technologies including thesaurus management, semantic search, and linked data integration. Their mission is to make semantic technologies easy to use based on W3C standards. Their components include PoolParty Thesaurus (PPT) for managing controlled vocabularies, PoolParty Extract (PPX) for text mining and metadata mapping, and PoolParty Search (PPS) for faceted search and query expansion. They have many customers across industries and help connect distributed information through linked data.
This document discusses the role of thesauri in semantic search and provides examples of semantic search implementations using PoolParty Semantic Search. It describes how thesauri can improve search by enabling functions like auto-complete, query expansion, faceted search across languages and data sources. Two show cases are presented: a web catalogue of renewable energy actors integrated with databases using a thesaurus, and a large financial institution's semantic search of document management systems. A live demo of PoolParty Semantic Search is available.
PoolParty Semantic Search Server is described technologically. How to use SKOS thesauri to map data from different sources and how to generate a semantic index. How to build precise faceted search.
1. Open data can provide benefits to enterprises by improving data integration and reducing costs. However, businesses have concerns about data quality, licensing, and economic value.
2. Linked open data addresses some of these concerns by linking data together using common standards, which allows for easier integration and discovery of related information.
3. Examples like BBC Music and Nature, and Reegle show how linking open data can improve search and discovery of related content to benefit customers, stakeholders, and knowledge workers.
This document discusses semantic search and how thesauri can improve search experiences. It describes different types of semantic searches and demands for smarter searches. PoolParty Semantic Search is presented as a solution that leverages thesauri to provide auto-complete, query expansion, faceted search, and integration of linked data from multiple sources. A live demo of PoolParty Semantic Search is available online.
The document appears to be a collection of short phrases and sentences on various topics including being closed, structural coupling, a fly not being open to art, better search capabilities, integrated views, gadgets, opening up slowly, jokes and the weather, enterprise mashups, open innovation, content enrichment, large amounts of data, and spreading data. It does not provide any clear overall theme or narrative to summarize.
PoolParty Thesaurus Management - ISKO UK, London 2010Andreas Blumauer
Building and maintaining thesauri are complex and laborious tasks. PoolParty is a Thesaurus Management Tool (TMT) for the Semantic Web, which aims to support the creation and maintenance of thesauri by utilizing Linked Open Data (LOD), text-analysis and easy-to-use GUIs, so thesauri can be managed and utilized by domain experts without needing knowledge about the semantic web. Some aspects of thesaurus management, like the editing of labels, can be done via a wiki-style interface, allowing for lowest possible access barriers to contribution.
The document discusses how linking data and using semantic technologies can make applications and machines smarter. It provides examples of how linked data is being used by organizations like the BBC, Ordnance Survey, and Foursquare. It also outlines some barriers to wider adoption of linked data like business models, licensing, scalability, and privacy.
1. Von Big Data zu Smart Data
The Power of Linked Data
Mag. Andreas Blumauer
Semantic Web Company
www.semantic-web.at
www.poolparty.biz
2. Willkommen!
• Wirtschaftsinformatiker
• CEO and Partner der
Semantic Web Company
GmbH, Wien
• Produkt Management:
PoolParty Semantic Suite
• Kunden: Banken,
Verwaltung, Medien,
Pharma, Energie
12. Linked Data basierte Suche
‘Versteckte Beziehungen’ zwischen Dokumenten, Dingen
und Personen werden erkannt.
Komplexere Abfragen möglich!
13. PoolParty Semantic Integrator
Ihr CMS
1.
2.
3.
4.
Eigene Wissensgraphen entwickeln und einsetzen
Inhalte aus verschiedenen Quellen zusammenführen
Inhalte automatisch verlinken
Inhalte mit komplexen Queries abfragen können
14. Round Table Diskussion
Round Table 2 (13:10 Uhr):
Semantische Technologien gezielt nutzen
Anwendungsszenarien im Umfeld von Big Data
Was ist Linked Data?
Integration von Dateninseln
Text Analytics mit Linked Data
Linked Data basierte Suche
PoolParty Semantic Integrator
15. Danke für Ihre Aufmerksamkeit!
Andreas Blumauer
CEO, Semantic Web Company
+43 1 4021235
a.blumauer@semantic-web.at
www.semantic-web.at
www.poolparty.biz
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