The document describes the DALICC Vocabulary, which was developed as part of the DALICC project to represent legal expressions from licenses in a machine-readable way. The vocabulary extends the ODRL and CCRel ontologies with additional properties needed to capture the full semantic spectrum of copyright statements. Examples are provided showing how the BSD 3.0, CC-BY, and Apache licenses can be represented using the DALICC vocabulary. The goal is to significantly reduce the costs of license clearance for derivative works by developing a framework that can understand and process license information.
More Information:
http://flevy.com/browse/flevypro/artificial-intelligence-ai-deep-learning-3250
As organizations invest more and more into advanced automation, we are seeing significant advancements in Artificial Intelligence (AI) in the business world. The rise of the machines is becoming an impending reality. The AI revolution is here. Most businesses are aware of this and see the tremendous potential of AI. In fact, the largest tech companies and governments are all heavily investing in AI research.
The most common type of AI is currently still Machine Learning (ML), which leverages statistical techniques to give computer systems the ability to learn with data, without being explicitly programmed.
This presentation specifically discusses a specific type of ML called Deep Learning. Deep Learning uses computers to create networks which simulate the way a human brain perceives, organizes, and makes decisions from data input.
This presentation further explores the most widely used models of Deep Learning in the business world:
1. Convolutional Neural Network (CNN)
2. Recurrent Neural Network (RNN)
Examples of Deep Learning being used include:
* Processing handwritten material
* Diagnosing health diseases from medical scans
* Using radar imagery to help guide self-driving cars
* Generating captions to images
* Assessing the likelihood that a credit card transaction is fraudulent
* etc.
This deck also includes slide templates for you to use in your own business presentations.
Got a question about the product? Email us at flevypro@flevy.com. If you cannot view the preview above this document description, go here to view the large preview instead.
Source: Artificial Intelligence (AI): Deep Learning PowerPoint document
ABOUT FLEVYPRO
FlevyPro is a subscription service for on-demand business frameworks and analysis tools. FlevyPro subscribers receive access to an exclusive library of curated business documents—business framework primers, presentation templates, Lean Six Sigma tools, and more—among other exclusive benefits.
Semantic Web for 360-degree Health: State-of-the-Art & Vision for Better Inte...Amit Sheth
Ora Lassila and Amit Sheth, "Semantic Web for 360-degree Health: State-of-the-Art & Vision for Better Interoperability", Invited Talk at ONC-HHS Invitational Workshop on Next Generation Interoperability for Health, Washington DC, January 19-20, 2011.
More Information:
http://flevy.com/browse/flevypro/artificial-intelligence-ai-deep-learning-3250
As organizations invest more and more into advanced automation, we are seeing significant advancements in Artificial Intelligence (AI) in the business world. The rise of the machines is becoming an impending reality. The AI revolution is here. Most businesses are aware of this and see the tremendous potential of AI. In fact, the largest tech companies and governments are all heavily investing in AI research.
The most common type of AI is currently still Machine Learning (ML), which leverages statistical techniques to give computer systems the ability to learn with data, without being explicitly programmed.
This presentation specifically discusses a specific type of ML called Deep Learning. Deep Learning uses computers to create networks which simulate the way a human brain perceives, organizes, and makes decisions from data input.
This presentation further explores the most widely used models of Deep Learning in the business world:
1. Convolutional Neural Network (CNN)
2. Recurrent Neural Network (RNN)
Examples of Deep Learning being used include:
* Processing handwritten material
* Diagnosing health diseases from medical scans
* Using radar imagery to help guide self-driving cars
* Generating captions to images
* Assessing the likelihood that a credit card transaction is fraudulent
* etc.
This deck also includes slide templates for you to use in your own business presentations.
Got a question about the product? Email us at flevypro@flevy.com. If you cannot view the preview above this document description, go here to view the large preview instead.
Source: Artificial Intelligence (AI): Deep Learning PowerPoint document
ABOUT FLEVYPRO
FlevyPro is a subscription service for on-demand business frameworks and analysis tools. FlevyPro subscribers receive access to an exclusive library of curated business documents—business framework primers, presentation templates, Lean Six Sigma tools, and more—among other exclusive benefits.
Semantic Web for 360-degree Health: State-of-the-Art & Vision for Better Inte...Amit Sheth
Ora Lassila and Amit Sheth, "Semantic Web for 360-degree Health: State-of-the-Art & Vision for Better Interoperability", Invited Talk at ONC-HHS Invitational Workshop on Next Generation Interoperability for Health, Washington DC, January 19-20, 2011.
How HudsonAlpha Innovates on IT for Research-Driven Education, Genomic Medici...Dana Gardner
Transcript of a discussion on how HudsonAlpha leverages modern IT infrastructure and big data analytics to power research projects as well as pioneering genomic medicine findings.
Recommender systems support the decision making processes of customers with personalized suggestions. These widely used systems influence the daily life of almost everyone across domains like ecommerce, social media, and entertainment. However, the efficient generation of relevant recommendations in large-scale systems is a very complex task. In order to provide personalization, engines and algorithms need to capture users’ varying tastes and find mostly nonlinear dependencies between them and a multitude of items. Enormous data sparsity and ambitious real-time requirements further complicate this challenge. At the same time, deep learning has been proven to solve complex tasks like object or speech recognition where traditional machine learning failed or showed mediocre performance.
Explore a use case for vehicle recommendations at mobile.de, Germany’s biggest online vehicle market. Marcel shares a novel regularization technique for the optimization criterion and evaluates it against various baselines. To achieve high scalability, he combines this method with strategies for efficient candidate generation based on user and item embeddings—providing a holistic solution for candidate generation and ranking.
The proposed approach outperforms collaborative filtering and hybrid collaborative-content-based filtering by 73% and 143% for MAP@5. It also scales well for millions of items and users returning recommendations in tens of milliseconds.
Loyalty Management Innovator AIMIA's Transformation Journey to Modernized and...Dana Gardner
Transcript of a discussion on how improving end-user experiences and using big data analytics helps head off digital disruption and improve core operations.
Mending the Gap between Library's Electronic and Print Collections in ILS and...New York University
This presentation proposed a conceptual model to model user's info seeking behavior in the context of their experience and use the model to improve library's collections and services using St. John's University Libraries for case study. It reviewed Web content technologies offered by IT vendors, and compared what offered in content technologies by Library IT vendors. To fill in the gap, It developed the preliminary proposal for 1) required data architecture in SOA framework, 2) desired features for managing library print and electronic content on library's website, 3) adoption of Semantic Web standards and technologies for managing library resources, and 4) the case study scenario with sample conceptual model.
A STUDY ON THE IMPLEMENTATION OF SEMANTIC WIKI-BASED KNOWLEDGE MANAGEMENT SYSTEM FOR APPLICATION SERVICE PROVIDERS (ASP\’S) IN MANAGING SOFTWARE ARTIFACTS
Search Solutions 2011: Successful Enterprise Search By DesignMarianne Sweeny
When your colleagues say they want Google, they don’t mean the Google Search Appliance. They mean the Google Search user experience: pervasive, expedient and delivering the information that they need. Successful enterprise search does not start with the application features, is not part of the information architecture, does not come from a controlled vocabulary and does not emerge on its own from the developers. It requires enterprise-specific data mining, enterprise-specific user-centered design and fine tuning to turn “search sucks” into search success within the firewall. This presentation looks at action items, tools and deliverables for Discovery, Planning, Design and Post Launch phases of an enterprise search deployment.
Cross discipline collaboration benefits from group think, a consolidation of soft system methodology and user focused design that all starts with design thinking that sees clients, designers, developers and information architects working together to address user problems and needs. As with any great adventure, design thinking starts with exploration and discovery.This presentation examines the high level tenants of system thinking, expands the scope of user thinking to include tools and devices that users employ to find out designs and delve into the specifics of design thinking, its methods and outcomes.
Linked Data Love: research representation, discovery, and assessment
#ALAAC15
The explosion of linked data platforms and data stores over the last five years has been profound – both in terms of quantity of data as well as its potential impact. Research information systems such as VIVO (www.vivoweb.org) play a significant role in enabling this work. VIVO is an open source, Semantic Web-based application that provides an integrated, searchable view of the scholarly activities of an organization. The uniform semantic structure of VIVO-ISF data enables a new class of tools to advance science. This presentation will provide a brief introduction and update to VIVO and present ways that this semantically-rich data can enable visualizations, reporting and assessment, next-generation collaboration and team building, and enhanced multi-site search. Libraries are uniquely positioned to facilitate the open representation of research information and its subsequent use to spur collaboration, discovery, and assessment. The talk will conclude with a description of ways librarians are engaged in this work – including visioning, metadata and ontology creation, policy creation, data curation and management, technical, and engagement activities.
Kristi Holmes, PhD
Director, Galter Health Sciences Library
Director of Evaluation, NUCATS
Associate Professor, Preventive Medicine-Health and Biomedical Informatics
Northwestern University Feinberg School of Medicine
AHM 2014: OceanLink, Smart Data versus Smart Applications EarthCube
Presentation given by Krysztof Janowicz and Pascal Hitzler in the afternoon Architecture Forum Session on Day 1, June 24, at the EarthCube All-Hands Meeting.
DevOps Support for an Ethical Software Development Life Cycle (SDLC)Mark Underwood
As part of the IEEE SA P7000 and P2675 working groups, it has been determined that DevOps engineering practices can support (or hinder) the environment for an ethical software development life cycle (SDLC). This deck scratches the surface.
The current status of Linked Open Data (LOD) shows evidence of many datasets available on the Web in RDF. In the meantime, there are still many challenges to overcome by organizations in their journey of publishing five stars datasets on the Web. Those challenges are not only technical, but are also organizational. At this moment where connectionist AI is gaining a wave of popularity with many applications, LOD needs to go beyond the guarantee of FAIR principles. One direction is to build a sustainable LOD ecosystem with FAIR-S principles. In parallel, LOD should serve as a catalyzer for solving societal issues (LOD for Social Good) and personal empowerment through data (Social Linked Data).
How HudsonAlpha Innovates on IT for Research-Driven Education, Genomic Medici...Dana Gardner
Transcript of a discussion on how HudsonAlpha leverages modern IT infrastructure and big data analytics to power research projects as well as pioneering genomic medicine findings.
Recommender systems support the decision making processes of customers with personalized suggestions. These widely used systems influence the daily life of almost everyone across domains like ecommerce, social media, and entertainment. However, the efficient generation of relevant recommendations in large-scale systems is a very complex task. In order to provide personalization, engines and algorithms need to capture users’ varying tastes and find mostly nonlinear dependencies between them and a multitude of items. Enormous data sparsity and ambitious real-time requirements further complicate this challenge. At the same time, deep learning has been proven to solve complex tasks like object or speech recognition where traditional machine learning failed or showed mediocre performance.
Explore a use case for vehicle recommendations at mobile.de, Germany’s biggest online vehicle market. Marcel shares a novel regularization technique for the optimization criterion and evaluates it against various baselines. To achieve high scalability, he combines this method with strategies for efficient candidate generation based on user and item embeddings—providing a holistic solution for candidate generation and ranking.
The proposed approach outperforms collaborative filtering and hybrid collaborative-content-based filtering by 73% and 143% for MAP@5. It also scales well for millions of items and users returning recommendations in tens of milliseconds.
Loyalty Management Innovator AIMIA's Transformation Journey to Modernized and...Dana Gardner
Transcript of a discussion on how improving end-user experiences and using big data analytics helps head off digital disruption and improve core operations.
Mending the Gap between Library's Electronic and Print Collections in ILS and...New York University
This presentation proposed a conceptual model to model user's info seeking behavior in the context of their experience and use the model to improve library's collections and services using St. John's University Libraries for case study. It reviewed Web content technologies offered by IT vendors, and compared what offered in content technologies by Library IT vendors. To fill in the gap, It developed the preliminary proposal for 1) required data architecture in SOA framework, 2) desired features for managing library print and electronic content on library's website, 3) adoption of Semantic Web standards and technologies for managing library resources, and 4) the case study scenario with sample conceptual model.
A STUDY ON THE IMPLEMENTATION OF SEMANTIC WIKI-BASED KNOWLEDGE MANAGEMENT SYSTEM FOR APPLICATION SERVICE PROVIDERS (ASP\’S) IN MANAGING SOFTWARE ARTIFACTS
Search Solutions 2011: Successful Enterprise Search By DesignMarianne Sweeny
When your colleagues say they want Google, they don’t mean the Google Search Appliance. They mean the Google Search user experience: pervasive, expedient and delivering the information that they need. Successful enterprise search does not start with the application features, is not part of the information architecture, does not come from a controlled vocabulary and does not emerge on its own from the developers. It requires enterprise-specific data mining, enterprise-specific user-centered design and fine tuning to turn “search sucks” into search success within the firewall. This presentation looks at action items, tools and deliverables for Discovery, Planning, Design and Post Launch phases of an enterprise search deployment.
Cross discipline collaboration benefits from group think, a consolidation of soft system methodology and user focused design that all starts with design thinking that sees clients, designers, developers and information architects working together to address user problems and needs. As with any great adventure, design thinking starts with exploration and discovery.This presentation examines the high level tenants of system thinking, expands the scope of user thinking to include tools and devices that users employ to find out designs and delve into the specifics of design thinking, its methods and outcomes.
Linked Data Love: research representation, discovery, and assessment
#ALAAC15
The explosion of linked data platforms and data stores over the last five years has been profound – both in terms of quantity of data as well as its potential impact. Research information systems such as VIVO (www.vivoweb.org) play a significant role in enabling this work. VIVO is an open source, Semantic Web-based application that provides an integrated, searchable view of the scholarly activities of an organization. The uniform semantic structure of VIVO-ISF data enables a new class of tools to advance science. This presentation will provide a brief introduction and update to VIVO and present ways that this semantically-rich data can enable visualizations, reporting and assessment, next-generation collaboration and team building, and enhanced multi-site search. Libraries are uniquely positioned to facilitate the open representation of research information and its subsequent use to spur collaboration, discovery, and assessment. The talk will conclude with a description of ways librarians are engaged in this work – including visioning, metadata and ontology creation, policy creation, data curation and management, technical, and engagement activities.
Kristi Holmes, PhD
Director, Galter Health Sciences Library
Director of Evaluation, NUCATS
Associate Professor, Preventive Medicine-Health and Biomedical Informatics
Northwestern University Feinberg School of Medicine
AHM 2014: OceanLink, Smart Data versus Smart Applications EarthCube
Presentation given by Krysztof Janowicz and Pascal Hitzler in the afternoon Architecture Forum Session on Day 1, June 24, at the EarthCube All-Hands Meeting.
DevOps Support for an Ethical Software Development Life Cycle (SDLC)Mark Underwood
As part of the IEEE SA P7000 and P2675 working groups, it has been determined that DevOps engineering practices can support (or hinder) the environment for an ethical software development life cycle (SDLC). This deck scratches the surface.
The current status of Linked Open Data (LOD) shows evidence of many datasets available on the Web in RDF. In the meantime, there are still many challenges to overcome by organizations in their journey of publishing five stars datasets on the Web. Those challenges are not only technical, but are also organizational. At this moment where connectionist AI is gaining a wave of popularity with many applications, LOD needs to go beyond the guarantee of FAIR principles. One direction is to build a sustainable LOD ecosystem with FAIR-S principles. In parallel, LOD should serve as a catalyzer for solving societal issues (LOD for Social Good) and personal empowerment through data (Social Linked Data).
ASTRAZENECA. Knowledge Graphs Powering a Fast-moving Global Life Sciences Org...Neo4j
AstraZeneca share their experience of share their experience of building a knowledge graph platform and central service, to power the next generation of insights and analytics at AstraZeneca.
The Rensselaer Institute for Data Exploration and Applications is addressing new modes of data exploration and integration to enhance the work of campus researchers (and beyond). This talk outlines the "data exploration" technologies being explored
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
UiPath Test Automation using UiPath Test Suite series, part 3
Session 0.0 poster minutes madness
1. SEMANTiCS 2017, Amsterdam, The Netherlands, September 11-14, 2017
Towards a Semantic Outlier Detection
Framework in Wireless Sensor Networks
Iker Esnaola-Gonzalez
2. Is there a country that publishes formal key registers as linked data?
9. Semantic Health Notice
Come and get the cure ! (free trial)
http://www.irisa.fr/LIS/ferre/sparklis/
Sébastien Ferré
● Ground: SPARQL endpoints
● Patients: RDF-hungry people
● Symptoms: paralysis (can’t write!), syntax errors,
schema mismatch, empty results
➔ FRUSTRATION and HUNGER !
● Diagnostic: SPARQL queries are toxic to humans
●
Treatment: use SparklisSparklis to avoid direct contact
composition: natural language, full guidance, expressive
power, compliance to standards (no empty-results)
P&D 204
SPARKLIS
10.
11. Semantic mining of respiratory health knowledge from
scientific literature and clinical guidelines
Sergio Consoli, Xiao Ming Zhou, Wei-Shun Bao, Declan P. Kelly, Vincent Lou
Philips Research: [name.surname]@philips.com
• Application of NLP, data mining, and advanced text analytics into advanced AI systems for semantically mining
information from scientific literature and clinical guidelines to extract new knowledge on the respiratory health domain
• Curated repository of selected medical documents into knowledge-base in respiratory health
12. • Goal feeding and controlling connected respiratory health devices according the gathered knowledge and providing
intuitive visualization interfaces for user understanding
Scope 1: data bootstrap via scientific literatures to extract knowledge
Scope 2: provide relevant
feedback and insights from data
Challenges
• Repository of biomedical scientific literature
– Large volume & Accessibility
• Data Processing and Interpretation
– Performance VS Speed
• Knowledgebase
– Data-linking of concepts and relationships to ensure both syntactic and semantic interoperability
• Information Querying and Retrieval
– ML & prediction models for deriving rules and facts, and providing feedbacks/insights/recommendations
13. Is Semantic Markup really
helping websites improve
traffic?
Build Your Own Knowledge Graph and make
your content easy to be found.
WordLift team wordlift.io
14. Key Findings from our research
1. After 3 Months organic visits went up by 12.13%
2. Google is faster in bringing new users (+18.47%
increased of sessions from Google only)
3. Enriched article compared to other pages performed
2.4 times better in terms of pageviews and sessions
4. Average time spent went up 17.3% for enriched
articles
5. Average session duration improved by 13.75%
Yes it does!
15. “Findability” is not simply SEO
BEFORE and AFTER
Get Your Free Demo! wordlift.io/welcome
16. Towards Open Data Mashups for Data Journalism
Fajar J. Ekaputra, Niina Maarit Novak, Elmar Kiesling, Peb R. Aryan, Ba-Lam Do, Tuan-Dat Trinh, A Min Tjoa
Linked Data Lab, Institute of Software Technology and Information Systems, TU Wien, Austria
Prototype:Open Data Mashups for Data Journalism (ODMOJO):
17. PRESS: A Publication REpository Semantic System
• PRESS is an open-source publication system that exploits semantic
technologies, in order to cover the needs of both individuals and
organizations
• Fast data entry, user-based repository
• Advanced query capabilities
• Integration with other systems
• Commercial: designed mainly for experts, not extensible
• Existing open-source: difficulty in expressing complex queries, rely on rigid relational schemas
FORTH, Institute of Computer Science
VS. Other Approaches
Ioannis Chrysakis, Emmanouil Dermitzakis, Giorgos Flouris, Theodore Patkos and Dimitris Plexousakis
Learn more at stand #2
18. Vision and market gap
• Motivation
– Comments are becoming an integral part
of the Web, and not only the Social Web
– Yet, comment management is largely ad-
hoc and inefficient
• Grand vision: interconnect, search,
store, retrieve, evaluate comments that
exist on the Web
Methinks
Methinks Application
• Advantages for consumers/end-users
– Become well-informed in just a glance
– Quickly identify non-standard information that can be
found only in comments
– Browse based on arguments, not on words
• Advantages for analysts (admins)
– A cheap way to integrate fancy, comment-related
functionality in one’s web site
– A measurable way to extract conclusions (analytics) in
online discussions
Contact: Giorgos Flouris (fgeo@ics.forth.gr)Learn more at stand #3
19. Information is archived in a way
disregarding its meaning and context
Retrieval systems search, analysis
Retrieval systems visualization
Information is archived in a way disregarding
itsmeaning and context
Retrievalsystems search, analysis
Retrieval systems visualization options
Problem & VIScover SolutionUncovering the Hidden in Large Knowledge Graphs
1
How to connect the dots in my Knowledge Graph?
• How to get meaningful insight?
• Which groups of objects connect
to each other?
• How to build sophisticated
queries without syntax?
• How about data integrity or
anomalies?
naive graph
rendering fails
SPARQL, cypher, etc.
require data insight
20. Information is archived in a way
disregarding its meaning and context
Retrieval systems search, analysis
Retrieval systems visualization
Information is archived in a way disregarding
itsmeaning and context
Retrievalsystems search, analysis
Retrieval systems visualization options
Problem & VIScover SolutionSemSpect: Visualizing and Querying Knowledge Graphs
2
Poster &
Wed.
10:45
http://panama.semspect.de
21. Michael Färber and Achim Rettinger, KIT: A Statistical Comparison of Current Knowledge Bases
22. Now: In a Crunch, so CrunchBase
Michael Färber, Carsten Menne, Andreas Harth: “A Linked Data Wrapper for CrunchBase”
23. 1WIS
Challenge: Form an Educated Opinion for Online Products
Twilight (2008): 1545 reviews on IMDB.com, 3,053 reviews on Amazon.com.
Which reviews to read?
Example: Is the movie “Twilight” any good?
Horrible Story, Horrible ActingGreat Story, Great Acting
Sorted by Usefulness
Grouped by Aspects
VS.
Proposed solution: Semantically group reviews to help users!
25. 1
● Statement-level metadata allows to store
fine-grained
○ traceability and provenance information
○ license and access rights,
○ data trustworthiness and confidence
scores
for every single fact in the knowledge graph
● Different MRMs have been proposed, varying
in structure, performance
benefits/disadvantages
● Hard to choose appropriate format
beforehand
MaSQue: An Approach for Flexible Metadata
Storage and Querying in RDF
Knowledge Integration and Linked Data Technologies (AKSW/KILT)
at InfAI & Leipzig University
Johannes Frey, Sebastian Hellmann
Metadata Representation Models
27. Network-based Knowledge Graph Assessment
What is it about?
Real-world entities and their relations
Information retrieval
Effectiveness depends on quality
1Rörden, Revenko, Haslhofer, Blumauer:
Network-based Knowledge Graph Assessment.
28. Network-based Knowledge Graph Assessment
What is our approach?
Network metrics
Domain-specific corpus
Combine and compare!
2Rörden, Revenko, Haslhofer, Blumauer:
Network-based Knowledge Graph Assessment.
29. ‹#› Het begint met een idee
A STUDY OF INTENSIONAL CONCEPT DRIFT
IN TRENDING DBPEDIA CONCEPTS
Albert Meroño-Peñuela, Efstratios Kontopoulos,
Sándor Darányi, Ioannis Kompatsiaris
Causes?
• Interaction between ordinary humans and systems
• Ontology evolution patterns of use
34. Introduction
DALICC stands for Data Licenses Clearance Center. The
project‘s aim is to develop a software framework that
significantly reduces the costs of license clearance in the
creation of derivative (data) works.
DALICC follows a deontic approach to express machine-
readable permissions, prohibitions and duties defined in a
license. DALICC utilizes the ODRL 2.0 ontology in
combination with CCRel. Additionally DALICC utilizes an
extended set of properties that are necessary to capture the
full semantic spectrum of legal expressions defined in a
license text.
By doing so DALICC allows to represent property rights
policies in a legally valid and machine-processable way.
Partners:
• UAS St. Pölten (Lead) – Tassilo Pellegrini, Andrea Schönhofer, Peter Judmaier, Stefanie Größbacher
• Vienna University of Economics & Business – Simon Steyskal, Sabrina Kirrane, Axel Polleres
• University of Innsbruck – Oleksandra Panasiuk, Anna Fensel
• Höhne, In der Maur & Partner Rechtsanwälte OG – Markus Dörfler
• Semantic Web Company GmbH – Thomas Thurner, Victor Mireles-Chavez, Kurt Moser
Contact: www.dalicc.net
Acknowledgment: DALICC is funded by the Austrian Federal Ministry of Transport, Innovation and Technology
(BMVIT) under the program "ICT of the Future" between November 2016 - October 2018. More information
https://iktderzukunft.at/en/
DALICC Vocabulary – REL Extension
The DALICC vocabulary extensions evolved from an in depth
analysis of 15 standard licenses (including CC, APACHE, BSD,
GPL MIT) under the supervision of legal experts. The following
expressions need to be added to cover the full semantic
spectrum of copyright statements:
PROPERTIES AFFECTING THE ASSET PROPERTIES AFFECTING THE LICENCE
dalicc:charge dalicc:addStatement
dalicc:sublicense dalicc:attributionNotice
dalicc:promote dalicc:attachOffer
dalicc:publish dalicc:chargeOffer
dalicc:irrevocable
dalicc:modificationNotice
dalicc:noWarrantyNotice
dalicc:patentFree
dalicc:patentNotice
dalicc:perpetual
dalicc:royaltyFree
dalicc:worldwide
The examples illustrate the RDF/Turle syntax of BSD 3.0, CC-BY
and APACHE using the DALICC properties (bold).
Example 3: APACHE
@prefix odrl:<http://www.w3.org/ns/odrl/2/> .
@prefix : <https://dalicc.net/license-finder> .
@prefix dalicc: <https://dalicc.poolparty.biz/DALICCVocabulary>.
@prefix rdf:<http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix cc:<http://creativecommons.org/ns#> .
@prefix dct: <http://purl.org/dc/terms/> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
@prefix rdf:<http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
:APACHE_2.0 a odrl:Policy;
odrl:permission [
a odrl:Permission;
odrl:target
<http://purl.org/dc/dcmitype/Software>,
<http://purl.org/dc/dcmitype/Sound>,<http://purl.
org/dc/dcmitype/Text>,<http://purl.org/dc/dcmity
pe/Image>,<http://purl.org/dc/dcmitype/MovingI
mage>,<http://purl.org/dc/dcmitype/Dataset>;
odrl:action odrl:present, odrl:display, odrl:derive;
odrl:duty [
a odrl:Duty;
odrl:action cc:Notice;
]
];
odrl:permission [
a odrl:Permission;
odrl:target
<http://purl.org/dc/dcmitype/Software>,<http://p
url.org/dc/dcmitype/Sound>,<http://purl.org
/dc/dcmitype/Text>,<http://purl.org/dc/dcmitype
/Image>,<http://purl.org/dc/dcmitype/Movin
gImage>,<http://purl.org/dc/dcmitype/Dataset>;
odrl:action odrl:reproduce, odrl:distribute,
dalicc:sublicense, dalicc:addStatement,
dalicc:chargeOffer, dalicc:patentFree;
odrl:duty [
a odrl:Duty;
odrl:action dalicc:modificationNotice, cc:Notice,
dalicc:patentNotice, dalicc:atributionNotice,
dalicc:noWarrantyNotice, cc:ShareAlike,
dalicc:perpetual, dalicc:royaltyFree,
dalicc:irrevocable, dalicc:worldwide
]
];
odrl:prohibition [
a odrl:Prohibition;
odrl:target
<http://purl.org/dc/dcmitype/Software>,<http://p
url.org/dc/dcmitype/Sound>,<http://purl.org/dc/d
cmitype/Text>,<http://purl.org/dc/dcmitype/Image
>,<http://purl.org/dc/dcmitype/MovingImage>,
<http://purl.org/dc/dcmitype/Dataset>;
odrl:action odrl:ensureExclusivity, dalicc:charge;
].
Example 1: BSD 3.0
@prefix odrl:<http://www.w3.org/ns/odrl/2/> .
@prefix : <https://dalicc.net/license-finder> .
@prefix dalicc: <https://dalicc.poolparty.biz/DALICCVocabulary>.
@prefix rdf:<http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix cc:<http://creativecommons.org/ns#> .
@prefix dct: <http://purl.org/dc/terms/> .
:licBSD-3-Clause a odrl:Policy;
odrl:permission [
a odrl:Permission;
odrl:target <http://purl.org/dc/dcmitype/Software>;
odrl:action odrl:mofify, odrl:distribute, odrl:reproduce;
odrl:duty [
a odrl:Duty;
odrl:action cc:Notice, dalicc:nowarrantyNotice;
]
];
odrl:prohibition [
a odrl:Prohibition;
odrl:target <http://purl.org/dc/dcmitype/Software>;
odrl:action dalicc:promote
];
dct:title "The 3-Clause BSD License"@en ;
dct:alternative "BSD-3-Clause";
dct:source <https://opensource.org/licenses/BSD-3-Clause>.
Example 2: CC-BY
@prefix odrl:<http://www.w3.org/ns/odrl/2/> .
@prefix : <https://dalicc.net/license-finder> .
@prefix dalicc: <https://dalicc.poolparty.biz/DALICCVocabulary>.
@prefix rdf:<http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix cc:<http://creativecommons.org/ns#> .
@prefix dct: <http://purl.org/dc/terms/> .
@prefix foaf: <http://xmlns.com/foaf/0.1/> .
:CC-BY_4.0 a odrl:Policy;
odrl:permission [
a odrl:Permission;
odrl:target
<http://purl.org/dc/dcmitype/Dataset>,<http://purl.org/d
c/dcmitype/Sound>,<http://purl.org/dc/dcmitype/Text>,<
http://purl.org/dc/dcmitype/Image>,<http://purl.org/dc/
dcmitype/MovingImage>;
odrl:action odrl:distribute, odrl:reproduce,odrl:extract,
odrl:derive, odrl:present;
odrl:duty [
a odrl:Duty;
odrl:action cc:SourceCode, dalicc:royaltyFree,
dalicc:irrevocable, dalicc:worldwide, cc:Notice,
dalicc:noWarrantyNotice, dalicc:modificationNotice,
cc:attributionName
]
];
odrl:prohibition [
a odrl:Prohibition;
odrl:target
<http://purl.org/dc/dcmitype/Dataset>,<http://purl.org/dc
/dcmitype/Sound>,<http://purl.org/dc/dcmitype/Text>,
<hattp://purl.org/dc/dcmitype/Image>,<http://purl.org/dc
/dcmitype/MovingImage>;
odrl:action odrl:ensureExclusivity, dalicc:sublicense
];
dct:title "Attribution 4.0 International"@en ;
dct:alternative "CC BY 4.0";
dct:publisher "Creative Commons";
foaf:logo <http://i.creativecommons.org/l/by/4.0/88x31.png> ;
dct:source <http://creativecommons.org/licenses/by/4.0/> ;
cc:legalcode
"""https://creativecommons.org/licenses/by/4.0/legalcode"""@en.
Future Work
The DALICC Framework will consist of four components:
• License Composer: Lets you create customized licenses
• License Library: Lets you choose from a set of standard licenses
• License Annotator: Provides you with a machine-readable and human-readable version of
your license
• License Negotiator: Checks compatibility, detects conflicts and supports conflict resolution
Data Set
N License N
License
{A … N} Derivative Work
Data Set
… License …
Data Set
B License B
Data Set
A License A
License
Composer
License
Annotator
License
Library
DALICC Framework
License
Negotiator
consults
tags audits proposes
• Compatibility
• Conflict Detection
• Conflict Resolution
35. ‹#› Het begint met een idee
CEDAR: THE DUTCH HISTORICAL CENSUSES
(1795-1971) AS LINKED OPEN DATA
Albert Meroño-Peñuela, Ashkan Ashkpour,
Christophe Guéret, Stefan Schlobach
1st historical census data as Linked Data
RDF Data Cube with
• 6.8M observations
• Internal links: sex, marital status, occupation
position, housing type, residence status
• External links
• Geographical: 2.7M
• Occupations: 350K
• Belief: 250K
• Linked to HISCO, ICONCLASS, Dutch Ships and
Sailors, DBpedia, gemeentegeschiedenis.nl,
GeoNames
• New variables and classifications
• Housing type
• Lower level of municipal areas (kom, wijk)
• Residence status
36. ‹#› Het begint met een idee
http://www.licr.io
http://purl.org/licr/vocab
Bottom-up codes
from:
• NAPP
• IPUMS
• HL7
37. ‹#› Het begint met een idee
HISCO – Historical International Standard
Classification of Occupations
9 major groups
1675 occupation
classes
Labels in 14
languages
38. SEMANTiCS 2017, Amsterdam, The Netherlands, September 11-14, 2017
The EEPSA Ontology
The Energy Efficiency Prediction Semantic Assistant Ontology
Iker Esnaola-Gonzalez
https://w3id.org/eepsa
40. From diverse and
complex solutions...
The Linked Web APIs Ontology
- semantic Web API description model -
...to a unified
solution.
FOAF
Hydra
SADI
WSMO
SAWSDL
OpenAPI
apis.json
The Linked Web APIs
Ontology
WADL
WSDL
“A lightweight model for
description of information
related to Web APIs,
mashups, developers and
API providers.”
WADL
MSM
OWL-S
HTML
See: http://linked-web-apis.fit.cvut.cz/ns/core/
41. (Non-)Functional props:
“what functionalities a Web
API or mashup offers.”
Provenance info:
“Who created What
and How”
Temporal information:
“the time a Web API or a
mashup was created.”
Technical props:
“supported protocols,
formats, endpoints, etc.”
Over 11K Web APIs,
7K mashups and
7K developer profiles
First and largest Linked Data
dataset with semantic Web API
descriptions!
The Linked Web APIs Dataset
- Web APIs meet Linked Data -
More info at: http://linked-web-apis.fit.cvut.cz/
42. PRODUCT PASSPORT OF YOUR GARMENT
Produced By: Mud Jeans
Product ID: RM1600016
Production Step Produced By Production Date Composition
Textiles Collected Mud Jeans 01-05-2016 Discarded Jeans 100%
Recycled Fibers Recover 10-05-2016 Denim Recycled 100%
Garment Produced Yousstex 15-09-2016
Denim Recycled 20%;
Cotton 75%
Activity Agent
Product
Linked Data
Circular Economy
Textile Use Case
Elke Sauter & Martijn Witjes
46. Talk of Europe
Laura Hollink, Astrid van Aggelen, Jacco van Ossenbruggen
The debates of the European
Parliament as Linked Open Data*
Centrum Wiskunde & Informatica (CWI)
Amsterdam, The Netherlands
Talk of Europe
made by
the ECLinks:
Motivation:
Access is crucial for EU residents
to make informed votes and hold
Members of Parliament accountable.
Access is necessary
for researchers in
party position, ideology,
issue selection, and
emphasis.
What?
1. scrape http://www.europarl.europa.eu/
2. convert to RDF
3. enrich with links to
external sources
Why?
Access is crucial for EU residents
to make informed votes and hold
Members of Parliament accountable.
Access is necessary
for researchers in
party position, ideology,
issue selection, and
emphasis.
47. Example query: The number
of speeches of each country
per year.
session
session day
dcterms:partOf
item on the
agenda
partOf
speech
partOf
...This is indeed a
homecoming...@en
spoken
text
...Dette er i høj grad
en hjemkomst...@da
translated
text
speaker
speaker
member of
parliamentrdf:type
political function
president role
2002
beginningEuropean
Parliament
institution
2004
end
political function
substituterole
1989
beginning
Committee on
budgetary control
institution
1992
end
sub-properties
of text
design pattern:
n-ary relation
spokenAs
redundant but convenient
additional property
foaf:name
....
re-use of Dublin Core
and FOAF vocabularies
Vocabulary:
Published as:
Astrid van Aggelen, Laura Hollink, Max Kemman, Martijn
Kleppe, Henri Beunders. The debates of the European
Parliament as Linked Open Data. Semantic Web 8(2), IOS
Press, 2017
Website: http://talkofeurope.eu/
SPARQL endpoint: http://purl.org/linkedpolitics/sparql/
Acknowledgements: