Spadrole is a business dedicated to getting breakthrough results for high-performing individuals, companies and associations. We believe that leaders who dare to dream and implement real changes create a contagious environment, one that leads to healthy, satisfied, high-achieving teams—an inspired workforce! Creative thinking skyrockets. Cooperation soars. Job satisfaction goes through the roof!
As an author, innovator and proud member of the Canadian Association of Professional Speakers, Rolande Kirouac has trained dozens of leaders about the health benefits of dreaming big and creating a dynamic game plan to make things happen.
Rolande works with groups and individuals who want to make real change happen now!
Spadrole is a business dedicated to getting breakthrough results for high-performing individuals, companies and associations. We believe that leaders who dare to dream and implement real changes create a contagious environment, one that leads to healthy, satisfied, high-achieving teams—an inspired workforce! Creative thinking skyrockets. Cooperation soars. Job satisfaction goes through the roof!
As an author, innovator and proud member of the Canadian Association of Professional Speakers, Rolande Kirouac has trained dozens of leaders about the health benefits of dreaming big and creating a dynamic game plan to make things happen.
Rolande works with groups and individuals who want to make real change happen now!
www.igadi.org
Presentation
IGADI presents its first World Report on de facto States, which intends to regularly monitor these new figures on the international scene that reflect the emergence, and even consolidation, of those subjects, up to now marginal and totally fenced-in within the world order. Now such subjects usually appear in privileged positions on the global agenda whether directly(Russia-Georgia War) or indirectly(piracy in Somalia), displaying a strong impact capability.
In addition, we provide fact sheets for each of these de facto States, which have been chosen upon compliance with a series of common elements. These fact sheets include a brief analysis, momentary diagnoses, which both point out the clues that determine their present state and include specific alerts concerning vectors that may anticipate the appearance of serious crisis on the horizon.
This report tries to bring together some of the activities of IGADI's Research Program on International System's Security, Conflicts, and Alternatives, a usual work space for some of the contributors to this document.
We would like to thank all the authors for their contributions, since without their generosity and rigorousness, it would have been impossible to carry out this Report.
IGADI, February 28th, 2011.
Opintojaksolla etsitään yhdessä vastauksia esimerkiksi seuraaviin kysymyksiin:
Miten sosiaalista mediaa voi hyödyntää yrityksen markkinoinnissa? Mitä sosiaalisen median kanavia on olemassa? Miten sopivat kanavat valitaan? Mitä lisäarvoa sosiaalinen media voi tuoda yritykselle? Miten sosiaalisen median käyttöä suunnitellaan ja toteutetaan käytännössä?
Keskustellaan, pohditaan ja rakennetaan yhdessä osallistujille soveltuvia lähestymistapoja sosiaaliseen mediaan!
O 'Infórmate a Fondo' é o boletín trimestral do Fondo Galego. No IAF 137, número 6 da época dixital, poderás atopar toda a información sobre os últimos meses de vida da asociación municipalista, xunto a unha entrevista co reporteiro Gonzo.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
www.igadi.org
Presentation
IGADI presents its first World Report on de facto States, which intends to regularly monitor these new figures on the international scene that reflect the emergence, and even consolidation, of those subjects, up to now marginal and totally fenced-in within the world order. Now such subjects usually appear in privileged positions on the global agenda whether directly(Russia-Georgia War) or indirectly(piracy in Somalia), displaying a strong impact capability.
In addition, we provide fact sheets for each of these de facto States, which have been chosen upon compliance with a series of common elements. These fact sheets include a brief analysis, momentary diagnoses, which both point out the clues that determine their present state and include specific alerts concerning vectors that may anticipate the appearance of serious crisis on the horizon.
This report tries to bring together some of the activities of IGADI's Research Program on International System's Security, Conflicts, and Alternatives, a usual work space for some of the contributors to this document.
We would like to thank all the authors for their contributions, since without their generosity and rigorousness, it would have been impossible to carry out this Report.
IGADI, February 28th, 2011.
Opintojaksolla etsitään yhdessä vastauksia esimerkiksi seuraaviin kysymyksiin:
Miten sosiaalista mediaa voi hyödyntää yrityksen markkinoinnissa? Mitä sosiaalisen median kanavia on olemassa? Miten sopivat kanavat valitaan? Mitä lisäarvoa sosiaalinen media voi tuoda yritykselle? Miten sosiaalisen median käyttöä suunnitellaan ja toteutetaan käytännössä?
Keskustellaan, pohditaan ja rakennetaan yhdessä osallistujille soveltuvia lähestymistapoja sosiaaliseen mediaan!
O 'Infórmate a Fondo' é o boletín trimestral do Fondo Galego. No IAF 137, número 6 da época dixital, poderás atopar toda a información sobre os últimos meses de vida da asociación municipalista, xunto a unha entrevista co reporteiro Gonzo.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
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.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
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.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
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.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Generating a custom Ruby SDK for your web service or Rails API using Smithy
Semantic web rdf and inferencing
1. "Golden Delicious"
"Elstar"
rdfs:label
el
"Conference"
:lab
bot:GoldenDelicious
rdfs
"Gala" "Fuji"
rdfs:l
el
abel bot:Elstar
:lab
bot:Gala
el
rdfs
b
:la "any edible part of a plant with a sweet flavor"
bot:Braeburn fs
bot:Apple rd
Conference bot:Fuji
l
labe
rdfs:
t
rdf
men
"Braeburn" "Fig"
s:la
:com
be
"Fruit"
l
rdfs:label
rdfs
"Pear" "Apple" l
: labe
rdfs
cul:Fruit
el bot:Fig
"Pommegranate"
l ab
s:
df :label
rdfs
bot:pomaceousFruit bot:accessoryFruit
bot:Pommegranate
"Structure of
label
el
ab
hinese Pear" "Fruit"
s:l
rdfs:
rdf
el
:lab
el lab
rdfs rdfs:
" #" "Pomaceous Fruit" "Accessory Fruit" bot:Fruit
bo bot:PlantStructure
bot:Strawberry t:c
el on
ab ta
l ins bot:N
bo
:
fs
t
t:p
rd
el
en
ar
:lab
Semantic Web mm
tO
gkeum
s
f
:co
rdf
:Seed
s
rd
rdf
fs: bot:Plant
la "Strawberry"
be
l
DON WILLEMS
RDF and Inferencing
"!"" bo
INTELLIGENT SYSTEMS ONTOLOGY LUNCH MEETING JUNE 14TH 2011
"the ovary of a seed-bearing plant"
WAGENINGEN UR/FOOD & BIOBASEDtOf
:par
RESEARCH
bot
bot:Tomato
2. based on:
Chapter 5 - RDF and Inferencing
Semantic Web for the Working Ontologist
Dean Allemang and Jim Hendler
ISBN 978-0-12-373556-0
3. Making Data Smarter
In the semantic web we have an integrated and
distributed representation of data
Modeling is needed to make sense of this network
of data
But how can a model help us make sense of this
network of data?
4. Example
bot:Fruit cul:Fruit
Suppose you find RDF
data concerning bot:accessoryFruit
bot:Kosui
How would you know bot:pomaceousFruit
that Kosui is a type of
fruit? bot:Pear
bot:EuropeanPear bot:ChinesePear
bot:Conference bot:DoyenneDuComice bot:BlakesPride bot:Forelle bot:Kosui bot:Shinko bot:Whangkeum
5. Example: Query
Solution 1: Leverage the power of the query:
SELECT ?super WHERE {{
bot:Kosui rdfs:subClassOf ?super.
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf ?super].
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf [rdfs:subClassOf ?super]].
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf [rdfs:subClassOf
[rdfs:subClassOf ?super]]].
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf [rdfs:subClassOf
[rdfs:subClassOf [rdfs:subClassOf ?super]]]].
} ...
}
6. Example: Query
Solution 1: Leverage the power of the query:
SELECT ?super WHERE {{
bot:Kosui rdfs:subClassOf ?super. ---> bot:ChinesePear
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf ?super].
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf [rdfs:subClassOf ?super]].
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf [rdfs:subClassOf
[rdfs:subClassOf ?super]]].
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf [rdfs:subClassOf
[rdfs:subClassOf [rdfs:subClassOf ?super]]]].
} ...
}
7. Example: Query
Solution 1: Leverage the power of the query:
SELECT ?super WHERE {{
bot:Kosui rdfs:subClassOf ?super.
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf ?super].---> bot:Pear
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf [rdfs:subClassOf ?super]].
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf [rdfs:subClassOf
[rdfs:subClassOf ?super]]].
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf [rdfs:subClassOf
[rdfs:subClassOf [rdfs:subClassOf ?super]]]].
} ...
}
8. Example: Query
Solution 1: Leverage the power of the query:
SELECT ?super WHERE {{
bot:Kosui rdfs:subClassOf ?super.
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf ?super].
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf [rdfs:subClassOf ?super]].
} UNION { ---> bot:pomaceousFruit
bot:Kosui rdfs:subClassOf [rdfs:subClassOf [rdfs:subClassOf
[rdfs:subClassOf ?super]]].
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf [rdfs:subClassOf
[rdfs:subClassOf [rdfs:subClassOf ?super]]]].
} ...
}
9. Example: Query
Solution 1: Leverage the power of the query:
SELECT ?super WHERE {{
bot:Kosui rdfs:subClassOf ?super.
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf ?super].
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf [rdfs:subClassOf ?super]].
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf [rdfs:subClassOf
[rdfs:subClassOf ?super]]].
} UNION {
---> bot:accessoryFruit
bot:Kosui rdfs:subClassOf [rdfs:subClassOf [rdfs:subClassOf
[rdfs:subClassOf [rdfs:subClassOf ?super]]]].
} ...
}
10. Example: Query
Solution 1: Leverage the power of the query:
SELECT ?super WHERE {{
bot:Kosui rdfs:subClassOf ?super.
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf ?super].
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf [rdfs:subClassOf ?super]].
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf [rdfs:subClassOf
[rdfs:subClassOf ?super]]].
} UNION {
bot:Kosui rdfs:subClassOf [rdfs:subClassOf [rdfs:subClassOf
[rdfs:subClassOf [rdfs:subClassOf ?super]]]].
} ...
}
---> bot:Fruit
---> cul:Fruit
11. Example: Inferencing
Solution 2: Inferencing
IF
IF ?A rdfs:subClassOf ?B.
?A rdfs:subClassOf ?super. AND
AND ?B rdfs:subClassOf ?C.
?x rdf:type ?A. THEN
THEN ?A rdfs:subClassOf ?C.
?x rdf:type ?super.
subclass-propagation
type-propagation rule
rule
12. Example: Inferencing
bot:Fruit cul:Fruit
IF
?A rdfs:subClassOf ?B.
bot:accessoryFruit
AND
?B rdfs:subClassOf ?C.
THEN
?A rdfs:subClassOf ?C.
bot:pomaceousFruit
bot:Pear
bot:EuropeanPear bot:ChinesePear
bot:Conference bot:DoyenneDuComice bot:BlakesPride bot:Forelle bot:Kosui bot:Shinko bot:Whangkeum
13. Example: Inferencing
bot:Fruit cul:Fruit
IF
?A rdfs:subClassOf ?B.
bot:accessoryFruit
AND
?B rdfs:subClassOf ?C.
THEN
?A rdfs:subClassOf ?C.
bot:pomaceousFruit
bot:Pear
bot:EuropeanPear bot:ChinesePear
bot:Conference bot:DoyenneDuComice bot:BlakesPride bot:Forelle bot:Kosui bot:Shinko bot:Whangkeum
14. Example: Inferencing
bot:Fruit cul:Fruit
IF
?A rdfs:subClassOf ?B.
bot:accessoryFruit
AND
?B rdfs:subClassOf ?C.
THEN
?A rdfs:subClassOf ?C.
bot:pomaceousFruit
bot:Pear
bot:EuropeanPear bot:ChinesePear
bot:Conference bot:DoyenneDuComice bot:BlakesPride bot:Forelle bot:Kosui bot:Shinko bot:Whangkeum
15. Example: Inferencing
bot:Fruit cul:Fruit
IF
?A rdfs:subClassOf ?B.
bot:accessoryFruit
AND
?B rdfs:subClassOf ?C.
THEN
?A rdfs:subClassOf ?C.
bot:pomaceousFruit
bot:Pear
bot:EuropeanPear bot:ChinesePear
bot:Conference bot:DoyenneDuComice bot:BlakesPride bot:Forelle bot:Kosui bot:Shinko bot:Whangkeum
16. Example: Inferencing
bot:Fruit cul:Fruit
IF
?A rdfs:subClassOf ?B.
AND bot:accessoryFruit
?B rdfs:subClassOf ?C.
THEN
?A rdfs:subClassOf ?C.
bot:pomaceousFruit
bot:Pear
bot:EuropeanPear bot:ChinesePear
bot:Conference bot:DoyenneDuComice bot:BlakesPride bot:Forelle bot:Kosui bot:Shinko bot:Whangkeum
17. Example: Inferencing
bot:Fruit cul:Fruit
IF
?A rdfs:subClassOf ?B.
AND bot:accessoryFruit
?B rdfs:subClassOf ?C.
THEN
?A rdfs:subClassOf ?C.
bot:pomaceousFruit
bot:Pear
bot:EuropeanPear bot:ChinesePear
bot:Conference bot:DoyenneDuComice bot:BlakesPride bot:Forelle bot:Kosui bot:Shinko bot:Whangkeum
18. Example: Inferencing
bot:Fruit cul:Fruit
How would you know bot:accessoryFruit
that Kosui is a type of
fruit?
bot:pomaceousFruit
Kosui is a subclass of
Fruit bot:Pear
bot:EuropeanPear bot:ChinesePear
bot:Conference bot:DoyenneDuComice bot:BlakesPride bot:Forelle bot:Kosui bot:Shinko bot:Whangkeum
19. Inferencing
bot:Fruit cul:Fruit
bot:accessoryFruit
Problem: Possible
explosion of the bot:pomaceousFruit
number of triples
bot:Pear
bot:EuropeanPear bot:ChinesePear
bot:Conference bot:DoyenneDuComice bot:BlakesPride bot:Forelle bot:Kosui bot:Shinko bot:Whangkeum
21. Inferencing:
asserted vs. inferred Triples
Think of inferencing and querying
Asserted Triples as separate processes
Inferred Triples 1. Use inference rules to find all
inferred triples using the
asserted triples as a conditional
2. Run SPARQL query over
asserted and inferred triples
22. Inferencing:
when does inferencing happen?
Out of range of the RDFS and OWL definitions
Depends on the implementation of the inference
engine
• As soon as a conditional pattern is identified,
inference happens and inferred triples are
stored in the same RDF store --> explosion
risk
• Never store inferred triples. Inference only
happens in response to a query --> duplicate
inference work
23. Inferencing:
change management
One problem (if inferred triples are stored) is
change management.
• What happens when a data source changes
• A triple is added --> inferencing
• A triple is removed/changed -->
• Which inferred triples need to be
removed?
24. Example:
change management
cul:Ingredient
State of triple store
before inference bot:Fruit cul:Vegetable
bot:Tomato
26. Example:
change management
cul:Ingredient
Apply subclass-
propagation rule
Resulting (inferred)
triple already exists bot:Fruit cul:Vegetable
and is not added
again
bot:Tomato
27. Example:
change management
cul:Ingredient
State of triple store
after inference bot:Fruit cul:Vegetable
bot:Tomato
28. Example:
change management
cul:Ingredient
Remove erroneous
triple
(not all Fruits (in a botanical
X
sense) are ingredients (in a
bot:Fruit cul:Vegetable
culinary sense).
bot:Tomato
29. Example:
change management
cul:Ingredient
Remove triples that
were inferred as a
result of the
existence of the
erroneous triple.
bot:Fruit
X cul:Vegetable
bot:Tomato
30. Example:
change management
State after triple cul:Ingredient
removal
Problem: The
inferred triple should
not have been bot:Fruit cul:Vegetable
removed because it
could have been
inferred using
another set of
bot:Tomato
conditionals
31. Example:
change management
State after triple cul:Ingredient
removal
Problem: The
inferred triple should
not have been bot:Fruit cul:Vegetable
removed because it
could have been
inferred using
another set of
bot:Tomato
conditionals
32. Example:
change management
Desired state after
triple removal cul:Ingredient
Two solutions:
1. Very complex
inference and bot:Fruit cul:Vegetable
change
management
2. Remove all inferred
triples and re-infer bot:Tomato
everything
33. Inferencing:
forward vs. backward chaining
Until now we used forward chaining as inference
method.
1. Find all existing triples that can be used as
condition (the IF part) in the inference rule.
2. Add a new triple specified in the result (THEN)
part of the inference rule.
This inference method is mostly used after (a) new
fact(s) are added to the triple store.
34. Inferencing:
forward vs. backward chaining
Backward chaining works the other way around.
1. Find all triples that can be seen as a result
(THEN part) of an inference rule.
cul:Ingredient
IF
?A rdfs:subClassOf ?B.
AND
bot:Fruit cul:Vegetable
?B rdfs:subClassOf ?C.
THEN
?A rdfs:subClassOf ?C.
bot:Tomato
35. Inferencing:
forward vs. backward chaining
Backward chaining works the other way around.
1. Find all triples that can be seen as a result
(THEN part) of an inference rule.
cul:Ingredient
IF
?A rdfs:subClassOf ?B.
AND
bot:Fruit cul:Vegetable
?B rdfs:subClassOf ?C.
THEN
?A rdfs:subClassOf ?C.
bot:Tomato
36. Inferencing:
forward vs. backward chaining
Backward chaining works the other way around.
2. If the triple(s) in the condition do not yet exist
try to fulfill the condition by other means (ask
the user)
Is cul:Vegetable Is Fruit
a subclass a subclass
cul:Ingredient cul:Ingredient
of cul:Ingredient? of cul:Ingredient?
? ?
bot:Fruit cul:Vegetable bot:Fruit cul:Vegetable
bot:Tomato bot:Tomato
37. Inferencing:
forward vs. backward chaining
Backward chaining works the other way around.
3. If the condition is fulfilled add the inferred triple
(defined in the condition) to the triple store.
cul:Ingredient
NO YES
bot:Fruit cul:Vegetable
bot:Tomato
38. Conclusion
• We want to be able to write a single query that
can fetch related data from all integrated data
sources.
• RDF provides a consistent way to represent data
so that information from multiple sources can
be brought together.
• Information integration is achieved by invoking
inference before or during the query process.