WebProtégé is a web-based collaborative ontology editor that allows multiple users to edit ontologies simultaneously. The document discusses collaborative ontology development processes used by projects like the Gene Ontology and International Classification of Diseases. It then provides an overview of WebProtégé's interface and collaboration features like change tracking, user roles, and sharing settings. Finally, it outlines a hands-on exercise to model an online newspaper ontology in WebProtégé.
Apache Kylin Meetup: Berlin - With OLX GroupTyler Wishnoff
Hosted by OLX Group, the October 2019 Apache Kylin Meetup in Berlin, Germany offered a great opportunity to learn what's new with OLAP and Apache Kylin, as well see real use cases where Kylin is having an impact at OLX. These slides provide the bulk of the information shared at the Meetup. Learn more about Apache Kylin here: https://kyligence.io/apache-kylin-overview/
Introduction to Ontology Engineering with Fluent Editor 2014Cognitum
An introductory course for Ontology Engineering using Controlled Natural Language. Fluent Editor (FE) is an ontology editor that is a tool for editing and manipulating ontologies. The main feature of Fluent Editor is that it uses controlled natural language (CNL) to communicate with a user. Communication with CNL is a more suitable for human users alternative to XML-based OWL editors.
5 Reasons not to use Dita from a CCMS PerspectiveMarcus Kesseler
The document discusses some of the drawbacks of using DITA from the perspective of a large content management system (CCMS). It notes that DITA's coverage of core CCMS requirements is surprisingly small, addressing only 18% of requirements compared to 67% for a typical CCMS. It also argues that the evolution of the DITA standard is too slow given market demands. Additionally, it outlines how DITA deals with the proliferation of files as content is translated and new versions are created, noting this can result in many files versus a single topic accessed differently in a CCMS.
Presto: Optimizing Performance of SQL-on-Anything EngineDataWorks Summit
Presto, an open source distributed SQL engine, is widely recognized for its low-latency queries, high concurrency, and native ability to query multiple data sources. Proven at scale in a variety of use cases at Airbnb, Bloomberg, Comcast, Facebook, FINRA, LinkedIn, Lyft, Netflix, Twitter, and Uber, in the last few years Presto experienced an unprecedented growth in popularity in both on-premises and cloud deployments over Object Stores, HDFS, NoSQL and RDBMS data stores.
With the ever-growing list of connectors to new data sources such as Azure Blob Storage, Elasticsearch, Netflix Iceberg, Apache Kudu, and Apache Pulsar, recently introduced Cost-Based Optimizer in Presto must account for heterogeneous inputs with differing and often incomplete data statistics. This talk will explore this topic in detail as well as discuss best use cases for Presto across several industries. In addition, we will present recent Presto advancements such as Geospatial analytics at scale and the project roadmap going forward.
The document discusses the basics of ontologies, including their origin in philosophy, definitions, types, benefits and application areas. Some key points are:
- An ontology is a formal specification of a conceptualization used to help humans and programs share knowledge. It establishes a shared vocabulary for exchanging information.
- Ontologies describe domain knowledge and provide an agreed-upon understanding of a domain through concepts and relations. They help solve problems of ambiguity and enable knowledge sharing.
- Ontologies benefit applications like information retrieval, digital libraries, knowledge engineering and natural language processing by facilitating semantic search and integration of data.
Apache Kylin Meetup: Berlin - With OLX GroupTyler Wishnoff
Hosted by OLX Group, the October 2019 Apache Kylin Meetup in Berlin, Germany offered a great opportunity to learn what's new with OLAP and Apache Kylin, as well see real use cases where Kylin is having an impact at OLX. These slides provide the bulk of the information shared at the Meetup. Learn more about Apache Kylin here: https://kyligence.io/apache-kylin-overview/
Introduction to Ontology Engineering with Fluent Editor 2014Cognitum
An introductory course for Ontology Engineering using Controlled Natural Language. Fluent Editor (FE) is an ontology editor that is a tool for editing and manipulating ontologies. The main feature of Fluent Editor is that it uses controlled natural language (CNL) to communicate with a user. Communication with CNL is a more suitable for human users alternative to XML-based OWL editors.
5 Reasons not to use Dita from a CCMS PerspectiveMarcus Kesseler
The document discusses some of the drawbacks of using DITA from the perspective of a large content management system (CCMS). It notes that DITA's coverage of core CCMS requirements is surprisingly small, addressing only 18% of requirements compared to 67% for a typical CCMS. It also argues that the evolution of the DITA standard is too slow given market demands. Additionally, it outlines how DITA deals with the proliferation of files as content is translated and new versions are created, noting this can result in many files versus a single topic accessed differently in a CCMS.
Presto: Optimizing Performance of SQL-on-Anything EngineDataWorks Summit
Presto, an open source distributed SQL engine, is widely recognized for its low-latency queries, high concurrency, and native ability to query multiple data sources. Proven at scale in a variety of use cases at Airbnb, Bloomberg, Comcast, Facebook, FINRA, LinkedIn, Lyft, Netflix, Twitter, and Uber, in the last few years Presto experienced an unprecedented growth in popularity in both on-premises and cloud deployments over Object Stores, HDFS, NoSQL and RDBMS data stores.
With the ever-growing list of connectors to new data sources such as Azure Blob Storage, Elasticsearch, Netflix Iceberg, Apache Kudu, and Apache Pulsar, recently introduced Cost-Based Optimizer in Presto must account for heterogeneous inputs with differing and often incomplete data statistics. This talk will explore this topic in detail as well as discuss best use cases for Presto across several industries. In addition, we will present recent Presto advancements such as Geospatial analytics at scale and the project roadmap going forward.
The document discusses the basics of ontologies, including their origin in philosophy, definitions, types, benefits and application areas. Some key points are:
- An ontology is a formal specification of a conceptualization used to help humans and programs share knowledge. It establishes a shared vocabulary for exchanging information.
- Ontologies describe domain knowledge and provide an agreed-upon understanding of a domain through concepts and relations. They help solve problems of ambiguity and enable knowledge sharing.
- Ontologies benefit applications like information retrieval, digital libraries, knowledge engineering and natural language processing by facilitating semantic search and integration of data.
This document provides an overview of self-organizing maps (SOMs), a type of artificial neural network. It discusses the biological motivation for SOMs, which are inspired by self-organizing systems in the brain. The document outlines the basic architecture and learning algorithm of SOMs, including initialization, training procedures, and classification. It also reviews various properties of SOMs, such as their ability to approximate input spaces and perform topological ordering and density matching. Finally, applications of SOMs are briefly mentioned, such as for speech recognition, image analysis, and data visualization.
This document discusses building and using ontologies. It defines an ontology as defining a domain of interest in terms of things, attributes, and relationships. Ontologies are used to share a common understanding of a domain among people and machines. The document then discusses ontology engineering processes, examples of ontologies like DBpedia, and semantic technologies used to create intelligent applications.
This document describes a tutorial on advanced ATL techniques including model refactoring. The tutorial agenda includes an introduction to model transformations using ATL, exercises on model visualization, refactoring, and compiling a DSL, as well as discussions of ATL architecture and industrialization. The document provides examples of using ATL to transform a class diagram metamodel to a relational database metamodel.
A Beginner's Guide to Large Language ModelsAjitesh Kumar
Large Language Models (LLMs) are a type of deep learning model designed to process and understand vast amounts of natural language data. Built on neural network architectures, particularly the transformer architecture, LLMs have revolutionized the field of natural language processing. In this presentation, we will explore the world of LLMs, their significance, and the different types of LLMs based on the transformer architecture, such as autoregressive language models (e.g., GPT), autoencoding language models (e.g., BERT), and combined models (e.g., T5). Join us as we delve into the world of LLMs and discover their potential in shaping the future of natural language processing.
Neural Text Embeddings for Information Retrieval (WSDM 2017)Bhaskar Mitra
The document describes a tutorial on using neural networks for information retrieval. It discusses an agenda for the tutorial that includes fundamentals of IR, word embeddings, using word embeddings for IR, deep neural networks, and applications of neural networks to IR problems. It provides context on the increasing use of neural methods in IR applications and research.
A presentation about Ontology Learning with an overview of the area and some methods used, specially techniques of Ontology Learning from Text. This presentation was part of a seminary in the MSc Course in Computer Science at UFPE - Recife - Brazil.
This document discusses principles of software design and reducing complexity. It identifies several "red flags" that can indicate increased complexity, such as change amplification, unknown unknowns, shallow modules, information leakage between classes, exceptions, repetitive code, and comments or documentation that don't enhance intuition. The document advocates for designing modules to have simple interfaces while hiding complexity internally, separating concerns into specialized modules, and avoiding unnecessary abstractions that don't reduce complexity or duplication. Overall it focuses on simplifying software design to reduce bugs and ease of understanding and modification.
The Business Case for Semantic Web Ontology & Knowledge GraphCambridge Semantics
This document discusses how semantic web ontologies and knowledge graphs can help reduce high IT costs by providing a common schema and linking data across systems. It introduces AnzoGraph DB, a graph database built on semantic web standards that can perform both analytics and graph algorithms on large datasets. The document demonstrates how public flight delay data can be converted to a knowledge graph and analyzed using techniques like PageRank, shortest paths, and querying for delayed flights. Overall, it argues that semantic technologies can help address the problem of data integration costs by enabling linked and standardized data.
Data and AI summit: data pipelines observability with open lineageJulien Le Dem
Presentation of Data lineage an Observability with OpenLineage at the "Data and AI summit" (formerly Spark summit). With a focus on the Apache Spark integration for OpenLineage
This document provides a summary of a presentation on object-oriented programming (OOP) and clean code given at IPB Computer Science on March 28, 2017. It introduces the speaker, Ifnu Bima, and his background working at Deutsche Bank and blibli.com. The presentation covers topics like code quality metrics, meaningful naming conventions, high-quality functions, comments, and unit testing. It emphasizes writing code that is easy to maintain and modify over time to prevent issues like bugs and technical debt.
Deep neural methods have recently demonstrated significant performance improvements in several IR tasks. In this lecture, we will present a brief overview of deep models for ranking and retrieval.
This is a follow-up lecture to "Neural Learning to Rank" (https://www.slideshare.net/BhaskarMitra3/neural-learning-to-rank-231759858)
The Django admin site provides a web-based interface for trusted administrators to manage content on a Django website. It allows adding, editing, and deleting data from database models. The admin is activated by adding django.contrib.admin to INSTALLED_APPS and running syncdb. Models can be customized in the admin using ModelAdmin classes to configure properties like the change list display, search fields, filters, and form layout. The admin uses a permissions system to control which users can access and modify each model.
The document contains notes on Java programming concepts from Unit 1. It defines key terms like platform, Java platform, Java Virtual Machine (JVM), and Java Application Programming Interface (API). It also discusses features of the Java language like being object-oriented, robust, portable, and platform independent. The notes provide examples of Java applications and applets and explain why Java is important for internet programming. It also lists differences between Java and C, describes components of the Java Development Kit (JDK), and covers data types and variables in Java.
Using Apache Calcite for Enabling SQL and JDBC Access to Apache Geode and Oth...Christian Tzolov
When working with BigData & IoT systems we often feel the need for a Common Query Language. The system specific languages usually require longer adoption time and are harder to integrate within the existing stacks.
To fill this gap some NoSql vendors are building SQL access to their systems. Building SQL engine from scratch is a daunting job and frameworks like Apache Calcite can help you with the heavy lifting. Calcite allow you to integrate SQL parser, cost-based optimizer, and JDBC with your NoSql system.
We will walk through the process of building a SQL access layer for Apache Geode (In-Memory Data Grid). I will share my experience, pitfalls and technical consideration like balancing between the SQL/RDBMS semantics and the design choices and limitations of the data system.
Hopefully this will enable you to add SQL capabilities to your prefered NoSQL data system.
Here is a recursive function to check if a list contains an element:
(defun contains (element list)
(cond ((null list) nil)
((equal element (car list)) t)
(t (contains element (cdr list)))))
To check the guest list:
(contains 'robocop guest-list)
This function:
1. Base case: If list is empty, element is not contained - return nil
2. Check if element equals car of list - if so, return t
3. Otherwise, recursively call contains on element and cdr of list
So it will recursively traverse the list until it finds a match or reaches empty list.
File Format Benchmarks - Avro, JSON, ORC, & ParquetOwen O'Malley
Hadoop Summit June 2016
The landscape for storing your big data is quite complex, with several competing formats and different implementations of each format. Understanding your use of the data is critical for picking the format. Depending on your use case, the different formats perform very differently. Although you can use a hammer to drive a screw, it isn’t fast or easy to do so. The use cases that we’ve examined are: * reading all of the columns * reading a few of the columns * filtering using a filter predicate * writing the data Furthermore, it is important to benchmark on real data rather than synthetic data. We used the Github logs data available freely from http://githubarchive.org We will make all of the benchmark code open source so that our experiments can be replicated.
The document provides an introduction to Prof. Dr. Sören Auer and his background in knowledge graphs. It discusses his current role as a professor and director focusing on organizing research data using knowledge graphs. It also briefly outlines some of his past roles and major scientific contributions in the areas of technology platforms, funding acquisition, and strategic projects related to knowledge graphs.
Techniques for Context-Aware and Cold-Start RecommendationsMatthias Braunhofer
Context-aware recommender systems better identify interesting items for users by adapting their suggestions to the specific contextual situations, e.g., to the current weather, if an excursion is to be recommended . But, the cold-start problem may jeopardise the quality of the recommendations: for users, items or contextual situations that are new to the system, recommendations are hard to compute. We have developed a number of novel techniques to tame this problem, and in particular, new hybrid algorithms that combine several, simpler, algorithms in order to exploit their strengths and avoid their weaknesses. We have also developed algorithms for actively identifying the most useful preference information to ask the user in order to bootstrap the system. Our results obtained from a series of offline and online experiments reveal that the proposed techniques can effectively alleviate the cold-start problem of context-aware recommender systems.
HITS and PageRank are algorithms used by search engines to rank web pages. HITS calculates hub and authority scores for each page based on the link structure related to a specific query topic. PageRank assigns each page a single prestige score based on the entire link structure, making it query-independent and resistant to spam. While both aim to identify important pages, HITS does so in a topic-specific manner, whereas PageRank provides a general importance score for each page.
This document provides a tutorial on using the Protege software to build ontologies. It explains that Protege allows constructing domain models and knowledge bases using ontologies. The tutorial then demonstrates how to install Protege, create classes and subclasses, add properties and restrictions, define domains and ranges, and use a reasoner to classify and check the ontology for inconsistencies. Various exercises are presented to help the user learn how to structure information in Protege.
Ontology development in protégé-آنتولوژی در پروتوغهsadegh salehi
This document describes an agenda for an ontology development presentation in Protégé. It discusses the syntactic web and its limitations, as well as the promise of the semantic web to address these issues by adding meaning to web content that is understandable to machines. It outlines two sessions on ontology and OWL basics, Protégé, and developing a pizza ontology in Protégé.
This document provides an overview of self-organizing maps (SOMs), a type of artificial neural network. It discusses the biological motivation for SOMs, which are inspired by self-organizing systems in the brain. The document outlines the basic architecture and learning algorithm of SOMs, including initialization, training procedures, and classification. It also reviews various properties of SOMs, such as their ability to approximate input spaces and perform topological ordering and density matching. Finally, applications of SOMs are briefly mentioned, such as for speech recognition, image analysis, and data visualization.
This document discusses building and using ontologies. It defines an ontology as defining a domain of interest in terms of things, attributes, and relationships. Ontologies are used to share a common understanding of a domain among people and machines. The document then discusses ontology engineering processes, examples of ontologies like DBpedia, and semantic technologies used to create intelligent applications.
This document describes a tutorial on advanced ATL techniques including model refactoring. The tutorial agenda includes an introduction to model transformations using ATL, exercises on model visualization, refactoring, and compiling a DSL, as well as discussions of ATL architecture and industrialization. The document provides examples of using ATL to transform a class diagram metamodel to a relational database metamodel.
A Beginner's Guide to Large Language ModelsAjitesh Kumar
Large Language Models (LLMs) are a type of deep learning model designed to process and understand vast amounts of natural language data. Built on neural network architectures, particularly the transformer architecture, LLMs have revolutionized the field of natural language processing. In this presentation, we will explore the world of LLMs, their significance, and the different types of LLMs based on the transformer architecture, such as autoregressive language models (e.g., GPT), autoencoding language models (e.g., BERT), and combined models (e.g., T5). Join us as we delve into the world of LLMs and discover their potential in shaping the future of natural language processing.
Neural Text Embeddings for Information Retrieval (WSDM 2017)Bhaskar Mitra
The document describes a tutorial on using neural networks for information retrieval. It discusses an agenda for the tutorial that includes fundamentals of IR, word embeddings, using word embeddings for IR, deep neural networks, and applications of neural networks to IR problems. It provides context on the increasing use of neural methods in IR applications and research.
A presentation about Ontology Learning with an overview of the area and some methods used, specially techniques of Ontology Learning from Text. This presentation was part of a seminary in the MSc Course in Computer Science at UFPE - Recife - Brazil.
This document discusses principles of software design and reducing complexity. It identifies several "red flags" that can indicate increased complexity, such as change amplification, unknown unknowns, shallow modules, information leakage between classes, exceptions, repetitive code, and comments or documentation that don't enhance intuition. The document advocates for designing modules to have simple interfaces while hiding complexity internally, separating concerns into specialized modules, and avoiding unnecessary abstractions that don't reduce complexity or duplication. Overall it focuses on simplifying software design to reduce bugs and ease of understanding and modification.
The Business Case for Semantic Web Ontology & Knowledge GraphCambridge Semantics
This document discusses how semantic web ontologies and knowledge graphs can help reduce high IT costs by providing a common schema and linking data across systems. It introduces AnzoGraph DB, a graph database built on semantic web standards that can perform both analytics and graph algorithms on large datasets. The document demonstrates how public flight delay data can be converted to a knowledge graph and analyzed using techniques like PageRank, shortest paths, and querying for delayed flights. Overall, it argues that semantic technologies can help address the problem of data integration costs by enabling linked and standardized data.
Data and AI summit: data pipelines observability with open lineageJulien Le Dem
Presentation of Data lineage an Observability with OpenLineage at the "Data and AI summit" (formerly Spark summit). With a focus on the Apache Spark integration for OpenLineage
This document provides a summary of a presentation on object-oriented programming (OOP) and clean code given at IPB Computer Science on March 28, 2017. It introduces the speaker, Ifnu Bima, and his background working at Deutsche Bank and blibli.com. The presentation covers topics like code quality metrics, meaningful naming conventions, high-quality functions, comments, and unit testing. It emphasizes writing code that is easy to maintain and modify over time to prevent issues like bugs and technical debt.
Deep neural methods have recently demonstrated significant performance improvements in several IR tasks. In this lecture, we will present a brief overview of deep models for ranking and retrieval.
This is a follow-up lecture to "Neural Learning to Rank" (https://www.slideshare.net/BhaskarMitra3/neural-learning-to-rank-231759858)
The Django admin site provides a web-based interface for trusted administrators to manage content on a Django website. It allows adding, editing, and deleting data from database models. The admin is activated by adding django.contrib.admin to INSTALLED_APPS and running syncdb. Models can be customized in the admin using ModelAdmin classes to configure properties like the change list display, search fields, filters, and form layout. The admin uses a permissions system to control which users can access and modify each model.
The document contains notes on Java programming concepts from Unit 1. It defines key terms like platform, Java platform, Java Virtual Machine (JVM), and Java Application Programming Interface (API). It also discusses features of the Java language like being object-oriented, robust, portable, and platform independent. The notes provide examples of Java applications and applets and explain why Java is important for internet programming. It also lists differences between Java and C, describes components of the Java Development Kit (JDK), and covers data types and variables in Java.
Using Apache Calcite for Enabling SQL and JDBC Access to Apache Geode and Oth...Christian Tzolov
When working with BigData & IoT systems we often feel the need for a Common Query Language. The system specific languages usually require longer adoption time and are harder to integrate within the existing stacks.
To fill this gap some NoSql vendors are building SQL access to their systems. Building SQL engine from scratch is a daunting job and frameworks like Apache Calcite can help you with the heavy lifting. Calcite allow you to integrate SQL parser, cost-based optimizer, and JDBC with your NoSql system.
We will walk through the process of building a SQL access layer for Apache Geode (In-Memory Data Grid). I will share my experience, pitfalls and technical consideration like balancing between the SQL/RDBMS semantics and the design choices and limitations of the data system.
Hopefully this will enable you to add SQL capabilities to your prefered NoSQL data system.
Here is a recursive function to check if a list contains an element:
(defun contains (element list)
(cond ((null list) nil)
((equal element (car list)) t)
(t (contains element (cdr list)))))
To check the guest list:
(contains 'robocop guest-list)
This function:
1. Base case: If list is empty, element is not contained - return nil
2. Check if element equals car of list - if so, return t
3. Otherwise, recursively call contains on element and cdr of list
So it will recursively traverse the list until it finds a match or reaches empty list.
File Format Benchmarks - Avro, JSON, ORC, & ParquetOwen O'Malley
Hadoop Summit June 2016
The landscape for storing your big data is quite complex, with several competing formats and different implementations of each format. Understanding your use of the data is critical for picking the format. Depending on your use case, the different formats perform very differently. Although you can use a hammer to drive a screw, it isn’t fast or easy to do so. The use cases that we’ve examined are: * reading all of the columns * reading a few of the columns * filtering using a filter predicate * writing the data Furthermore, it is important to benchmark on real data rather than synthetic data. We used the Github logs data available freely from http://githubarchive.org We will make all of the benchmark code open source so that our experiments can be replicated.
The document provides an introduction to Prof. Dr. Sören Auer and his background in knowledge graphs. It discusses his current role as a professor and director focusing on organizing research data using knowledge graphs. It also briefly outlines some of his past roles and major scientific contributions in the areas of technology platforms, funding acquisition, and strategic projects related to knowledge graphs.
Techniques for Context-Aware and Cold-Start RecommendationsMatthias Braunhofer
Context-aware recommender systems better identify interesting items for users by adapting their suggestions to the specific contextual situations, e.g., to the current weather, if an excursion is to be recommended . But, the cold-start problem may jeopardise the quality of the recommendations: for users, items or contextual situations that are new to the system, recommendations are hard to compute. We have developed a number of novel techniques to tame this problem, and in particular, new hybrid algorithms that combine several, simpler, algorithms in order to exploit their strengths and avoid their weaknesses. We have also developed algorithms for actively identifying the most useful preference information to ask the user in order to bootstrap the system. Our results obtained from a series of offline and online experiments reveal that the proposed techniques can effectively alleviate the cold-start problem of context-aware recommender systems.
HITS and PageRank are algorithms used by search engines to rank web pages. HITS calculates hub and authority scores for each page based on the link structure related to a specific query topic. PageRank assigns each page a single prestige score based on the entire link structure, making it query-independent and resistant to spam. While both aim to identify important pages, HITS does so in a topic-specific manner, whereas PageRank provides a general importance score for each page.
This document provides a tutorial on using the Protege software to build ontologies. It explains that Protege allows constructing domain models and knowledge bases using ontologies. The tutorial then demonstrates how to install Protege, create classes and subclasses, add properties and restrictions, define domains and ranges, and use a reasoner to classify and check the ontology for inconsistencies. Various exercises are presented to help the user learn how to structure information in Protege.
Ontology development in protégé-آنتولوژی در پروتوغهsadegh salehi
This document describes an agenda for an ontology development presentation in Protégé. It discusses the syntactic web and its limitations, as well as the promise of the semantic web to address these issues by adding meaning to web content that is understandable to machines. It outlines two sessions on ontology and OWL basics, Protégé, and developing a pizza ontology in Protégé.
The document discusses several ontology applications in agriculture domains including:
1. A food safety ontology with 1600 concepts for an international food safety portal.
2. A fisheries ontology integrating three systems with 25,000 concepts in English.
3. A journal bibliography ontology with 14 metadata concepts and 1800 instances in 3 languages.
4. External examples including a crop biosecurity ontology cataloging training resources and a crop pest ontology for image searching.
Microsoft Protege Grand Final Pres 6th Maygthorsley
The document outlines a marketing campaign plan involving 6 student groups who will create Facebook pages and communities to promote Windows Phone 7 on their university campuses through events, competitions, sponsored content and press relations in order to engage students and generate buzz around the new product launch. The campaign will utilize television, online, public relations and student ambassador strategies over an 8 week pre-launch period followed by ongoing activities.
Properties and Individuals in OWL: Reasoning About Family Historyrobertstevens65
Slides used in an advanced OWL tutorial in 2012. The tutorial is based on family history and uses OWL individuals as a first class citizen in the learning.
This document provides an overview and agenda for a tutorial on ontology tools. It summarizes the main features and strengths of the KAON and Protégé ontology development tools, including their interfaces, supported formats, and purposes. The tutorial will focus on using the KAON tool suite to create an RDFS-based ontology and Protégé 2000 to create an OWL ontology, with the goal of providing an introduction to these ontology editing tools.
The document discusses the semantic web and ontologies. It provides information on ontology languages like OWL and RDF. It discusses ontology development tools like Protege and how ontologies can be used to define concepts, properties, and relationships in a domain. Ontologies are described as a mechanism for managing requirements specifications by enabling traceability, consistency checking, and automated reasoning about changes. Examples of existing ontologies are also provided.
Pal gov.tutorial4.session5.lab ontologytoolsMustafa Jarrar
This document provides an overview of ontology tools that can be used to build ontologies. It discusses several popular and freely available tools, including Protégé, TopBraid, SWOOP, VisioModeler, NORMA, DogmaModeler, and how each one can be used to create and edit ontologies. It then focuses on using Protégé, providing a quick user guide on how to perform basic tasks like creating classes and object properties, adding domains and ranges, and viewing the ontology structure as a graph.
The document discusses ontologies, including their definition, purpose, and typical engineering process. It provides examples of existing ontologies such as DBpedia, Wikidata, and WordNet. It also outlines some key activities for developing ontologies, such as finding relevant existing ontologies, selecting which to use or extend, and adjusting or expanding them as needed. Some basics of ontology conceptualization are also introduced, such as modeling classes, instances, attributes, and relationships between classes.
This document provides an overview of JessTab, a Protégé plug-in that allows running the Jess rule engine within Protégé. It discusses background on ontologies and rule engines, describes how to install JessTab and Jess, and provides examples of using Jess to programmatically manage ontologies in Protégé through functions like defclass and make-instance, as well as writing Jess rules to reason over ontology instances.
Issues and activities in authoring ontologiesrobertstevens65
The document discusses issues in authoring ontologies and describes a study conducted to better understand the ontology authoring process. The study used an instrumented version of Protégé called Protégé4US to collect interaction logs and eye tracking data from ontology authors. Analysis of the data revealed common patterns of exploration, editing, and reasoning activities. Key findings include the repetitive nature of editing tasks and lack of situational awareness after running reasoning. Design recommendations aim to better support activities like bulk editing and anticipating the effects of reasoning.
This document discusses how ontologies can be used to do biology. It describes how ontologies allow biological data and knowledge to be shared and integrated by providing common definitions and vocabularies. It also discusses how ontologies can enable new discoveries by revealing unexpected connections between different data sources and facilitating automated reasoning. While ontologies help biologists find new things, real biological insights still require human analysis and experimentation. The document uses examples from kidney and urinary system research to illustrate how ontologies are built and applied in bioinformatics.
This document summarizes research into the quality of method reporting in biology experiments. It describes analyzing papers on experiments involving various parasite types like Trypanosoma to see how well they complied with checklists for reporting experimental methods. It was found that compliance was low for reporting details about the parasite, host, and experimental conditions. The document also discusses using text mining to analyze over 15,000 papers on mouse experiments to determine how often they reported sex and age of the subjects. Reporting of these details was found to be inconsistent.
This document discusses developing an ontology for integrating genomic data from multiple sources. It proposes using OWL to represent genomic models and data in a way that allows for semantic queries. Key points include:
- Developing an ontology to represent genetics, genomics, and comparative aspects at different levels of abstraction
- Using OWL to model maps, markers, and their relationships to physical chromosomes and genomic regions
- Performing "local closure" on queries to return all entailed knowledge from the source knowledgebase
- The challenges of developing sophisticated ontologies that reconcile different representations of biological entities
OBOPedia: An Encyclopaedia of Biology Using OBO OntologiesObopedia swat4ls-20...robertstevens65
A talk on OBOPedia (HTTP://www.obopedia.org.uk) given at Semantic Web Applicaitons and Tools for Life Sciences (SWAT4Ls) 2015 in cambridge, UK December 2015
A brief overview to SWRL.
The Semantic Web Rule Language (SWRL) is based on a combination of the OWL DL and OWL Lite sublanguages of the OWL Web Ontology Language with the Unary/Binary Datalog RuleML sublanguages of the Rule Markup Language. It extends the set of OWL axioms to include Horn-like rules. It thus enables Horn-like rules to be combined with an OWL knowledge base.
The state of the nation for ontology developmentrobertstevens65
This document discusses the maturity of ontology development as an engineering discipline. It analyzes ontology development using the Capability Maturity Model (CMM), which assesses the formality and optimization of software development processes. While ontology development has established technologies and methods, it still relies heavily on ad hoc practices. The document argues ontology development would benefit from increased understanding of development processes, tool support for those processes, and the ability to quantitatively measure and manage processes. This would help move ontology development from a reliance on individual expertise to more mature and repeatable engineering practices.
Protégé4US: Harvesting Ontology Authoring Data with ProtégéMarkel Vigo
The inherent complexity of ontologies poses a number of cognitive and perceptual challenges for ontology authors. We investigate how users deal with the complexity of the authoring process by analysing how one of the most widespread ontology development tools (i.e. Protégé) is used. To do so, we build Protégé4US (Protégé for User Studies) by extending Protégé in order to generate log files that contain ontology authoring events. These log files not only contain data about the interaction with the environment, but also about OWL entities and axioms. We illustrate the usefulness of Protégé4US with a case study with 15 participants. The data generated from the study allows us to know more about how Protégé is used (e.g. most frequently used tabs), how well users perform (e.g. task completion times) and identify emergent authoring strategies, including moving down the class hierarchy or saving the cur- rent workspace before running the reasoner. We argue that Protégé4US is an valuable instrument to identify ontology authoring patterns.
This document discusses ontological categories and word classes from a linguistic perspective. It covers topics like nouns and things, countability of nouns, and how word classes are not universal across all languages. For example, some languages like Mandarin Chinese and Yurok do not have an adjective class. The document also notes that while linguists often define word classes based on morphosyntactic properties, ontological categories provide an alternative semantic perspective. The lab session will focus on applying ontological categories like things, situations, and properties to lexical semantics and analyzing word classes like nouns, verbs, and adjectives.
Collaborative Development of Ontologies using BioPortal and WebProtégé Trish Whetzel
The document discusses the integration of WebProtégé and BioPortal to provide a collaborative environment for ontology development. WebProtégé allows simultaneous editing and discussion of ontologies. BioPortal publishes ontologies and collects community feedback through comments. This integrated platform allows ontology editors to see comments in context and update the ontology accordingly.
Collaborative Development of Ontologies using BioPortal and WebProtégé Trish Whetzel
The document discusses the integration of WebProtégé and BioPortal to provide a collaborative environment for ontology development. WebProtégé allows simultaneous editing and discussion of ontologies. BioPortal publishes ontologies and collects community feedback through comments. It also provides analytics. The integration allows editors to see comments in context and make changes, with comments archived once tasks are complete. This provides a full lifecycle of ontology development, feedback, and refinement.
The document discusses the present and future of the OpenOffice.org documentation project. Currently, documentation is scattered across various websites and sources, with outdated and unclear information. Going forward, the project aims to create a central portal for easy user access, ensure content is targeted, up-to-date, and allows contributions from the community. Challenges include legal issues, improving the wiki structure, and combining English and non-English documentation.
Presentation made in the context of the FAO AIMS Webinar titled “Knowledge Organization Systems (KOS): Management of Classification Systems in the case of Organic.Edunet” (http://aims.fao.org/community/blogs/new-webinaraims-knowledge-organization-systems-kos-management-classification-systems)
21/2/2014
The objective of this webinar is to provide a brief overview of the Knowledge Organization Systems (KOS) and the tools used for managing them. The presentation will focus on the management of the multilingual Organic.Edunet ontology as a case study. In this context it will present aspects such as the collaborative work, multilinguality needs and update of the concepts using an online KOS management tool (MoKi).
This document discusses OpenOffice extensions and templates repositories that were migrated from their original hosting to SourceForge in February 2012. It outlines the agenda which includes an overview of the two sites, the migration process, how to create and upload extensions and templates. Statistics on downloads are provided and improvements discussed including anti-spam measures, future plans to update platforms, improve search and integrate more web 2.0 features. The presentation concludes with a request for feedback from the community.
- EndNote is a bibliographic management software that allows users to organize references, search online databases to retrieve citations, and format citations and bibliographies in documents.
- It can be downloaded for free by current HKU staff and students and used on campus and at home. Various tutorials are provided to demonstrate its functions.
- New features in EndNote X include managing PDFs, using different library formats, and improved searching capabilities. Other bibliographic software include Reference Manager, RefWorks, Biblioscape, and Bibliographix, some of which have free versions.
Open Access Week 2017: Life Sciences and Open Sciences - worfkflows and toolsOpenAIRE
This document discusses open science practices for publishing and sharing research outputs like publications, data, code, and software. It covers topics like open access, documenting work, version control, reproducibility, and using platforms and workflows like Docker, Nextflow, and Galaxy to package and share research objects. The overall message is that applying open science principles of transparency, accessibility, and reproducibility can help researchers collaborate and build on each other's work.
WIDOCO: A Wizard for Documenting Ontologiesdgarijo
WIDOCO is a WIzard for DOCumenting Ontologies that guides users through the documentation process of their vocabularies. Given an RDF vocabulary, WIDOCO detects missing vocabulary metadata and creates a documentation with diagrams, human readable descriptions of the ontology terms and a summary of
changes with respect to previous versions of the ontology. The documentation consists on a set of linked enriched HTML pages that can be further extended by end users. WIDOCO is open source and builds on well established Semantic Web tools. So far, it has been used to document more than one hundred ontologies in different domains.
Open Source software grew out of the practice of freely and openly sharing source code across academia and industry from the early days of computer programming. It took off along with the rapid growth of the Internet. Nowadays, open source software runs most of the World Wide Web, as well as the majority of smartphones and supercomputers. Companies are increasing their use of open source, developers continue to adopt open source programming languages and techniques, and society as a whole is being transformed by the principles of open source collaboration at a number of levels, from education to government to popular culture.
La Plata National University is one of the major universities in Argentina with over 90,000 students. It launched the Intellectual Creation Dissemination Service (SeDiCI) in 2003 to publish faculty works. SeDiCI developed the Celsius-DL digital library software and has since expanded to include open access journals and conference proceedings through the Journal Portal and Congress Portal. Workshops and customizations of the Open Journal Systems and Open Conference Systems software help UNLP members publish and organize their works through these new online services.
The document discusses various online tools for effective literature management and reference searching. It introduces popular tools like Mendeley, EndNote and Zotero for building local reference databases and sharing references online. Social bookmarking and networking sites like Diigo, SlideShare and Wikipedia are also covered that allow searching references through tags and connecting with other users.
Wiser Pku Lecture@Life Science School Pkuguest8ed46d
The document discusses various online tools for effective literature management and reference searching. It introduces popular tools like Mendeley, EndNote and Zotero for building local reference databases and sharing references online. Social bookmarking and networking sites like Diigo, SlideShare and Wikipedia are described as useful resources for searching references in a social way through tags and user connections.
How community software supports language documentation and data analysisPeter Bouda
Field linguists have increasingly adopted the latest technologies and tools for language documentation. Their needs have led to remarkable developments in software and archiving, exemplified by work at the MPI in Nijmegen, which leads the innovation cycles that take place in the digital working environments of field linguists. The next step in research is now the analysis and theoretical exploitation of the huge amount of data that has been collected in numerous language documentation projects that use these environments. This research will also rely on computer-based strategies, as data is instantly available in digital formats.
In this talk I will introduce some of the lesser known tools and software packages for annotation and analysis tasks. Some of these tools were created within DOBES projects and/or as community projects by small teams; they can be combined with well-known tools like ELAN or Toolbox to give researchers access to their data. I will focus on how a combination of simple, special purpose tools makes researchers more productive and how existing software libraries allow scientific projects to create their own, task-specific software tools that they can tailor to their own needs.
The document discusses collaborative development models and their applications beyond just software. It notes that:
1) Many software projects already involve non-code artifacts like documentation and graphics that can be collaboratively developed.
2) Experiments with collaborative models in non-software domains like Wikipedia have shown quality on par with traditional models when evaluated identically.
3) While software is uniquely suited due to its modular structure, many non-software projects also have modular structures that enable collaborative development through platforms like wikis. The lack of unifying platforms is a main difference between domains.
DSpace-CRIS: a CRIS enhanced repository platformAndrea Bollini
International Conference on Economics and Business Information 19 to 20 April 2016 in Berlin
This presentation introduces you to the version 5.5.0 of the DSpace-CRIS extension. With such extension you can capture the full picture of the research activities conduct in your institution and their context. It enables to showcase the experts, the facilities, the services and much more to attract funding, facilitate collaborations and curate the scientific reputation of your Institution.
A lecture discussing the use of some popular Web 2.0 tools for online collaboration.
Originally posted as a Google Presentation, hyperlinks lost in conversion:
http://docs.google.com/Presentation?id=dgsbm7jn_35dcmp8rcj
Collaborative development models have been successfully applied to open source software projects. However, traditionally these models were thought to be unable to produce secure, high-quality software. Some experiments applying these models to non-software projects like Wikipedia have shown results comparable to closed development. The collaborative structure of many projects, regardless of type, is similar to software with modular components and public versioning. For collaborative models to work outside software, unifying platforms are important, and constraints like in physical objects limit participation.
Research Objects for improved sharing and reproducibilityOscar Corcho
Presentation about the usage of Research Objects to improve scientific experiment sharing and reproducibility, given at the Dagstuhl Perspective Workshop on the intersection between Computer Sciences and Psychology (July 2015)
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
4. What is Protégé?
• An open-source ontology editor
• developed at Stanford University
• has more than 200,00 registered users
• has dozens of plugins for
• visualization
• inference
• import and export
• ….
• has an API for developers
5. A bit of Protégé history
• Started more than 20 years ago
• Has gone through many iterations
• Was the first editor to support OWL 1
• Informed the design of OWL 2
• Has a thriving user community:
• conferences
• mailing list
• short courses
8. WebProtégé
•A Web-based application
•edit ontologies in your Web browser
•nothing to install
•Supports distributed editing
•multiple editors can make changes at the
same time
•Includes many collaboration features
•discussion, watches, feeds
12. Collaborative Ontology Development
Collaboration: several users contribute to the
development of one ontology
– Small group → larger community
– Larger ontologies that concern a certain community
– Individual process → social process
Each community does it its own way
13. Use cases of collaborative development in
biomedical domain
• Gene Ontology (GO)
• NCI Thesaurus
• BiomedGT
• OBI, BIRNLex, RadLex
• Open Biomedical Ontologies (OBO)
• International Classification:
– of Diseases (ICD-11)
– of Traditional Medicine (ICTM)
– of Patient Safety (ICPS)
14. The NCI Thesaurus collaborative
development process
●
Simultaneous editing in Protégé
clients
●
Custom UI for restricting user
input and enforcing business
rules
●
Development cycle begins after
baseline
●
~20 full-time editors making
changes; 1 “lead editor” who
approves the changes, and
assigns new tasks
●
Released version on NCI
website and BioPortal
Reference ontology for cancer biology, translational science, and clinical
oncology
15. ICD-11
● 11th Revision of the International
Classification of Diseases
● Over 10.000 categories used for coding,
billing, statistics, policy making all over the
world
● Collaborative and international effort
● Current version: published as books
● Goal for the new version: use a more formal
representation and published in electronical
format; use Web-based collaboration and
social platforms for editing
16. Construction of ICD-10:
Revision Process in the 20th
Century
● 8 Annual Revision Conferences (1982
- 89)
● 17 – 58 Countries participated
– 1- 5 person delegations
– Mainly Health Statisticians
● Manual curation
– List exchange
– Index was done later
● "Decibel” Method of discussion
● Output: Paper Copy
● Work in English only
● Limited testing in the field
17. ICD-11 process today
● Over 250 domain experts from around the world
● Organized in groups, which edit different parts of the ontology
18. ICD-11 process today (cont.)
● Each night a snapshot of the commonly edited ontology is
published in a public platform to encourage feedback from
the larger community
http://apps.who.int/classifications/icd11/browse/f/en
● Editorial workflow
● Centrally overseen by WHO
● Peer-reviewed process for the content and structure
● WebProtégé used as the collaborative ontology
development platform
19. Other ways of collaborating: Wikis
● Wikis are well known; Wikipedia
● Semantic Wikis – add semantic extensions to the wiki
platforms
● Assign a wiki page to an entity in the ontology (e.g. the
class “Mountain”)
● Export/import RDF
21. The challenge with wikis
Source: Hoehndorf, Robert, et al. "BOWiki: an ontology-based wiki for annotation of data and integration of knowledge in biology."
BMC bioinformatics 10.Suppl 5 (2009): S5.
24. Other collaboration processes
● Use source control repositories – SVN, CVS
– Text based mechanisms
– Hard to merge local copies in the shared copy
● Locking mechanisms (lock parts of an ontology for editing)
● Use specialized (domain dependent) ontology repositories,
e.g., BioPortal
25. BioPortal
● An open repository of biomedical ontologies developed by NCBO at
Stanford
● Publishing of ontologies, versioning (over 350 ontologies)
● Discussions and structured proposals
● Mappings, views
● Storing metadata
● Search over all ontologies
● Browsing different versions of an ontology
● All content and functionality also available as REST Web services →
mash-up of applications
● Technology is domain independent
● http://bioportal.bioontology.org
29. Useful features for collaboration
● Tools for discussion and reaching consensus
– Add notes to ontology entities (classes, properties, individuals,
axioms)
– Add reviews and change proposals anywhere in the ontology
– Document the decision process and final decisions
● Complete Change history
– Establish provenance
– Retrieve ontology snapshots at any time
– Implement different conflict resolution mechanisms
● Personalized views of an ontology based on:
– User’s role and tasks
– User’s level of expertise
30. Useful features for collaboration (cont.)
● User roles and access control
– Fine-grained control for editing and viewing rights
– Sharing of ontologies
● Publishing released versions of an ontology in a central
location,e.g. a repository
● Scalability, reliability and robustness
34. Creating an Account II
Email address - used for notifications such as ontology changes
User name - displayed next to changes you make and notes that you post
35. The “Home Screen”
Side bar
Project list. Click project
name to open
Create project
Download project
Sign In/Sign Out
Trash projectUpload project
36. The Side Bar
All public projects plus your projects that are not in the trash
Your projects that are in the trash
Only projects owned by you that are not in the trash
37. Projects
A project encompasses: A collection of ontologies
Notes & discussions and watches
Some user interface settings
Some sharing settings
A list of revisions and a log of changes
38. Creating a Project
Create New Project
Project name - does not need to be unique
Project description - appears in the project list
39. Uploading a Project
Upload Project
Project name - does not need to be unique
Project description - appears in the project list
Local OWL file name
41. Public Projects
➊ Select public
➋ Assign permissions for anyone including guests
➌ Assign more fine-grained access for specific users
Enter names in list and press “Add”
42. Private Projects
➊ Select public
Access is restricted to specific users
➋ Assign more permissions for specific users.
Enter names in list and press “Add”
43. Class tree Editor (similar for properties and individuals) Notes & Discussions
Project feed
Editing Class Descriptions
45. Editing Class Descriptions
Display name - corresponds to the value of rdfs:label here
IRI - Internationalized Resource Identifier. Auto-generated, globally unique
“Property values”
(Class expressions under the hood
owl:subClassOf)
Annotation assertions
Values can be class names, datatype names,
individual names, numbers, dates and strings
Language editor for plain literals
Delete row
47. On-the-Fly Creation
New property warning
(helps prevent typos!)
Press the tab key and enter value to create property
(property type will be determined from the value)
49. Display name - corresponds to the value of rdfs:label here
IRI - Internationalized Resource Identifier. Auto-generated, globally unique
“Property values”
(Annotations, property assertions or
class expressions under the hood -
owl:subClassOf)
Type assertions
(rdf:type)
Values can be class names, datatype names,
individual names, numbers, dates and strings
Delete row
Same individuals
(owl:sameAs)
Editing Individual Descriptions
50. Icon Cheat Sheet
Class
Individual (named)
Datatype (xsd:integer, xsd:double etc.)
Property (object/data property)
Annotation property
Number
Date-Time
Literal
Link (http:)
IRI
53. ModellingTask
Build an ontology to describe an online newspaper
or news website e.g. www.nyt.com or www.bbc.com
Goal: Become familiar with WebProtégé
and some aspects of collaborative ontology editing
54. Content
Articles:
title, author, date published, edited by, keywords/topics,
published in section, media (pictures, video), external links
etc.
Advertisements:
Standard ad, personal ad, Service ad etc.
Model different kinds of articles and their properties. For example,
55. Structure
Newspaper:
date published, issue, front matter etc.
Sections:
Domestic News,World News, Editorial, Magazine, Letters,
Commentary,Television Listings,Advertisements,
Appointments/Jobs, Sport, Business etc.
Sections and subsections
Model the structure of a news paper - different sections and how they
fit together. For example,
56. People
Employees:
Columnist, Editor, Section Editor, Reporter, International
Reporter, Manager
name, contact details: email, phone number, role
Other people:
Politician, President,Actor etc. Individual people, e.g.
Barack Obama.
Model the people who contribute to the news paper and people who
are the subject of articles. For example,
57.
58. Custom entry forms for editing the ontology
content
● Easy to create user interfaces for the domain experts
● Use common entry forms, but still keep the ontology
“intelligence” behind it
● A form widget (e.g., text field) is linked to a property in the
ontology
● Easy to create custom forms with different views for
different users
● Hides complex ontology stuff
59. Form configuration in WebProtégé
Form-based editing and configuration of the user interface for the development of ICD-11
http://icatdemo.stanford.edu
61. Importing BioPortal terms into
WebProtégé
(1) Search term in BioPortal ontologies
(2) Get
search
results
(3) Browse
details of
results
(4) Import into WebProtégé with
single click
62. WebProtégé – Make Up
Protégé Collaboration
Framework
WebProtégé
WebProtégé Server
GWT RPC
Server side
Client side
Java
Java
Java at
development time
JavaScript at
run- time
2 parts: server and client
Server is completely
implemented in Java and makes
API calls to the OWL-API and
other libraries
Client side is developed in Java,
and later compiled by GWT into
JavaScript
Communication between server
client is done via GWT RPC or
simple HTTP calls
63. WebProtégé is pluggable
WebProtégé User Interface
(GWT)
Portlets
Event manager Other managers
WebProtégé Server (Java)
Access policies
service
...
Ontology
Service
Notes and
changes Service
pluggable
pluggable
64. Extending WebProtégé
Plug-in infrastructure very similar to Protégé's: create your
own tabs and portlets
Extend: AbstractTab or AbstractEntityPortlet
Implement your own RPCs, if needed
Reuse existing portlet code
Writing a tab – as easy as creating an empty class that
extends AbstractTab
http://protegewiki.stanford.edu/wiki/WebProtegeImplementationGuide
65. Resources
●
Online WebProtégé server: http://webprotege.stanford.edu
●
WebProtégé documentation:http://protegewiki.stanford.edu/wiki/WebProtege
●
WebProtégé paper: “WebProtégé: A Collaborative Ontology Editor and Knowledge
Acquisition Tool for the Web”, Tania Tudorache, Csongor Nyulas, Natalya F. Noy,
Mark A. Musen, Semantic Web Journal (SWJ) 4 (Number 1 / 2013), 89 - 99
●
WebProtégé in use: “Will Semantic Web Technologies Work for the Development of
ICD-11?”, T. Tudorache, S. M. Falconer, C. I. Nyulas, N. F. Noy, M. A. Musen. The 9th
International Semantic Web Conference, ISWC 2010 (In-Use track), Shanghai,
China, Springer. Published in 2010.
http://bmir.stanford.edu/file_asset/index.php/1646/BMIR-2010-1427.pdf
●
Other References: http://protegewiki.stanford.edu/wiki/WebProtege#References