The document discusses the basics of linked data modeling, including defining classes and properties to describe resources, creating instances of classes, and interlinking related data across datasets using properties like rdfs:seeAlso and owl:sameAs. It explains key concepts like URIs, RDF, and SPARQL and compares linked data modeling to traditional database modeling in terms of tables, columns, rows, and relations. The goal of linked data modeling is to publish structured data that can be interlinked to become more useful and discoverable on the semantic web.
2017년 4월에 진행된 도서관최신동향 과정에 있었던 발표자료입니다.
서지 분야에서의 Linked Data의 개념과 활용에 대한 내용을 담고 있습니다.
구체적으로는 아래와 같은 내용을 포함합니다.
- Linked Data란 무엇인가?
- 왜 도서관에서 Linked Data를 이야기하는가?
- Linked Data를 누가 쓰고 있나?
2017년 4월에 진행된 도서관최신동향 과정에 있었던 발표자료입니다.
서지 분야에서의 Linked Data의 개념과 활용에 대한 내용을 담고 있습니다.
구체적으로는 아래와 같은 내용을 포함합니다.
- Linked Data란 무엇인가?
- 왜 도서관에서 Linked Data를 이야기하는가?
- Linked Data를 누가 쓰고 있나?
This is a lecture note #10 for my class of Graduate School of Yonsei University, Korea.
It describes SPARQL to retrieve and manipulate data stored in Resource Description Framework format
RDF is a general method to decompose knowledge into small pieces, with some rules about the semantics or meaning of those pieces. The point is to have a method so simple that it can express any fact, and yet so structured that computer applications can do useful things with knowledge expressed in RDF.
Libraries around the world have a long tradition of maintaining authority files to assure the consistent presentation and indexing of names. As library authority files have become available online, the authority data has become accessible -- and many have been published as Linked Open Data (LOD) -- but names in one library authority file typically had no link to corresponding records for persons and organizations in other library authority files. After a successful experiment in matching the Library of Congress/NACO authority file with the German National Library's authority file, an online system called the Virtual International Authority File was developed to facilitate sharing by ingesting, matching, and displaying the relations between records in multiple authority files.
The Virtual International Authority File (VIAF) has grown from three source files in 2007 to more than two dozen files today. The system harvests authority records, enhances them with bibliographic information and brings them together into clusters when it is confident the records describe the same identity. Although the most visible part of VIAF is a HTML interface, the API beneath it supports a linked data view of VIAF with URIs representing the identities themselves, not just URIs for the clusters. It supports names for person, corporations, geographic entities, works, and expressions. With English, French, German, Spanish interfaces (and a Japanese in process), the system is used around the world, with over a million queries per day.
Speaker
Thomas Hickey is Chief Scientist at OCLC where he helped found OCLC Research. Current interests include metadata creation and editing systems, authority control, parallel systems for bibliographic processing, and information retrieval and display. In addition to implementing VIAF, his group looks into exploring Web access to metadata, identification of FRBR works and expressions in WorldCat, the algorithmic creation of authorities, and the characterization of collections. He has an undergraduate degree in Physics and a Ph.D. in Library and Information Science.
Development of Semantic Web based Disaster Management SystemNIT Durgapur
Semantic Web model In the field of disaster management to structurise the data such that any information needed during emergency will be easily available.
Modeling Webinar: State of the Union for Data Innovation - 2016DATAVERSITY
Karen declared 2015 as the Year of Data. And with future outlooks, it's still looking great for data in 2016. As we start the new year, let's look at some of the trends and predictions coming from the data industry. We'll include data modeling topics, but also look to the types of innovations in the data world that will influence our data architectures, jobs and tools.
Some have been around for a while but just now gaining traction and some are just now rolling out: Machine Learning, Internet of Things, New and NoSQL DBs, Data Wrangling, Data Virtualization and more.
This is a lecture note #10 for my class of Graduate School of Yonsei University, Korea.
It describes SPARQL to retrieve and manipulate data stored in Resource Description Framework format
RDF is a general method to decompose knowledge into small pieces, with some rules about the semantics or meaning of those pieces. The point is to have a method so simple that it can express any fact, and yet so structured that computer applications can do useful things with knowledge expressed in RDF.
Libraries around the world have a long tradition of maintaining authority files to assure the consistent presentation and indexing of names. As library authority files have become available online, the authority data has become accessible -- and many have been published as Linked Open Data (LOD) -- but names in one library authority file typically had no link to corresponding records for persons and organizations in other library authority files. After a successful experiment in matching the Library of Congress/NACO authority file with the German National Library's authority file, an online system called the Virtual International Authority File was developed to facilitate sharing by ingesting, matching, and displaying the relations between records in multiple authority files.
The Virtual International Authority File (VIAF) has grown from three source files in 2007 to more than two dozen files today. The system harvests authority records, enhances them with bibliographic information and brings them together into clusters when it is confident the records describe the same identity. Although the most visible part of VIAF is a HTML interface, the API beneath it supports a linked data view of VIAF with URIs representing the identities themselves, not just URIs for the clusters. It supports names for person, corporations, geographic entities, works, and expressions. With English, French, German, Spanish interfaces (and a Japanese in process), the system is used around the world, with over a million queries per day.
Speaker
Thomas Hickey is Chief Scientist at OCLC where he helped found OCLC Research. Current interests include metadata creation and editing systems, authority control, parallel systems for bibliographic processing, and information retrieval and display. In addition to implementing VIAF, his group looks into exploring Web access to metadata, identification of FRBR works and expressions in WorldCat, the algorithmic creation of authorities, and the characterization of collections. He has an undergraduate degree in Physics and a Ph.D. in Library and Information Science.
Development of Semantic Web based Disaster Management SystemNIT Durgapur
Semantic Web model In the field of disaster management to structurise the data such that any information needed during emergency will be easily available.
Modeling Webinar: State of the Union for Data Innovation - 2016DATAVERSITY
Karen declared 2015 as the Year of Data. And with future outlooks, it's still looking great for data in 2016. As we start the new year, let's look at some of the trends and predictions coming from the data industry. We'll include data modeling topics, but also look to the types of innovations in the data world that will influence our data architectures, jobs and tools.
Some have been around for a while but just now gaining traction and some are just now rolling out: Machine Learning, Internet of Things, New and NoSQL DBs, Data Wrangling, Data Virtualization and more.
The Information Technology have led us into an era where the production, sharing and use of information are now part of everyday life and of which we are often unaware actors almost: it is now almost inevitable not leave a digital trail of many of the actions we do every day; for example, by digital content such as photos, videos, blog posts and everything that revolves around the social networks (Facebook and Twitter in particular). Added to this is that with the "internet of things", we see an increase in devices such as watches, bracelets, thermostats and many other items that are able to connect to the network and therefore generate large data streams. This explosion of data justifies the birth, in the world of the term Big Data: it indicates the data produced in large quantities, with remarkable speed and in different formats, which requires processing technologies and resources that go far beyond the conventional systems management and storage of data. It is immediately clear that, 1) models of data storage based on the relational model, and 2) processing systems based on stored procedures and computations on grids are not applicable in these contexts. As regards the point 1, the RDBMS, widely used for a great variety of applications, have some problems when the amount of data grows beyond certain limits. The scalability and cost of implementation are only a part of the disadvantages: very often, in fact, when there is opposite to the management of big data, also the variability, or the lack of a fixed structure, represents a significant problem. This has given a boost to the development of the NoSQL database. The website NoSQL Databases defines NoSQL databases such as "Next Generation Databases mostly addressing some of the points: being non-relational, distributed, open source and horizontally scalable." These databases are: distributed, open source, scalable horizontally, without a predetermined pattern (key-value, column-oriented, document-based and graph-based), easily replicable, devoid of the ACID and can handle large amounts of data. These databases are integrated or integrated with processing tools based on the MapReduce paradigm proposed by Google in 2009. MapReduce with the open source Hadoop framework represent the new model for distributed processing of large amounts of data that goes to supplant techniques based on stored procedures and computational grids (step 2). The relational model taught courses in basic database design, has many limitations compared to the demands posed by new applications based on Big Data and NoSQL databases that use to store data and MapReduce to process large amounts of data.
Course Website http://pbdmng.datatoknowledge.it/
Contact me for other informations and to download
LDM Slides: How Data Modeling Fits into an Overall Enterprise ArchitectureDATAVERSITY
Enterprise Architecture (EA) provides a visual blueprint of the organization, and shows key interrelationships between data, process, applications, and more. By abstracting these assets in a graphical view, it’s possible to see key interrelationships, particularly as it relates to data and its business impact across the organization.
Join this webinar for a discussion on how a data model can be combined with an overall enterprise architecture for enhanced business value and success.
LDM Webinar: Data Modeling & Business IntelligenceDATAVERSITY
Business Intelligence (BI) is a valuable way to use information to show the overall health and performance of the organization. At its core is quality, well-structured data that allows for successful reporting and analytics. A data model helps provide both the business definitions as well as the structural optimization needed for successful BI implementations.
Join this webinar to see how a data model underpins business intelligence and analytics in today’s organization.
Lessons in Data Modeling: Why a Data Model is an Important Part of Your Data ...DATAVERSITY
Data can provide tremendous value to an organization in today’s information-driven economy. New customer insights, better efficiency, and new product innovation are just some of the ways organizations are obtaining value through data. But in order to achieve this value, a strong data architecture is required to ensure that the data infrastructure runs smoothly, while at the same time aligning with business needs and corporate culture. A Data Strategy can assist in building a data architecture foundation through:
Identifying business requirements, rules & definitions via a business-centric data model
Creating a data inventory & integrating disparate data sources
Building a technical data architecture through data models & related artifacts
Coordinating the people, processes and culture necessary for success
Identifying tools & technology needed for creating & maintaining high quality data
The recent focus on Big Data in the data management community brings with it a paradigm shift—from the more traditional top-down, “design then build” approach to data warehousing and business intelligence, to the more bottom up, “discover and analyze” approach to analytics with Big Data. Where does data modeling fit in this new world of Big Data? Does it go away, or can it evolve to meet the emerging needs of these exciting new technologies? Join this webinar to discuss:
Big Data –A Technical & Cultural Paradigm Shift
Big Data in the Larger Information Management Landscape
Modeling & Technology Considerations
Organizational Considerations
The Role of the Data Architect in the World of Big Data
An ontology is a computational artifact used to describe a conceptualization of some part of the world via precise, descriptive statements. In this presentation, we discuss the features of the W3C's Ontology Web Language (OWL) and how it can be used to reduce ambiguity in the semantics (i.e., the meaning) of Data Dictionary terminology.
Linked data for Libraries, Archives, Museumsljsmart
General introduction to Linked Data concepts presented to Maryland Library Association Technical Services Division at "Tech Services on the Edge" forum
This presentation covers the whole spectrum of Linked Data production and exposure. After a grounding in the Linked Data principles and best practices, with special emphasis on the VoID vocabulary, we cover R2RML, operating on relational databases, Open Refine, operating on spreadsheets, and GATECloud, operating on natural language. Finally we describe the means to increase interlinkage between datasets, especially the use of tools like Silk.
A lecture/conversation focusing on the first 12 years of Semantic Web - delivered on February 21, 2012.
See http://j.mp/SWIntro for more details. More detailed course material is at http://knoesis.org/courses/web3/
One day workshop Linked Data and Semantic WebVictor de Boer
As taught at UNIMAS July 2019. based on a three day summer school by Knud Hinnerk Moeller and Victor de Boer. Includes hands on excercises using SWI-Prolog ClioPatria
What Are Links in Linked Open Data? A Characterization and Evaluation of Link...Armin Haller
Linked Open Data promises to provide guiding principles to publish interlinked knowledge graphs on the Web in the form of findable, accessible, interoperable, and reusable datasets. In this talk I argue that while as such, Linked Data may be viewed as a basis for instantiating the FAIR principles, there are still a number of open issues that cause significant data quality issues even when knowledge graphs are published as Linked Data. In this talk I will first define the boundaries of what constitutes a single coherent knowledge graph within Linked Data, i.e., present a principled notion of what a dataset is and what links within and between datasets are. I will also define different link types for data in Linked datasets and present the results of our empirical analysis of linkage among the datasets of the Linked Open Data cloud. Recent results from our analysis of Wikidata, which has not been part of the Linked Open Data Cloud, will also be presented.
JSP 프로그래밍 #02 서블릿과 JSP 시작하기
2.1 톰캣 애플리케이션 만들기 (온라인 강의: https://youtu.be/04LIGWKCFjY)
2.2 간단한 서블릿 만들기 (온라인 강의: https://youtu.be/4ajw5EsxYE8)
2.3 간단한 JSP 만들기 (온라인 강의: https://youtu.be/6h-qH8pGdT8)
2.4 간단한 자바빈즈 만들기 (온라인 강의: https://youtu.be/TlgXkAWi1sc)
JSP 프로그래밍 #01 웹 프로그래밍
1.1 웹 (온라인 강의: https://youtu.be/qDZXXHhMr4A)
1.2 서블릿 (온라인 강의: https://youtu.be/a8hHeUhbz2k)
1.3 JSP(Java Server Page) (온라인 강의: https://youtu.be/Q4ezLP6KLwM)
1.4 프로그래밍을 위한 환경 설정 (온라인 강의: https://youtu.be/k2eR6gLULA8)
2018년 7월 5일에 있었던 한국인터넷거버넌스포럼(KrIGF)에서 발표한 "오픈 데이터와 인공지능" 발표자료입니다.
다음과 같은 내용을 담고 있습니다.
* 오픈데이터의 정의
* 오픈데이터의 중요성
* 인공지능
* 인공지능에서 데이터의 중요성
* 제한된 데이터 환경에서의 문제점
* 인공지능을 위한 오픈데이터의 중요성
* 더 나은 인공지능 시대를 위한 제언
Development of Twitter Application #8 - Streaming APIMyungjin Lee
This series of slides describes how to develop a twitter application.
This slide shows how to search tweets using Twitter Search RESTful Open API and how to implement it using Twitter4J.
The Semantic Web #9 - Web Ontology Language (OWL)Myungjin Lee
This is a lecture note #9 for my class of Graduate School of Yonsei University, Korea.
It describes Web Ontology Language (OWL) for authoring ontologies.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Safalta Digital marketing institute in Noida, provide complete applications that encompass a huge range of virtual advertising and marketing additives, which includes search engine optimization, virtual communication advertising, pay-per-click on marketing, content material advertising, internet analytics, and greater. These university courses are designed for students who possess a comprehensive understanding of virtual marketing strategies and attributes.Safalta Digital Marketing Institute in Noida is a first choice for young individuals or students who are looking to start their careers in the field of digital advertising. The institute gives specialized courses designed and certification.
for beginners, providing thorough training in areas such as SEO, digital communication marketing, and PPC training in Noida. After finishing the program, students receive the certifications recognised by top different universitie, setting a strong foundation for a successful career in digital marketing.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
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
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
1. Linked Data Modeling
for Beginner
Dr. Myungjin Lee
http://www.industryleadersmagazine.com/wp-content/uploads/2011/03/j0401617.jpg
1
2. Linked Data
• Linked data describes a method of publishing
structured data so that it can be interlinked and become
more useful.
The Semantic Web isn't just about putting data
on the web. It is about making links, so that a
person or machine can explore the web of data.
With linked data, when you have some of it,
you can find other, related, data.
- A roadmap to the Semantic Web by Tim Berners-Lee
2
3. Four Principles of Linked Data
1. Use URIs to identify things.
2. Use HTTP URIs so that these things can be referred to
and looked up ("dereferenced") by people and user
agents.
3. Provide useful information about the thing when its
URI is dereferenced, using standard formats such as
RDF/XML.
4. Include links to other, related URIs in the exposed
data to improve discovery of other related information
on the Web.
3
4. 5 Star Linked Data
4
★ Available on the web (whatever format) but with an open
licence, to be Open Data
★★ Available as machine-readable structured data (e.g. excel
instead of image scan of a table)
★★★ as (2) plus non-proprietary format (e.g. CSV instead of
excel)
★★★★ All the above plus, Use open standards from W3C (RDF
and SPARQL) to identify things, so that people can point at
your stuff
★★★★★ All the above, plus: Link your data to other people’s data to
provide context
5. What do we know?
an elemental syntax
for content structure
within documents
a simple language
for expressing data models,
which refer to objects ("resources")
and their relationships
more vocabulary
for describing properties and classes
a vocabulary for describing
properties and classes
of RDF-based resources
a protocol and query
language
for semantic web data
sources
to exchange rules
between many
"rules languages"
a string of characters used to identify a name or a resource
5
6. URI (Uniform Resource Identifier)
Myungjin Lee
841002-1045617
identifier
name
resident registration number
http://www.semantics.kr/person/mjLee
identifier in the web
6
7. RDF (Resource Description Framework)
• a general method for conceptual description or
modeling of information that is implemented in web
resources, using a variety of syntax formats
has wife
7
http://semantics.kr/myungjinlee http://semantics.kr/hye-jinhan
http://semantics.kr/rel/hasWife
Subject
URI reference
Predicate
URI reference
Object
URI reference or Literal
Triple
8. RDFS (RDF Schema)
• to define classes and properties that may be used to
describe classes, properties and other resources
8
has wife
♂ ♀
is a is a
Male Female
Person
subset ofsubset of
9. OWL (Web Ontology Language)
• knowledge representation languages for authoring
ontologies
• when you need more expressiveness,
– such as,
9
Man Woman∩ = Ø
Person Person
descendant
Person
descendant
descendant
Husband Wife
1:1
10. SPARQL
• Why do we need a query language for RDF?
– Why de we need a query language for RDB?
– to get to the knowledge from RDF
• SPARQL Protocol and RDF Query Language
– to retrieve and manipulate data stored in Resource
Description Framework format
– to use SPARQL via HTTP
10
PREFIX foaf: <http://xmlns.com/foaf/0.1/>
SELECT ?name ?email
WHERE {
?person a foaf:Person.
?person foaf:name ?name.
?person foaf:mbox ?email.
}
RDF
Knowledge
Base
?name ?email
Myungjin Lee mjlee@li-st.com
Gildong Hong gildong@daum.net
Grace Byun grace@naver.com
11. Database and Linked Data Modeling
• Database Modeling
• Linked Data Modeling
11
Database
Modeling
Linked Data
Modeling≒
Understanding
Business Process
Extracting
Entities
Discovering
Relations
Defining
Attributes
Determine
Scope
Consider
Reuse
Enumerate
Terms
Define
Classes
Define
Properties
Create
Instances
13. Class
• sets, collections, concepts, or kinds of things
• Which one can be a class?
13
♂
MaleMyungjin Lee
Class
14. Comparing with Database
• Table ≒ Class
14
rrn name affiliation
841002-1045617 Myungjin Lee 10
410203-3983612 Gildong Hong 20
841105-2056143 Grace Byun 10
Person Table
Person Class
sid sname
10 Yonsei Univ.
20 Seoul Univ.
School Table
School Class
18. Label and Comment
• rdfs:label
– to provide a human-readable version of a resource's name
• rdfs:comment
– to provide a human-readable description of a resource
18
rdfs:label
Person person
a living human
rdfs:comment
28. Property Restrictions
• rdfs:domain
– to state that any resource that has a given property is an
instance of one or more classes
• rdfs:range
– to state that the values of a property are instances of one or
more classes
28
Subject Predicate Object
has wife? ?
domain:
what class
for subject
range:
what class
for object
29. Comparing with Database
29
CREATE TABLE School {
sid number(2) primary key
sname varchar(50)
}
range of ‘sname’
‘sname’ property
domain of ‘sname’
30. Declaration of Property Restrictions
30
rdfs:range
rdf:Property
Male
hasWife
rdf:type
Female
rdfs:domain
MyungjinLee Suji
hasWife
rdf:type rdf:type
33. Two Types of Property
• Object Property
– relations between instances of two classes
• Datatype Property
– relations between instances of classes and literals and XML
Schema datatypes
33
has wife
age
30
Object Property
Datatype Property
34. Comparing with Database
34
CREATE TABLE Person {
rrn varchar(14) primary key
name varchar(10)
FOREIGN KEY (affiliation) REFERENCES school(sid)
}
rrn name affiliation
841002-1045617 Myungjin Lee 10
410203-3983612 Gildong Hong 20
841105-2056143 Grace Byun 10
Person Table
sid sname
10 Yonsei Univ.
20 Seoul Univ.
School Table
Datatype Property ObjectProperty
39. Transitive Property
• If a property, P, is specified as transitive then for any x, y,
and z:
• P(x, y) and P(y, z) implies P(x, z)
• Which one can be a Transitive Property?
39
ancestorhasParent
Transitive Property
41. Symmetric Property
• If a property, P, is tagged as symmetric then for any x
and y:
• P(x, y) iff P(y, x)
• Which one can be a Transitive Property?
41
friend
MyungjinLee Peter
owl:SymmetricPropertyfriend
rdf:type
friend
hasWifefriend
42. Functional Property
• If a property, P, is tagged as functional then for all x, y,
and z:
• P(x, y) and P(x, z) implies y = z
• Which one can be a Transitive Property?
42
age
MyungjinLee
owl:FunctionalPropertyage
rdf:type
30
friendage
44. inverseOf
• If a property, P1, is tagged as the owl:inverseOf P2,
then for all x and y:
• P1(x, y) iff P2(y, x)
44
hasParent
MyungjinLee
hasParent
owl:inverseOf
hasChild
Kwangsu
hasChild
47. Comparing with Database
• Row ≒ Individual
47
rrn name affiliation
841002-1045617 Myungjin Lee 10
410203-3983612 Gildong Hong 20
841105-2056143 Grace Byun 10
Person Table
sid sname
10 Yonsei Univ.
20 Seoul Univ.
School Table
Individual of Person Class
Individual of School Class
51. Interlinking
• rdfs:seeAlso
– to indicate a resource that might provide additional
information about the subject resource
• owl:sameAs
– to declare two individuals to be identical
51
My Dataset
MyungjinLee •
DBPedia Dataset
• myung-jin_lee
owl:sameAs