INFO 287-10
Seminar in Information Science
Topic: Linked Data (2 Units)
Summer 2021 Syllabus

Dr. Lei Zhang
E-mail
Office Hours: Email or Zoom by appointment 

Syllabus Links
Textbooks
CLOs
Competencies
Prerequisites		 Resources
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Canvas Information: Courses will be available beginning Tuesday, June 1st unless you are taking an intensive or a one-unit or two-unit class that starts on a different day. In that case, the class will open on the first day that the class meets. 

This course runs from June 7 - August 2. It will be available on Canvas on June 7.

You will be enrolled in the Canvas site automatically.

Course Description

With the linked data principles, the valuable data that reside in libraries, archives, and museums can be made linkable, searchable, and usable on the Web. Linked Data has been adopted widely and has a profound influence on the information professions. 

This course introduces the principles and applications of linked data for organizing, managing, and sharing data of libraries, archives, and museums. An overview of the linked data vocabularies, standards, and approaches, including the basis of linked data RDF model, Web Ontology Language, and SPARQL query language, the metadata element sets and value vocabularies in linked data format, the Library of Congress and OCLC models for library linked data, and the linked data projects and practices in cultural heritage institutions.

Course Requirements

Assignments 

The four exercises are to gain hands-on experience working with linked data, completed with the use of free tools. Use case study is to review the selected use cases in libraries and other cultural heritage institutions and write an essay individually or in pairs. No programming background or coding skills are required. Some exposure to cataloging, metadata, and vocabulary control may be helpful. 

All assignments are due by 11:59 pm Pacific Time on the due date. Grades will be reduced for late work by ten percent per day late. Please contact the instructor prior to a deadline in cases of illness or emergency. 

Course Calendar

Week Topics Assignments

Week 1

June 7-13 

 Introduction to Semantic Web and Linked Data  Introductions due June 13 

Week 2

June 14-20

 RDF data model and serializations Exercise 1 due June 20

Week 3

June 21-27 

OWL Web Ontology Language 

Ontologies

 Exercise 2 due June 27 

Week 4

June 28-July 4  

SPARQL query language

Linked data for authority files

  

Week 5

July 5-11

Linked data for controlled vocabularies, SKOS 

 Exercise 3 due July 11 

Week 6

July 12-18  

Linked data for bibliographic data, BIBFRAME  

  

Week 7

July 19-25 

Linked data for metadata, Schema.org

 Exercise 4 due July 25

Week 8

July 26-August 2 

 Use cases in cultural heritage and other domains

Use case study due August 2

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Course Workload Expectations

Success in this course is based on the expectation that students will spend, for each unit of credit, a minimum of forty-five hours over the length of the course (normally 3 hours per unit per week with 1 of the hours used for lecture) for instruction or preparation/studying or course related activities including but not limited to internships, labs, clinical practica. Other course structures will have equivalent workload expectations as described in the syllabus.

Instructional time may include but is not limited to:
Working on posted modules or lessons prepared by the instructor; discussion forum interactions with the instructor and/or other students; making presentations and getting feedback from the instructor; attending office hours or other synchronous sessions with the instructor.

Student time outside of class:
In any seven-day period, a student is expected to be academically engaged through submitting an academic assignment; taking an exam or an interactive tutorial, or computer-assisted instruction; building websites, blogs, databases, social media presentations; attending a study group;contributing to an academic online discussion; writing papers; reading articles; conducting research; engaging in small group work.

Course Prerequisites

INFO 287 has no prequisite requirements.

Course Learning Outcomes

Upon successful completion of the course, students will be able to:

  1. Interpret the RDF data model and serialization syntaxes.
  2. Apply the Linked Data technologies such as RDF, OWL and SPARQL with the use of tools.
  3. Examine the practices of Linked Data in libraries and other cultural heritage institutions such as BIBFRAME, Schema.org and SKOS.
  4. Explain the vocabularies, standards and approaches related to Linked Data in libraries and other cultural heritage institutions.
  5. Discuss major issues, current developments and future trends in Linked Data.

Core Competencies (Program Learning Outcomes)

INFO 287 supports the following core competencies:

  1. E Design, query, and evaluate information retrieval systems.
  2. F Use the basic concepts and principles related to the selection, evaluation, organization, and preservation of physical and digital information items.
  3. G Demonstrate understanding of basic principles and standards involved in organizing information such as classification and controlled vocabulary systems, cataloging systems, metadata schemas or other systems for making information accessible to a particular clientele.
  4. H Demonstrate proficiency in identifying, using, and evaluating current and emerging information and communication technologies.

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Textbooks

Recommended Textbooks:

  • Carlson, S., Lampert, C., Melvin, D., & Washington, A. (2020). Linked data for the perplexed librarian. ALA Editions. Available as free eBook through King Libraryarrow gif indicating link outside sjsu domain
  • Jones, E., & Seikel, M. (2016). Linked data for cultural heritage. ALA Editions. Available through Amazon: 083891439Xarrow gif indicating link outside sjsu domain

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Grading Scale

The standard SJSU School of Information Grading Scale is utilized for all iSchool courses:

97 to 100 A
94 to 96 A minus
91 to 93 B plus
88 to 90 B
85 to 87 B minus
82 to 84 C plus
79 to 81 C
76 to 78 C minus
73 to 75 D plus
70 to 72 D
67 to 69 D minus
Below 67 F

 

In order to provide consistent guidelines for assessment for graduate level work in the School, these terms are applied to letter grades:

  • C represents Adequate work; a grade of "C" counts for credit for the course;
  • B represents Good work; a grade of "B" clearly meets the standards for graduate level work or undergraduate (for BS-ISDA);
    For core courses in the MLIS program (not MARA, Informatics, BS-ISDA) — INFO 200, INFO 202, INFO 204 — the iSchool requires that students earn a B in the course. If the grade is less than B (B- or lower) after the first attempt you will be placed on administrative probation. You must repeat the class if you wish to stay in the program. If - on the second attempt - you do not pass the class with a grade of B or better (not B- but B) you will be disqualified.
  • A represents Exceptional work; a grade of "A" will be assigned for outstanding work only.

Graduate Students are advised that it is their responsibility to maintain a 3.0 Grade Point Average (GPA). Undergraduates must maintain a 2.0 Grade Point Average (GPA).

University Policies

Per University Policy S16-9, university-wide policy information relevant to all courses, such as academic integrity, accommodations, etc. will be available on Office of Graduate and Undergraduate Programs' Syllabus Information web page at: https://www.sjsu.edu/curriculum/courses/syllabus-info.php. Make sure to visit this page, review and be familiar with these university policies and resources.

In order to request an accommodation in a class please contact the Accessible Education Center and register via the MyAEC portal.

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