Search This Blog
Showing posts with label LIS Notes. Show all posts
Showing posts with label LIS Notes. Show all posts

LIS Notes #09 - DSpace - Digital Library Software

 DSpace Digital Library Software

DSpace is an open-source digital repository software widely used for building open access repositories for academic, non-profit, and commercial organizations. Developed jointly by MIT Libraries and Hewlett-Packard (HP) in 2002, DSpace provides a robust platform for storing, managing, and preserving digital content, including research outputs, datasets, theses, dissertations, and other scholarly materials. Its flexibility, scalability, and adherence to international standards have made it one of the most popular repository solutions globally.

Key Features and Functionality

  1. Open Source and Customizable: DSpace is distributed under the BSD open-source license, allowing institutions to modify and adapt the software to meet their specific needs. Its modular architecture and extensive documentation facilitate customization, enabling institutions to create repositories that reflect their branding and functional requirements.

  2. Content Management: DSpace supports a wide range of digital formats, including text documents, images, videos, and datasets. It allows for the easy submission, storage, and retrieval of content. The software organizes content into a hierarchical structure of communities and collections, making it easy to manage and navigate.

  3. Metadata Support: DSpace employs qualified Dublin Core as its default metadata schema but is flexible enough to support other standards such as MARC, MODS, and METS. This ensures that the metadata associated with digital objects is rich and descriptive, facilitating better discovery and interoperability with other systems.

  4. Search and Retrieval: The platform offers powerful search and browsing capabilities, including full-text search, faceted browsing, and advanced filtering options. These features enhance the discoverability of content, making it easier for users to find relevant materials.

  5. Interoperability and Standards Compliance: DSpace is compliant with the Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH), enabling interoperability with other repositories and services. It also supports the ResourceSync framework, allowing for efficient synchronization of repository contents across different platforms.

  6. User and Access Management: The software includes robust user management features, allowing administrators to control access to content based on user roles and permissions. It supports integration with institutional authentication systems such as LDAP and Shibboleth, ensuring secure and seamless user access.

  7. Preservation and Sustainability: DSpace incorporates digital preservation tools and practices to ensure the long-term sustainability of digital content. It supports checksum validation, file format recognition, and version control, helping institutions maintain the integrity and authenticity of their digital assets over time.

  8. Community and Support: DSpace has a vibrant global community of developers, users, and institutions contributing to its ongoing development and support. Regular updates, community forums, and comprehensive documentation ensure that users have access to the latest features and best practices.

Applications and Use Cases

DSpace is widely used by academic institutions, research organizations, government agencies, and cultural heritage institutions to create institutional repositories, digital archives, and data repositories. It serves as a critical tool for managing and disseminating research outputs, promoting open access, and supporting scholarly communication. Universities use DSpace to archive theses and dissertations, while research institutions leverage it to share datasets and publications.

LIS Notes #08 - Useful Koha Commands

 

Koha is an open-source Integrated Library System (ILS) widely used by libraries for cataloging, circulation, and managing library resources. Here are some commonly used Koha commands and tasks, typically executed in a Linux terminal or via the Koha interface:

1. General System Commands

  • Start Koha instance:

sudo koha-start <instance-name>

  • Stop Koha instance:

sudo koha-stop <instance-name>

  • Restart Koha instance:

sudo koha-restart <instance-name>

  • Check the status of Koha instance:

sudo koha-list

sudo koha-shell <instance-name>

2. Database Management (MySQL/ MariaDB)

  • Access Koha MySQL database:

sudo koha-mysql <instance-name>

  • Backup the database:

sudo koha-dump <instance-name>

  • Restore the database:

sudo koha-restore <instance-name> /path/to/backup-file.sql.gz

3. Managing Users and Permissions

  • Create a new super librarian user:

sudo koha-create-admin <instance-name>

  • Reset a user's password:

sudo koha-passwd <instance-name> <username>

4. Maintenance and Housekeeping

  • Rebuild Zebra Indexes (for search):

sudo koha-rebuild-zebra -v -f <instance-name>

  • Clear Koha cache:

sudo koha-plack --restart <instance-name>

  • Run overdue notices and fines process:

sudo koha-foreach --enabled --command "/usr/share/koha/bin/cronjobs/overdue_notices.pl"

5. Log Management

  • View Koha logs:

tail -f /var/log/koha/<instance-name>/plack-error.log

tail -f /var/log/koha/<instance-name>/opac-error.log

6. Crontab Scheduling

  • Edit Koha Crontab for automated tasks (e.g., overdue notices, backups):

sudo crontab -e -u koha

7. Package and System Updates

  • Update Koha to the latest version:

sudo apt update

sudo apt upgrade koha-common



LIS Notes #07 - Faceted Classification Scheme

Faceted Classification Schemes offer a flexible, multidimensional approach to organizing information, allowing multiple characteristics (or facets) of a subject to be represented simultaneously. This system is especially useful for handling complex and interdisciplinary subjects.

Key Features of Faceted Classification Schemes

1. Division into Fundamental Categories (Facets)

Faceted systems break down subjects into basic categories or facets, each representing a different characteristic of the subject.

  • Example from Colon Classification (by Dr. S. R. Ranganathan):
    • P – Personality (Main subject)
    • M – Matter (Material or property of the subject)
    • E – Energy (Processes or activities related to the subject)
    • S – Space (Geographical location)
    • T – Time (Chronological aspect)

2. Flexibility and Scalability

Faceted classification allows for the combination of facets in various ways, offering flexibility to represent complex or new subjects without restructuring the entire system.

  • Example:
    You can classify "History of Mathematics in Europe during the 19th Century" by combining facets of subject (Mathematics), time (19th Century), and space (Europe).

3. Synthesis of Class Numbers

In faceted systems, class numbers are synthesised by combining notations from different facets, often using symbols like colons, commas, or periods.

  • Example:
    In Colon Classification, B3:5 could represent Algebra (B3) applied to Engineering (5).

4. Hospitality to New Subjects

Faceted classification schemes are open-ended and can easily accommodate new fields of knowledge without disrupting the existing structure.

  • Example:
    New technological advancements like Artificial Intelligence or Quantum Computing can be added by combining relevant facets.

5. Analytical Approach

Faceted classification employs an analytical-synthetic method:

  • Analytical: Breaking down complex subjects into their fundamental facets.
  • Synthetic: Recombining these facets to form specific, detailed class numbers.

6. Mnemonics and Predictability

Faceted systems often use mnemonics (memory aids) to make classification easier to learn and predict. Symbols or specific notations are consistently applied.

  • Example:
    The use of S for Space or T for Time across classifications in Colon Classification.

7. Useful for Multidisciplinary Subjects

Faceted classification is particularly effective for interdisciplinary or multidisciplinary topics where multiple aspects of knowledge intersect.

  • Example:
    Environmental Impact of Industrial Engineering in Asia (2020s) can be classified by combining environmental science, engineering, geography, and time facets.

8. Compatibility with Digital and Online Systems

Faceted systems are well-suited for digital libraries, databases, and online catalogues, where users can filter or refine searches based on multiple facets like subject, date, author, and location.

  • Example:
    E-commerce websites like Amazon use faceted navigation allowing users to filter products by brand, price, ratings, etc.

Advantages of Faceted Classification Schemes

  1. Greater Flexibility: Can handle complex, evolving, and interdisciplinary subjects.
  2. Ease of Expansion: New topics can be added without restructuring the system.
  3. User-Friendly: Facilitates easy navigation, especially in digital environments.
  4. Precision in Classification: Allows for detailed and specific categorisation.
  5. Supports Advanced Searching: Ideal for databases and digital catalogues where multi-faceted filtering is common.

Examples of Faceted Classification Systems

  1. Colon Classification (CC) – Developed by Dr. S. R. Ranganathan.
  2. Art & Architecture Thesaurus (AAT) – Used in museums and cultural institutions.
  3. BSO (Broad System of Ordering) – Developed for international information systems.
  4. Facet-based online catalogues – Used in digital libraries and e-commerce platforms for advanced search filtering.

LIS Notes #06 - Different Classification Schemes

Classification schemes are essential tools in Library and Information Science for organizing and arranging books, documents, and other resources in a systematic way. They help users locate materials efficiently and support libraries in managing their collections.

1. Major Classification Schemes

1.1 Dewey Decimal Classification (DDC)

  • Developed by: Melvil Dewey in 1876
  • Structure: Uses a decimal system dividing knowledge into 10 main classes, each subdivided into 10 divisions and further into 10 sections.
  • Notation: Numeric (e.g., 500 for Natural Sciences, 510 for Mathematics).
  • Widely Used In: Public libraries, school libraries, and small academic libraries globally.

Example:

  • 500 – Natural Sciences
  • 510 – Mathematics
  • 512 – Algebra

1.2 Universal Decimal Classification (UDC)

  • Developed by: Paul Otlet and Henri La Fontaine, based on DDC.
  • Structure: Uses decimal notation but is more flexible and detailed than DDC. It allows for complex subjects using auxiliary signs (like +, /, : ).
  • Notation: Numeric with symbols (e.g., 004.421.2 for Programming).
  • Widely Used In: Special libraries, research institutions, and technical libraries.

Example:

  • 004 – Computer Science
  • 004.421 – Programming
  • 004.421.2 – Programming Languages

1.3 Library of Congress Classification (LCC)

  • Developed by: Library of Congress, USA.
  • Structure: Divides knowledge into 21 main classes using alphabetical letters and further divisions using numbers.
  • Notation: Alphanumeric (e.g., QA for Mathematics, QA76 for Computer Science).
  • Widely Used In: Large academic libraries, research institutions.

Example:

  • Q – Science
  • QA – Mathematics
  • QA76 – Computer Science

1.4 Colon Classification (CC)

  • Developed by: Dr. S. R. Ranganathan in 1933.
  • Structure: Based on five fundamental categories (PMEST):
    • P – Personality (Main subject)
    • M – Matter (Material of the subject)
    • E – Energy (Processes/activities)
    • S – Space (Location)
    • T – Time (Period)
  • Notation: Combination of numbers, letters, and colons (e.g., A:5).
  • Widely Used In: Indian libraries and research institutions.

Example:

  • B – Mathematics
  • B3 – Algebra
  • B3:5 – Algebra (Applied in Engineering)

2. Other Classification Schemes

2.1 Bliss Bibliographic Classification (BC)

  • Developed by: Henry E. Bliss in 1935.
  • Structure: Focuses on subject order rather than numeric/alphabetic hierarchy.
  • Notation: Alphanumeric with a more natural and flexible arrangement of subjects.
  • Widely Used In: Some UK libraries and special libraries.

2.2 Cutter Expansive Classification (CEC)

  • Developed by: Charles Ammi Cutter in late 19th century.
  • Structure: Seven levels of classification from general to specific, designed to be adaptable for different library sizes.
  • Notation: Alphanumeric.

2.3 Bibliographic Classification (BC) by J. D. Brown

  • Developed by: J. D. Brown in the UK.
  • Structure: Based on a subject-based arrangement with emphasis on related topics being placed together.
  • Less commonly used compared to other systems.

3. Faceted Classification Systems

Faceted classification allows multiple characteristics or facets of a subject to be combined, offering more flexibility in organizing complex subjects.

  • Colon Classification (CC) by Ranganathan is a pioneering faceted system.
  • Art & Architecture Thesaurus (AAT) uses a faceted approach for organizing concepts in arts and culture.

4. Subject-Specific Classification Schemes

  1. Medical Subject Headings (MeSH): Used for medical and health sciences.
  2. ERIC Thesaurus: For education-related resources.
  3. Chemical Abstracts Service (CAS): For chemical compounds and literature.

5. Choosing a Classification Scheme

Factors influencing the choice of classification scheme include:

  • Library Type: Academic, public, special, or school libraries may prefer different systems.
  • Collection Size and Complexity: Large research libraries often prefer LCC, while smaller libraries use DDC.
  • User Needs: Libraries focusing on specialized subjects may adopt UDC or a faceted system.
  • Regional Preferences: For example, Colon Classification is widely used in Indian libraries.

LIS Notes #05 - Career in Library & Information Science

A career in Library and Information Science (LIS) is diverse and dynamic, offering opportunities beyond traditional library roles. With the rapid growth of digital information, the field has expanded to include various technology-driven and specialised positions.

1. Core Library Careers

  1. Academic Librarian

    • Works in colleges or universities assisting students, faculty, and researchers.
    • Roles include subject specialisation, collection development, and information literacy training.

  2. Public Librarian

    • Serves the general public in community libraries.
    • Focuses on programming, community engagement, and access to diverse resources.

  3. School Librarian/Media Specialist

    • Manages libraries in K-12 schools, supporting curriculum development and teaching information literacy.

  4. Special Librarian

    • Works in specialised libraries within corporations, law firms, hospitals, or government agencies.
    • Handles niche collections like legal documents, medical records, or business intelligence.

  5. Archivist

    • Preserves and organizes historical documents, photographs, and artifacts.
    • Often works in museums, government archives, or cultural institutions.

2. Information Science and Technology Roles

  1. Digital Librarian

    • Manages digital collections, e-books, online databases, and repositories.
    • Involves metadata management and digital preservation.

  2. Data Curator/Manager

    • Organizes, maintains, and ensures the accessibility of large datasets, often for research institutions.

  3. Information Architect

    • Designs information systems and structures for websites and databases to optimize user experience.

  4. Knowledge Manager

    • Implements systems to capture, share, and manage organisational knowledge and information.

  5. Records Manager

    • Focuses on managing records lifecycle, including creation, maintenance, and disposal, ensuring legal compliance.

3. Emerging and Specialised Careers

  1. User Experience (UX) Librarian

    • Focuses on improving library services and digital interfaces by studying user behaviour and feedback.

  2. Information Analyst/Scientist

    • Analyses data trends and provides insights, often in corporate or research settings.

  3. E-Governance Specialist

    • Works with government bodies to manage digital records and ensure transparent information dissemination.

  4. Library Technologist/Systems Librarian

    • Manages integrated library systems (ILS) and ensures technological infrastructure supports library services.

  5. Open Access and Scholarly Communications Librarian

    • Advocates and manages open access resources, ensuring free access to academic content.

4. Education and Qualifications

  • Undergraduate Degree:
    Some countries offer bachelor's programs in Library and Information Science.

  • Master's in Library and Information Science (MLIS):
    A widely recognized professional qualification, often required for advanced roles.

  • Certifications and Specializations:

    • Digital Libraries
    • Archival Studies
    • Information Technology and Data Science
    • Records Management

5. Skills Required

  • Technical Skills: Knowledge of library management systems (LMS), digital tools, and metadata standards.
  • Research & Analytical Skills: Critical for roles in academic or specialised libraries.
  • Communication & Outreach: Essential for public services, education, and user engagement.
  • Project Management: Especially important in digital projects and knowledge management roles.
  • Adaptability: Libraries are rapidly evolving with technology, requiring continuous learning.

6. Job Opportunities and Work Environments

  • Libraries: Academic, public, school, and special libraries.
  • Corporations: Business research, information analysis, competitive intelligence.
  • Government & NGOs: Managing public information, e-governance projects.
  • Museums & Archives: Preserving cultural heritage.
  • Technology Firms: Data management, UX design, and information architecture.

7. Career Growth and Prospects

  • Entry-Level Roles: Library Assistant, Cataloguer, Junior Librarian.
  • Mid-Level Positions: Reference Librarian, Systems Librarian, Archivist.
  • Senior Roles: Chief Librarian, Library Director, Head of Knowledge Management.
  • Academic Pathways: Becoming a LIS educator or researcher.

8. Professional Associations

  • International Federation of Library Associations and Institutions (IFLA)
  • American Library Association (ALA)
  • Chartered Institute of Library and Information Professionals (CILIP)
  • Indian Library Association (ILA)
  • Special Libraries Association (SLA)

LIS Notes # 04 - Staff Formula by D. R. Ranganathan

 

Ranganathan's Staff Formula

Ranganathan's staff formula is based on the idea that staffing should be proportional to the size, functions, and services provided by the library. It considers factors like:

  1. Collection Size: The total number of books, periodicals, and other resources.
  2. User Population: The number of patrons served by the library.
  3. Library Functions: The variety of services offered, such as circulation, reference, technical processing, and special services.
  4. Operational Hours: The number of hours the library remains open.

General Formula Structure:

Ranganathan suggested dividing library work into distinct sections and assigning staff based on the workload in each area. The major divisions are usually:

  • Administrative Work
  • Technical Processing (Cataloguing and Classification)
  • Circulation
  • Reference Services
  • Maintenance and Support Services

For example:

  • Professional Staff = PP
  • Semi-professional Staff = SS
  • Clerical Staff = CC
  • Attendant Staff = AA

The actual mathematical formula might vary depending on the specific library type (e.g., academic, public, or special libraries). The allocation of staff is often guided by workload measurement, such as books processed per day or circulation transactions.

Application Example:

For a medium-sized academic library:

  • 1 Librarian (Head)
  • 2-3 Professional Assistants (for reference, cataloguing)
  • 3-5 Clerical Staff (for circulation, records)
  • 2 Attendants (for shelving and maintenance)

Reference:

For detailed explanations, you may refer to Ranganathan's works, especially:

  • Library Administration (1959)
  • Library Manual (1933)

LIS Notes # 03 - Difference Between Bibliometrics, Almetrics and Webometrics

 Bibliometrics, altmetrics, and webometrics are all methods used to measure the impact and influence of academic or scholarly works, but they focus on different aspects and sources of data. Here's a breakdown of each:

1. Bibliometrics

  • Definition: Bibliometrics refers to the quantitative analysis of academic publications and citations. It uses statistical methods to assess the impact, productivity, and development of scientific research over time.
  • Key Focus:
    • Citation analysis: How often a paper or author is cited by others.
    • Journal impact factor (IF): A measure of the importance of a journal based on citations.
    • H-index: A metric to assess an individual researcher's productivity and citation impact.
  • Common Metrics: Citation counts, journal impact factors, h-index, g-index.
  • Sources: Academic databases like Scopus, Web of Science, and Google Scholar.

2. Altmetrics

  • Definition: Altmetrics (alternative metrics) measure the impact and engagement of academic work in non-traditional outlets, including social media, blogs, news media, policy documents, and other online platforms.
  • Key Focus:
    • Social media mentions (Twitter, Facebook, etc.)
    • Shares, downloads, and views of publications on academic platforms like ResearchGate or Academia.edu.
    • Blog posts, mainstream media coverage, or online discussions.
  • Common Metrics: Tweets, Facebook shares, news articles, online mentions, downloads.
  • Sources: Social media platforms, blogs, news websites, online repositories like Mendeley.

3. Webometrics

  • Definition: Webometrics (or cybermetrics) focuses on measuring the web presence and impact of scholarly institutions (universities, research centers), journals, and other academic entities based on their online activities and visibility.
  • Key Focus:
    • The online presence of academic institutions, including their websites, repositories, and research publications.
    • Website traffic, link structure, and academic content available on the web.
  • Common Metrics: Number of links pointing to a site, website traffic, external visibility, page rank.
  • Sources: Institutional websites, online repositories, citation databases, web crawlers.

Key Differences:

  • Bibliometrics focuses on traditional, citation-based measures of academic influence.
  • Altmetrics captures the broader, non-academic impact and attention on digital platforms.
  • Webometrics analyzes the online visibility and impact of academic institutions or their content on the web.

Conclusion: 

  • Bibliometrics is based on formal citation data, 
  • Altmetrics focuses on social media and online engagement, and 
  • Webometrics looks at the digital footprint of institutions or research entities.

LIS Notes # 02 - AI Tools for Literature Review

There are several AI tools available for conducting a literature review, helping with research discovery, summarization, citation management, and analysis. Here are some of the best AI-powered tools:

1. Research Discovery & Paper Search

  • Semantic Scholar – Uses AI to find relevant academic papers.
  • Elicit – AI-powered search for extracting key insights from research papers.
  • Connected Papers – Helps visualize connections between research papers.
  • Scite – Shows how papers cite each other (supporting, contrasting, or mentioning).

2. AI Summarization & Reading Assistance

  • ChatPDF – Allows interaction with PDFs and summarizes key points.
  • Scholarcy – Summarizes long research papers into key insights.
  • QuillBot – AI-powered paraphrasing and summarization tool.

3. Citation Management

  • Zotero – AI-assisted reference management.
  • Mendeley – Organizes and manages research citations.
  • EndNote – Helps with citation generation and reference management.

4. Writing & AI Assistance

  • Grammarly – AI-powered writing and grammar correction.
  • Trinka AI – AI for academic writing and language improvement.
  • Jenni AI – Assists in drafting and structuring research papers.

LIS Notes# 01 - Difference between COUNTER and SUSHI

COUNTER and SUSHI are related standards in the context of managing and reporting usage statistics for electronic resources, commonly used in libraries, publishers, and institutions. Here's what they mean:

COUNTER (Counting Online Usage of Networked Electronic Resources):

  • COUNTER is a standard for measuring the usage of electronic resources like e-journals, e-books, databases, and other digital content.
  • It ensures that usage statistics are consistent, credible, and comparable across publishers and platforms.
  • COUNTER reports provide key metrics, such as:
    • Total item requests (e.g., downloads or views of articles or chapters).
    • Searches within a platform or specific resource.
    • Access denials due to lack of subscription or permissions.
  • The latest version of the standard is COUNTER Release 5, which simplifies and unifies reporting formats compared to earlier releases.

SUSHI (Standardized Usage Statistics Harvesting Initiative):

  • SUSHI is a protocol designed to automate the retrieval of COUNTER usage reports.
  • It uses a machine-to-machine API, making it easier for libraries and institutions to collect usage data from multiple vendors without manual downloading.
  • SUSHI works by enabling systems (like library management software) to directly connect with publishers' platforms and retrieve COUNTER-compliant usage reports.
  • This automation saves time and ensures timely and accurate data collection.

How They Work Together:

  • COUNTER provides the framework for what data to collect and how to present it.
  • SUSHI provides the mechanism for libraries to retrieve COUNTER reports efficiently.

These standards help libraries justify the cost of subscriptions, analyze resource usage, and make data-driven decisions about their collections.

Subscribe to: Posts (Atom)