SlideShare une entreprise Scribd logo
1  sur  13
Cataloguing Museum Collections History, Trends, and Issues Michael Jenkins JHU Museum Studies Spring 2010
Week 5: Cataloguing Schemas and Standards Definitions Rationale for Standards Standards Resources
Definitions Database Schema-A database schema is a collection of meta-data that describes the relations in a database. A schema can be simply described as the "layout" of a database or the blueprint that outlines the way data is organized into tables.
Definitions Data Structure-the organizational scheme for a database. Data structure defines the tables and fields that make up a database. It also specifies the relationships of fields to one another. Data Content-Also referred to as data values, data content is the conceptual information that populates data structure. It is the value that populates a field in a database.
Definitions Data Format-the rules that specify the form of data entry. For example a data format rule might specify that a date field be entered as MM/DD/YYYY rather than DD/MM/YY. Data format rules can also specify things like capitalization, punctuation, and italicization.
Definitions Authority Controls-In library and information science, authority control is the practice of creating and maintaining headings for bibliographic material in a catalog. Authority control fulfills two important functions. First, it enables catalogers to disambiguate items with similar or identical headings. For example, two authors who happen to have published under the same name can be distinguished from each other by adding middle initials, birth and/or death (or flourished, if these are unknown) dates, or a descriptive epithet to the heading of one (or both) authors. Second, authority control is used by catalogers tocollocate materials that logically belong together, although they present themselves differently. For example, authority records are used to establish uniform titles, which can collocate all versions of a given work together even when they are issued under different titles. From Wikipedia.
Definitions Data Dictionary-A data dictionary is a collection of descriptions of the data objects or items in a data model for the benefit of programmers and others who need to refer to them. A first step in analyzing a system of objects with which users interact is to identify each object and its relationship to other objects. This process is called data modeling and results in a picture of object relationships. After each data object or item is given a descriptive name, its relationship is described (or it becomes part of some structure that implicitly describes relationship), the type of data (such as text or image or binary value) is described, possible predefined values are listed, and a brief textual description is provided. This collection can be organized for reference into a book called a data dictionary.
Why Do We Need Standards? Standards help cataloguers record information consistently. Consistent data enables effective information retrieval.
Standards Resources Cataloguing Cultural Resources: http://www.vraweb.org/ccoweb/cco/index.html CHIN Introduction to Standards: http://www.pro.rcip-chin.gc.ca/normes-standards/introduction-eng.jsp Standards at the Library of Congress http://www.loc.gov/standards/
Reading Review the following site: J. Paul Getty Trust and The College Art Association (Revised June 9, 2009) Categories for the Description of Works of Art and CDWA Lite, http://www.getty.edu/research/conducting_research/standards/cdwa/index.html Baca, M. et al. eds. (2006) Cataloguing Cultural Objects (pp. xi-xii, 1-76) Chicago, IL: American Library Association [eReserves] Weibel, S. (2005) "Border Crossings: Reflections on a Decade of Metadata Consensus Building." D-Lib Magazine, 11,7/8 (July/August), http://www.dlib.org/dlib/july05/weibel/07weibel.html
Written Assignment Create a template for a data dictionary for a website that will provide public access to a museum collection of your choosing. Describe the museum collection that you will be using for the next three assignments. If you like, be creative with the collection you choose. Fictional or personal collections are encouraged.Examples of data dictionaries can be found at http://www.amico.org/AMICOlibrary/dataDictionary.html and http://www.pro.rcip-chin.gc.ca/bd-dl/ddrcip_sn-chindd_ns/description-about-eng.jsp.
Written Assignment, Continued You will likely want to use a spreadsheet to create your data dictionary. Be sure to include attributes to describe your data fields. Examples of attributes include repeating, required, authority controlled, and core.Make sure your data dictionary contains fields for all of the information that you would like to make available online. Try to push the envelope of online collections and support meaningful interaction with your collection. Keep in mind that most online museum sites serve well over thirty fields.
Discussions Monitor the Discussion area of Sakai for this week’s topics.

Contenu connexe

Tendances

Data Journalism - Cleaning Data
Data Journalism - Cleaning DataData Journalism - Cleaning Data
Data Journalism - Cleaning DataBahareh Heravi
 
Krish data controls
Krish data controlsKrish data controls
Krish data controlssubakrish
 
Eac Presentation
Eac PresentationEac Presentation
Eac PresentationTroie82
 
Annotating Search Results from Web Databases
Annotating Search Results from Web Databases Annotating Search Results from Web Databases
Annotating Search Results from Web Databases Mohit Sngg
 
Access essentials brionna elmore
Access essentials brionna elmoreAccess essentials brionna elmore
Access essentials brionna elmorecapjjj
 
Introduction to databases
Introduction to databasesIntroduction to databases
Introduction to databasesakanksha007
 
Introduction to Data Modeling
Introduction to Data ModelingIntroduction to Data Modeling
Introduction to Data Modelingguest02ff4b5
 
CCO (Cataloging Cultural Objects): Incorporating CCO in Your Workflow
CCO (Cataloging Cultural Objects): Incorporating CCO in Your WorkflowCCO (Cataloging Cultural Objects): Incorporating CCO in Your Workflow
CCO (Cataloging Cultural Objects): Incorporating CCO in Your WorkflowVisual Resources Association
 
Dats nih-dccpc-kc7-april2018-prs-uoxf
Dats  nih-dccpc-kc7-april2018-prs-uoxfDats  nih-dccpc-kc7-april2018-prs-uoxf
Dats nih-dccpc-kc7-april2018-prs-uoxfPhilippe Rocca-Serra
 
RuleML2015: Rule-Based Exploration of Structured Data in the Browser
RuleML2015: Rule-Based Exploration of Structured Data in the BrowserRuleML2015: Rule-Based Exploration of Structured Data in the Browser
RuleML2015: Rule-Based Exploration of Structured Data in the BrowserRuleML
 
Definition of index
Definition of indexDefinition of index
Definition of indexrajib2
 
Scientific Units in the Electronic Age
Scientific Units in the Electronic AgeScientific Units in the Electronic Age
Scientific Units in the Electronic AgeStuart Chalk
 

Tendances (19)

Datasets with bioschemas
Datasets with bioschemasDatasets with bioschemas
Datasets with bioschemas
 
Index report
Index reportIndex report
Index report
 
MS Access Intro
MS Access IntroMS Access Intro
MS Access Intro
 
Metadata : Concentrating on the data, not on the scheme
Metadata : Concentrating on the data, not on the schemeMetadata : Concentrating on the data, not on the scheme
Metadata : Concentrating on the data, not on the scheme
 
Data Journalism - Cleaning Data
Data Journalism - Cleaning DataData Journalism - Cleaning Data
Data Journalism - Cleaning Data
 
Krish data controls
Krish data controlsKrish data controls
Krish data controls
 
Database
DatabaseDatabase
Database
 
Eac Presentation
Eac PresentationEac Presentation
Eac Presentation
 
Annotating Search Results from Web Databases
Annotating Search Results from Web Databases Annotating Search Results from Web Databases
Annotating Search Results from Web Databases
 
Access essentials brionna elmore
Access essentials brionna elmoreAccess essentials brionna elmore
Access essentials brionna elmore
 
Introduction to databases
Introduction to databasesIntroduction to databases
Introduction to databases
 
Introduction to Data Modeling
Introduction to Data ModelingIntroduction to Data Modeling
Introduction to Data Modeling
 
CCO (Cataloging Cultural Objects): Incorporating CCO in Your Workflow
CCO (Cataloging Cultural Objects): Incorporating CCO in Your WorkflowCCO (Cataloging Cultural Objects): Incorporating CCO in Your Workflow
CCO (Cataloging Cultural Objects): Incorporating CCO in Your Workflow
 
Dats nih-dccpc-kc7-april2018-prs-uoxf
Dats  nih-dccpc-kc7-april2018-prs-uoxfDats  nih-dccpc-kc7-april2018-prs-uoxf
Dats nih-dccpc-kc7-april2018-prs-uoxf
 
RuleML2015: Rule-Based Exploration of Structured Data in the Browser
RuleML2015: Rule-Based Exploration of Structured Data in the BrowserRuleML2015: Rule-Based Exploration of Structured Data in the Browser
RuleML2015: Rule-Based Exploration of Structured Data in the Browser
 
Definition of index
Definition of indexDefinition of index
Definition of index
 
New age
New ageNew age
New age
 
Ejis
EjisEjis
Ejis
 
Scientific Units in the Electronic Age
Scientific Units in the Electronic AgeScientific Units in the Electronic Age
Scientific Units in the Electronic Age
 

En vedette (9)

Jhu Week 2
Jhu Week 2Jhu Week 2
Jhu Week 2
 
Novell File Management Suite Use Cases
Novell File Management Suite Use CasesNovell File Management Suite Use Cases
Novell File Management Suite Use Cases
 
Jhu Week 3
Jhu Week 3Jhu Week 3
Jhu Week 3
 
Jhu Week 7
Jhu Week 7Jhu Week 7
Jhu Week 7
 
Application of Collaborative Working Agreements in the NZ Construction Industry
Application of Collaborative Working Agreements in the NZ Construction IndustryApplication of Collaborative Working Agreements in the NZ Construction Industry
Application of Collaborative Working Agreements in the NZ Construction Industry
 
Skeleton Coast
Skeleton CoastSkeleton Coast
Skeleton Coast
 
Jhu Week 4
Jhu Week 4Jhu Week 4
Jhu Week 4
 
Jhu Week 5
Jhu Week 5Jhu Week 5
Jhu Week 5
 
2006 Pmicos Using Evpm In Management Of Wies (Dr Gs) And Healthcare Projects ...
2006 Pmicos Using Evpm In Management Of Wies (Dr Gs) And Healthcare Projects ...2006 Pmicos Using Evpm In Management Of Wies (Dr Gs) And Healthcare Projects ...
2006 Pmicos Using Evpm In Management Of Wies (Dr Gs) And Healthcare Projects ...
 

Similaire à Jhu Week 6

2. Chapter Two.pdf
2. Chapter Two.pdf2. Chapter Two.pdf
2. Chapter Two.pdffikadumola
 
Dbms Lec Uog 02
Dbms Lec Uog 02Dbms Lec Uog 02
Dbms Lec Uog 02smelltulip
 
Bca examination 2017 dbms
Bca examination 2017 dbmsBca examination 2017 dbms
Bca examination 2017 dbmsAnjaan Gajendra
 
Semantic citation
Semantic citationSemantic citation
Semantic citationDeepak K
 
Metadata lecture(9 17-14)
Metadata lecture(9 17-14)Metadata lecture(9 17-14)
Metadata lecture(9 17-14)mhb120
 
Academic Linkage A Linkage Platform For Large Volumes Of Academic Information
Academic Linkage  A Linkage Platform For Large Volumes Of Academic InformationAcademic Linkage  A Linkage Platform For Large Volumes Of Academic Information
Academic Linkage A Linkage Platform For Large Volumes Of Academic InformationAmy Roman
 
Interpreting the Semantics of Anomalies Based on Mutual Information in Link M...
Interpreting the Semantics of Anomalies Based on Mutual Information in Link M...Interpreting the Semantics of Anomalies Based on Mutual Information in Link M...
Interpreting the Semantics of Anomalies Based on Mutual Information in Link M...ijdms
 
Part2- The Atomic Information Resource
Part2- The Atomic Information ResourcePart2- The Atomic Information Resource
Part2- The Atomic Information ResourceJEAN-MICHEL LETENNIER
 
Expression of Query in XML object-oriented database
Expression of Query in XML object-oriented databaseExpression of Query in XML object-oriented database
Expression of Query in XML object-oriented databaseEditor IJCATR
 
Expression of Query in XML object-oriented database
Expression of Query in XML object-oriented databaseExpression of Query in XML object-oriented database
Expression of Query in XML object-oriented databaseEditor IJCATR
 
Expression of Query in XML object-oriented database
Expression of Query in XML object-oriented databaseExpression of Query in XML object-oriented database
Expression of Query in XML object-oriented databaseEditor IJCATR
 
20IT501_DWDM_PPT_Unit_II.ppt
20IT501_DWDM_PPT_Unit_II.ppt20IT501_DWDM_PPT_Unit_II.ppt
20IT501_DWDM_PPT_Unit_II.pptPalaniKumarR2
 

Similaire à Jhu Week 6 (20)

2. Chapter Two.pdf
2. Chapter Two.pdf2. Chapter Two.pdf
2. Chapter Two.pdf
 
Dbms Lec Uog 02
Dbms Lec Uog 02Dbms Lec Uog 02
Dbms Lec Uog 02
 
Digital Library UNIT-3
Digital Library UNIT-3Digital Library UNIT-3
Digital Library UNIT-3
 
Spotlight
SpotlightSpotlight
Spotlight
 
Bca examination 2017 dbms
Bca examination 2017 dbmsBca examination 2017 dbms
Bca examination 2017 dbms
 
Database model BY ME
Database model BY MEDatabase model BY ME
Database model BY ME
 
Data models
Data modelsData models
Data models
 
Semantic citation
Semantic citationSemantic citation
Semantic citation
 
Data models
Data modelsData models
Data models
 
Data models
Data modelsData models
Data models
 
Metadata lecture(9 17-14)
Metadata lecture(9 17-14)Metadata lecture(9 17-14)
Metadata lecture(9 17-14)
 
Academic Linkage A Linkage Platform For Large Volumes Of Academic Information
Academic Linkage  A Linkage Platform For Large Volumes Of Academic InformationAcademic Linkage  A Linkage Platform For Large Volumes Of Academic Information
Academic Linkage A Linkage Platform For Large Volumes Of Academic Information
 
Bt0066 dbms
Bt0066 dbmsBt0066 dbms
Bt0066 dbms
 
Interpreting the Semantics of Anomalies Based on Mutual Information in Link M...
Interpreting the Semantics of Anomalies Based on Mutual Information in Link M...Interpreting the Semantics of Anomalies Based on Mutual Information in Link M...
Interpreting the Semantics of Anomalies Based on Mutual Information in Link M...
 
Database
DatabaseDatabase
Database
 
Part2- The Atomic Information Resource
Part2- The Atomic Information ResourcePart2- The Atomic Information Resource
Part2- The Atomic Information Resource
 
Expression of Query in XML object-oriented database
Expression of Query in XML object-oriented databaseExpression of Query in XML object-oriented database
Expression of Query in XML object-oriented database
 
Expression of Query in XML object-oriented database
Expression of Query in XML object-oriented databaseExpression of Query in XML object-oriented database
Expression of Query in XML object-oriented database
 
Expression of Query in XML object-oriented database
Expression of Query in XML object-oriented databaseExpression of Query in XML object-oriented database
Expression of Query in XML object-oriented database
 
20IT501_DWDM_PPT_Unit_II.ppt
20IT501_DWDM_PPT_Unit_II.ppt20IT501_DWDM_PPT_Unit_II.ppt
20IT501_DWDM_PPT_Unit_II.ppt
 

Dernier

Z Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphZ Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphThiyagu K
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdfQucHHunhnh
 
Class 11th Physics NEET formula sheet pdf
Class 11th Physics NEET formula sheet pdfClass 11th Physics NEET formula sheet pdf
Class 11th Physics NEET formula sheet pdfAyushMahapatra5
 
Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactdawncurless
 
Grant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingGrant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingTechSoup
 
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...fonyou31
 
Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104misteraugie
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...christianmathematics
 
Student login on Anyboli platform.helpin
Student login on Anyboli platform.helpinStudent login on Anyboli platform.helpin
Student login on Anyboli platform.helpinRaunakKeshri1
 
Interactive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationInteractive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationnomboosow
 
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdfBASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdfSoniaTolstoy
 
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptxSOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptxiammrhaywood
 
Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Celine George
 
A Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformA Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformChameera Dedduwage
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Krashi Coaching
 
social pharmacy d-pharm 1st year by Pragati K. Mahajan
social pharmacy d-pharm 1st year by Pragati K. Mahajansocial pharmacy d-pharm 1st year by Pragati K. Mahajan
social pharmacy d-pharm 1st year by Pragati K. Mahajanpragatimahajan3
 
Disha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdfDisha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdfchloefrazer622
 
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in DelhiRussian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhikauryashika82
 
Unit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxUnit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxVishalSingh1417
 

Dernier (20)

Z Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphZ Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot Graph
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
 
Class 11th Physics NEET formula sheet pdf
Class 11th Physics NEET formula sheet pdfClass 11th Physics NEET formula sheet pdf
Class 11th Physics NEET formula sheet pdf
 
Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impact
 
Grant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingGrant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy Consulting
 
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
 
Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104Nutritional Needs Presentation - HLTH 104
Nutritional Needs Presentation - HLTH 104
 
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
Explore beautiful and ugly buildings. Mathematics helps us create beautiful d...
 
Student login on Anyboli platform.helpin
Student login on Anyboli platform.helpinStudent login on Anyboli platform.helpin
Student login on Anyboli platform.helpin
 
Interactive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationInteractive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communication
 
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdfBASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
 
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptxSOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
 
Mattingly "AI & Prompt Design: The Basics of Prompt Design"
Mattingly "AI & Prompt Design: The Basics of Prompt Design"Mattingly "AI & Prompt Design: The Basics of Prompt Design"
Mattingly "AI & Prompt Design: The Basics of Prompt Design"
 
Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17
 
A Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformA Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy Reform
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
 
social pharmacy d-pharm 1st year by Pragati K. Mahajan
social pharmacy d-pharm 1st year by Pragati K. Mahajansocial pharmacy d-pharm 1st year by Pragati K. Mahajan
social pharmacy d-pharm 1st year by Pragati K. Mahajan
 
Disha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdfDisha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdf
 
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in DelhiRussian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
Russian Escort Service in Delhi 11k Hotel Foreigner Russian Call Girls in Delhi
 
Unit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxUnit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptx
 

Jhu Week 6

  • 1. Cataloguing Museum Collections History, Trends, and Issues Michael Jenkins JHU Museum Studies Spring 2010
  • 2. Week 5: Cataloguing Schemas and Standards Definitions Rationale for Standards Standards Resources
  • 3. Definitions Database Schema-A database schema is a collection of meta-data that describes the relations in a database. A schema can be simply described as the "layout" of a database or the blueprint that outlines the way data is organized into tables.
  • 4. Definitions Data Structure-the organizational scheme for a database. Data structure defines the tables and fields that make up a database. It also specifies the relationships of fields to one another. Data Content-Also referred to as data values, data content is the conceptual information that populates data structure. It is the value that populates a field in a database.
  • 5. Definitions Data Format-the rules that specify the form of data entry. For example a data format rule might specify that a date field be entered as MM/DD/YYYY rather than DD/MM/YY. Data format rules can also specify things like capitalization, punctuation, and italicization.
  • 6. Definitions Authority Controls-In library and information science, authority control is the practice of creating and maintaining headings for bibliographic material in a catalog. Authority control fulfills two important functions. First, it enables catalogers to disambiguate items with similar or identical headings. For example, two authors who happen to have published under the same name can be distinguished from each other by adding middle initials, birth and/or death (or flourished, if these are unknown) dates, or a descriptive epithet to the heading of one (or both) authors. Second, authority control is used by catalogers tocollocate materials that logically belong together, although they present themselves differently. For example, authority records are used to establish uniform titles, which can collocate all versions of a given work together even when they are issued under different titles. From Wikipedia.
  • 7. Definitions Data Dictionary-A data dictionary is a collection of descriptions of the data objects or items in a data model for the benefit of programmers and others who need to refer to them. A first step in analyzing a system of objects with which users interact is to identify each object and its relationship to other objects. This process is called data modeling and results in a picture of object relationships. After each data object or item is given a descriptive name, its relationship is described (or it becomes part of some structure that implicitly describes relationship), the type of data (such as text or image or binary value) is described, possible predefined values are listed, and a brief textual description is provided. This collection can be organized for reference into a book called a data dictionary.
  • 8. Why Do We Need Standards? Standards help cataloguers record information consistently. Consistent data enables effective information retrieval.
  • 9. Standards Resources Cataloguing Cultural Resources: http://www.vraweb.org/ccoweb/cco/index.html CHIN Introduction to Standards: http://www.pro.rcip-chin.gc.ca/normes-standards/introduction-eng.jsp Standards at the Library of Congress http://www.loc.gov/standards/
  • 10. Reading Review the following site: J. Paul Getty Trust and The College Art Association (Revised June 9, 2009) Categories for the Description of Works of Art and CDWA Lite, http://www.getty.edu/research/conducting_research/standards/cdwa/index.html Baca, M. et al. eds. (2006) Cataloguing Cultural Objects (pp. xi-xii, 1-76) Chicago, IL: American Library Association [eReserves] Weibel, S. (2005) "Border Crossings: Reflections on a Decade of Metadata Consensus Building." D-Lib Magazine, 11,7/8 (July/August), http://www.dlib.org/dlib/july05/weibel/07weibel.html
  • 11. Written Assignment Create a template for a data dictionary for a website that will provide public access to a museum collection of your choosing. Describe the museum collection that you will be using for the next three assignments. If you like, be creative with the collection you choose. Fictional or personal collections are encouraged.Examples of data dictionaries can be found at http://www.amico.org/AMICOlibrary/dataDictionary.html and http://www.pro.rcip-chin.gc.ca/bd-dl/ddrcip_sn-chindd_ns/description-about-eng.jsp.
  • 12. Written Assignment, Continued You will likely want to use a spreadsheet to create your data dictionary. Be sure to include attributes to describe your data fields. Examples of attributes include repeating, required, authority controlled, and core.Make sure your data dictionary contains fields for all of the information that you would like to make available online. Try to push the envelope of online collections and support meaningful interaction with your collection. Keep in mind that most online museum sites serve well over thirty fields.
  • 13. Discussions Monitor the Discussion area of Sakai for this week’s topics.

Notes de l'éditeur

  1. Welcome back to our online classroom for Cataloguing Museum Collections: History, Trends, and Issues.
  2. This week we are investigating cataloguing schemas and standards. We will begin this presentation by reviewing some key definitions as we consider standards. We will follow that with a look at the rationale for employing standards in cataloguing. Finally we will look at some resources that are helpful as museum work to implement standards locally.
  3. All catalogues must have a structure. That structure defines where data elements are located and how they relate to other elements in the system. Taken together these rules form the schema of a cataloguing system. Here is a good definition of a database schema that I found on About.com: “A database schema is a collection of meta-data that describes the relations in a database. A schema can be simply described as the "layout" of a database or the blueprint that outlines the way data is organized into tables.”Decisions about how a schema is organized, what is in the schema, and how changes are made to the schema can have a profound impact on the catalogue information contained in a system.
  4. Data Structure-the organizational scheme for a database. Data structure defines the tables and fields that make up a database. It also specifies the relationships of fields to one another.Data Content-Also referred to as data values, data content is the conceptual information that populates data structure. It is the value that populates a field in a database.
  5. Data format rules specify how we enter data content values into the database structure. Here is a definition of data format: Data Format-the rules that specify the form of data entry. For example a data format rule might specify that a date field be entered as MM/DD/YYYY rather than DD/MM/YY. Data format rules can also specify things like capitalization, punctuation, and italicization.
  6. Authority Controls-In library and information science, authority control is the practice of creating and maintaining headings for bibliographic material in a catalog. Authority control fulfills two important functions. First, it enables catalogers to disambiguate items with similar or identical headings. For example, two authors who happen to have published under the same name can be distinguished from each other by adding middle initials, birth and/or death (or flourished, if these are unknown) dates, or a descriptive epithet to the heading of one (or both) authors. Second, authority control is used by catalogers tocollocate materials that logically belong together, although they present themselves differently. For example, authority records are used to establish uniform titles, which can collocate all versions of a given work together even when they are issued under different titles. From Wikipedia.
  7. In our assignment this week, you are being asked to create a data dictionary for an online museum collection. Data dictionaries form the foundation of an organizations standards work. They literally define what it is we care about, how we catalogue it, and how it relates to other information. Here is a good working definition of a data dictionary-A data dictionary is a collection of descriptions of the data objects or items in a data model for the benefit of programmers and others who need to refer to them. A first step in analyzing a system of objects with which users interact is to identify each object and its relationship to other objects. This process is called data modeling and results in a picture of object relationships. After each data object or item is given a descriptive name, its relationship is described (or it becomes part of some structure that implicitly describes relationship), the type of data (such as text or image or binary value) is described, possible predefined values are listed, and a brief textual description is provided. This collection can be organized for reference into a book called a data dictionary.
  8. Standards help museums in several ways. First, standards for data structure provide the foundation for information systems that allow us to model the catalogue data about our objects in a way that makes sense to our professional staffs and our visitors. Next, standards around data content and format guide our cataloguers as they describe the works in our collection. Finally, a complete standards program ensures that we have good structured data that can be effectively investigated and retrieved.
  9. Here are three great resources for information about standards in museum cataloguing. Each of these resources links to many other places with community standards for cataloguing, information interchange, and retrieval.Cataloguing Cultural Resources:http://www.vraweb.org/ccoweb/cco/index.htmlCHIN Introduction to Standards:http://www.pro.rcip-chin.gc.ca/normes-standards/introduction-eng.jspStandards at the Library of Congresshttp://www.loc.gov/standards/
  10. Our readings this week take a look at data structure, data content, and data format. As you read, consider the layering effect of standards based systems, cataloguing, and information retrieval. Is one implementation of standards more important than the others? Can you make up for a lack on standards in one area with use of standards in another?Read the following: Review the following site: J. Paul Getty Trust and The College Art Association (Revised June 9, 2009) Categories for the Description of Works of Art and CDWA Lite, http://www.getty.edu/research/conducting_research/standards/cdwa/index.htmlBaca, M. et al. eds. (2006) Cataloguing Cultural Objects (pp. xi-xii, 1-76) Chicago, IL: American Library Association [eReserves]Weibel, S. (2005) "Border Crossings: Reflections on a Decade of Metadata Consensus Building." D-Lib Magazine, 11,7/8 (July/August), http://www.dlib.org/dlib/july05/weibel/07weibel.html
  11. Create a template for a data dictionary for a website that will provide public access to a museum collection of your choosing. Describe the museum collection that you will be using for the next three assignments. If you like, be creative with the collection you choose. Fictional or personal collections are encouraged.Examples of data dictionaries can be found at http://www.amico.org/AMICOlibrary/dataDictionary.html and http://www.pro.rcip-chin.gc.ca/bd-dl/ddrcip_sn-chindd_ns/description-about-eng.jsp.
  12. You will likely want to use a spreadsheet to create your data dictionary. Be sure to include attributes to describe your data fields. Examples of attributes include repeating, required, authority controlled, and core.Make sure your data dictionary contains fields for all of the information that you would like to make available online. Try to push the envelope of online collections and support meaningful interaction with your collection. Keep in mind that most online museum sites serve well over thirty fields.
  13. Our discussion this week will focus on the collections that you and your classmates will be using for the next three assignments.