Social_Vulnerability_Entities
Pacific Islands Fisheries Science Center
Entity
(ENT)
| ID: 59259
| Published / External
Created: 2020-04-08
|
Last Modified: 2022-08-09
Data Set (DS) | ID: 59258
ID: 59259
Entity (ENT)
* Discovery• First Pass
» Metadata Rubric
Item Identification
| * » Title | Social_Vulnerability_Entities |
|---|---|
| Short Name | |
| * Status | |
| Creation Date | |
| Revision Date | |
| • Publication Date | |
| * » Abstract | |
| * Purpose | |
| Notes | |
| Other Citation Details | |
| • Supplemental Information | |
| DOI (Digital Object Identifier) | |
| DOI Registration Authority | |
| DOI Issue Date |
Keywords
Theme Keywords
| Thesaurus | Keyword |
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Temporal Keywords
| Thesaurus | Keyword |
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* Spatial Keywords
| Thesaurus | Keyword |
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Stratum Keywords
| Thesaurus | Keyword |
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Instrument Keywords
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Platform Keywords
| Thesaurus | Keyword |
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Physical Location
| • » Organization | |
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| • » City | |
| • » State/Province | |
| • Country | |
| • » Location Description |
Entity Information
| Entity Type | Spreadsheet |
|---|---|
| Active Version? | Y |
| Alias | |
| Schema Name | |
| » Description |
Data dictionary for the social vulnerability indices used in the "Coral Reef Resilience and Social Vulnerability to Climate Change" reports for the main Hawaiian Islands, Guam, the Commonwealth of the Northern Mariana Islands, and American Samoa. |
| Change Summary |
Data Attributes
Attribute Summary
| Score | Req'd? | PKey? | » Name | Data Storage Type | Description |
|---|---|---|---|---|---|
| 100 | No | No | Community | TEXT | Layman's description of Community area. |
| 100 | No | No | CCD | TEXT | Census County Division name (long form). |
| 100 | No | No | CCD_Name | TEXT | Census County Division name (short form). |
| 100 | No | No | GEO_ID2 | NUMBER | Census County Division fully qualified geographic identifier (American Community Census, geoid2). This is the field to join the data in this table with the GEOID field in the TIGER Line shapefiles for County Subdivisions, so the data can be plotted in a mapping application (e.g., ArcGIS). |
| 100 | No | No | County | NUMBER | County Code, (American Community Census). |
| 100 | No | No | State | NUMBER | State Code, (American Community Census). |
| 100 | No | No | Island.Group | TEXT | Regional two-letter code. HI=Hawaii, AS=American Samoa, GU=Guam, and MP=Commonwealth of the Northern Mariana Islands. |
| 100 | No | No | Raw.Index.Val_Housing.Charcter. | NUMBER | Un-normalized principal component analysis (PCA) axis metric of Housing Characteristics: The housing characteristics index highlights the character of housing available within a community and measures the median rent (lowers vulnerability), median number of rooms in family dwellings (lowers vulnerability), and the percentage of houses that lack plumbing facilities (increases vulnerability). |
| 100 | No | No | Raw.Index.Val_Labor.Force | NUMBER | Un-normalized principal component analysis (PCA) axis metric of Labor Force Structure: Labor force structure index provides an indication of the strength and stability of the labor force, including variables on the percent of females in the labor force (lowers vulnerability), the percent of those in the service industry (lowers vulnerability), as well as the percent of families with income under $10,000 (increases vulnerability). |
| 100 | No | No | Raw.Index.Val_Personal.Disruption | NUMBER | Un-normalized principal component analysis (PCA) axis metric of Personal Disruption: The personal disruption index includes variables that might indicate unstable personal circumstances, including poverty (increases vulnerability), unemployment (increases vulnerability), and low educational attainment (increases vulnerability). |
| 100 | No | No | Raw.Index.Val_Population.Comp. | NUMBER | Un-normalized principal component analysis (PCA) axis metric of Population Composition: The population composition index describes demographic variables identified as indicators of socially vulnerable populations, including the percent of young children (increases vulnerability), the percent of female-headed households (increases vulnerability), and the percent of people without a Bachelor's degree (increases vulnerability). |
| 100 | No | No | Raw.Index.Val_Poverty | NUMBER | Un-normalized principal component analysis (PCA) axis metric of Poverty: The poverty index highlights the percentage of the total population in poverty (increases vulnerability) as well as the percentage in poverty of other vulnerable groups such as children (under 18; increases vulnerability), families with children under 5 (increases vulnerability), and single-female headed families (increases vulnerability). |
| 100 | No | No | Flag_RegionalReference_Housing.Charcter. | NUMBER | Leveled Housing Characteristic Metric: Housing Characteristic principal component analysis (PCA) data broken into four levels dependent upon the distribution of values within a Census County Division's region: 1, "Low" (values greater than mean plus one standard deviation); 2, "Med-Low" (values falling between the mean and the mean plus one standard deviation); 3, "Med-High" (values falling between the mean minus one standard deviation and the mean); 4, "High" (values less than the mean minus one standard deviation). |
| 100 | No | No | Flag_RegionalReference_Labor.Force | NUMBER | Leveled Labor Force Structure Metric: Labor Force Structure principal component analysis (PCA) data broken into four levels dependent upon the distribution of values within a Census County Division's region: 1, "Low" (values greater than mean plus one standard deviation); 2, "Med-Low" (values falling between the mean and the mean plus one standard deviation); 3, "Med-High" (values falling between the mean minus one standard deviation and the mean); 4, "High" (values less than the mean minus one standard deviation). |
| 100 | No | No | Flag_RegionalReference_Personal.Disruption | NUMBER | Leveled Personal Disruption Metric: Personal Disruption principal component analysis (PCA) data broken into four levels dependent upon the distribution of values within a Census County Division's region: 1, "Low" (values greater than mean plus one standard deviation); 2, "Med-Low" (values falling between the mean and the mean plus one standard deviation); 3, "Med-High" (values falling between the mean minus one standard deviation and the mean); 4, "High" (values less than the mean minus one standard deviation). |
| 100 | No | No | Flag_RegionalReference_Population.Comp. | NUMBER | Leveled Population Composition Metric: Population Composition principal component analysis (PCA) data broken into four levels dependent upon the distribution of values within a Census County Division's region: 1, "Low" (values greater than mean plus one standard deviation); 2, "Med-Low" (values falling between the mean and the mean plus one standard deviation); 3, "Med-High" (values falling between the mean minus one standard deviation and the mean); 4, "High" (values less than the mean minus one standard deviation). |
| 100 | No | No | Flag_RegionalReference_Poverty | NUMBER | Leveled Poverty Metric: Poverty principal component analysis (PCA) data broken into four levels dependent upon the distribution of values within a Census County Division's region: 1, "Low" (values greater than mean plus one standard deviation); 2, "Med-Low" (values falling between the mean and the mean plus one standard deviation); 3, "Med-High" (values falling between the mean minus one standard deviation and the mean); 4, "High" (values less than the mean minus one standard deviation). |
| 100 | No | No | Flag_RegionalReference_Overall_Aggregate | NUMBER | Number of underlying leveled social vulnerability metrics rated as "High". Values range from 0-5. |
Attribute Details
| Attribute Name | Community |
|---|---|
| Seq. Order | 1 |
| Data Storage Type | TEXT |
| Max Length | |
| Min Length | |
| Required | No |
| Primary Key | No |
| Precision | |
| Scale | |
| Status | Active |
| Description |
Layman's description of Community area. |
| General Data Type | |
| Unit of Measure | |
| Case Restriction | |
| Display Example | |
| Format Mask | |
| Null Value | |
| Null Value Meaning | |
| Allowed Values | |
| Default Value | |
| Foreign Key Relations | |
| Derivation | |
| Validation Rules |
| Attribute Name | CCD |
|---|---|
| Seq. Order | 2 |
| Data Storage Type | TEXT |
| Max Length | |
| Min Length | |
| Required | No |
| Primary Key | No |
| Precision | |
| Scale | |
| Status | Active |
| Description |
Census County Division name (long form). |
| General Data Type | |
| Unit of Measure | |
| Case Restriction | |
| Display Example | |
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| Null Value | |
| Null Value Meaning | |
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| Foreign Key Relations | |
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| Validation Rules |
| Attribute Name | CCD_Name |
|---|---|
| Seq. Order | 3 |
| Data Storage Type | TEXT |
| Max Length | |
| Min Length | |
| Required | No |
| Primary Key | No |
| Precision | |
| Scale | |
| Status | Active |
| Description |
Census County Division name (short form). |
| General Data Type | |
| Unit of Measure | |
| Case Restriction | |
| Display Example | |
| Format Mask | |
| Null Value | |
| Null Value Meaning | |
| Allowed Values | |
| Default Value | |
| Foreign Key Relations | |
| Derivation | |
| Validation Rules |
| Attribute Name | GEO_ID2 |
|---|---|
| Seq. Order | 4 |
| Data Storage Type | NUMBER |
| Max Length | |
| Min Length | |
| Required | No |
| Primary Key | No |
| Precision | |
| Scale | |
| Status | Active |
| Description |
Census County Division fully qualified geographic identifier (American Community Census, geoid2). This is the field to join the data in this table with the GEOID field in the TIGER Line shapefiles for County Subdivisions, so the data can be plotted in a mapping application (e.g., ArcGIS). |
| General Data Type | |
| Unit of Measure | |
| Case Restriction | |
| Display Example | |
| Format Mask | |
| Null Value | |
| Null Value Meaning | |
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| Derivation | |
| Validation Rules |
| Attribute Name | County |
|---|---|
| Seq. Order | 5 |
| Data Storage Type | NUMBER |
| Max Length | |
| Min Length | |
| Required | No |
| Primary Key | No |
| Precision | |
| Scale | |
| Status | Active |
| Description |
County Code, (American Community Census). |
| General Data Type | |
| Unit of Measure | |
| Case Restriction | |
| Display Example | |
| Format Mask | |
| Null Value | |
| Null Value Meaning | |
| Allowed Values | |
| Default Value | |
| Foreign Key Relations | |
| Derivation | |
| Validation Rules |
| Attribute Name | State |
|---|---|
| Seq. Order | 6 |
| Data Storage Type | NUMBER |
| Max Length | |
| Min Length | |
| Required | No |
| Primary Key | No |
| Precision | |
| Scale | |
| Status | Active |
| Description |
State Code, (American Community Census). |
| General Data Type | |
| Unit of Measure | |
| Case Restriction | |
| Display Example | |
| Format Mask | |
| Null Value | |
| Null Value Meaning | |
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| Derivation | |
| Validation Rules |
| Attribute Name | Island.Group |
|---|---|
| Seq. Order | 7 |
| Data Storage Type | TEXT |
| Max Length | |
| Min Length | |
| Required | No |
| Primary Key | No |
| Precision | |
| Scale | |
| Status | Active |
| Description |
Regional two-letter code. HI=Hawaii, AS=American Samoa, GU=Guam, and MP=Commonwealth of the Northern Mariana Islands. |
| General Data Type | |
| Unit of Measure | |
| Case Restriction | |
| Display Example | |
| Format Mask | |
| Null Value | |
| Null Value Meaning | |
| Allowed Values | |
| Default Value | |
| Foreign Key Relations | |
| Derivation | |
| Validation Rules |
| Attribute Name | Raw.Index.Val_Housing.Charcter. |
|---|---|
| Seq. Order | 8 |
| Data Storage Type | NUMBER |
| Max Length | |
| Min Length | |
| Required | No |
| Primary Key | No |
| Precision | |
| Scale | |
| Status | Active |
| Description |
Un-normalized principal component analysis (PCA) axis metric of Housing Characteristics: The housing characteristics index highlights the character of housing available within a community and measures the median rent (lowers vulnerability), median number of rooms in family dwellings (lowers vulnerability), and the percentage of houses that lack plumbing facilities (increases vulnerability). |
| General Data Type | |
| Unit of Measure | |
| Case Restriction | |
| Display Example | |
| Format Mask | |
| Null Value | |
| Null Value Meaning | |
| Allowed Values | |
| Default Value | |
| Foreign Key Relations | |
| Derivation | |
| Validation Rules |
| Attribute Name | Raw.Index.Val_Labor.Force |
|---|---|
| Seq. Order | 9 |
| Data Storage Type | NUMBER |
| Max Length | |
| Min Length | |
| Required | No |
| Primary Key | No |
| Precision | |
| Scale | |
| Status | Active |
| Description |
Un-normalized principal component analysis (PCA) axis metric of Labor Force Structure: Labor force structure index provides an indication of the strength and stability of the labor force, including variables on the percent of females in the labor force (lowers vulnerability), the percent of those in the service industry (lowers vulnerability), as well as the percent of families with income under $10,000 (increases vulnerability). |
| General Data Type | |
| Unit of Measure | |
| Case Restriction | |
| Display Example | |
| Format Mask | |
| Null Value | |
| Null Value Meaning | |
| Allowed Values | |
| Default Value | |
| Foreign Key Relations | |
| Derivation | |
| Validation Rules |
| Attribute Name | Raw.Index.Val_Personal.Disruption |
|---|---|
| Seq. Order | 10 |
| Data Storage Type | NUMBER |
| Max Length | |
| Min Length | |
| Required | No |
| Primary Key | No |
| Precision | |
| Scale | |
| Status | Active |
| Description |
Un-normalized principal component analysis (PCA) axis metric of Personal Disruption: The personal disruption index includes variables that might indicate unstable personal circumstances, including poverty (increases vulnerability), unemployment (increases vulnerability), and low educational attainment (increases vulnerability). |
| General Data Type | |
| Unit of Measure | |
| Case Restriction | |
| Display Example | |
| Format Mask | |
| Null Value | |
| Null Value Meaning | |
| Allowed Values | |
| Default Value | |
| Foreign Key Relations | |
| Derivation | |
| Validation Rules |
| Attribute Name | Raw.Index.Val_Population.Comp. |
|---|---|
| Seq. Order | 11 |
| Data Storage Type | NUMBER |
| Max Length | |
| Min Length | |
| Required | No |
| Primary Key | No |
| Precision | |
| Scale | |
| Status | Active |
| Description |
Un-normalized principal component analysis (PCA) axis metric of Population Composition: The population composition index describes demographic variables identified as indicators of socially vulnerable populations, including the percent of young children (increases vulnerability), the percent of female-headed households (increases vulnerability), and the percent of people without a Bachelor's degree (increases vulnerability). |
| General Data Type | |
| Unit of Measure | |
| Case Restriction | |
| Display Example | |
| Format Mask | |
| Null Value | |
| Null Value Meaning | |
| Allowed Values | |
| Default Value | |
| Foreign Key Relations | |
| Derivation | |
| Validation Rules |
| Attribute Name | Raw.Index.Val_Poverty |
|---|---|
| Seq. Order | 12 |
| Data Storage Type | NUMBER |
| Max Length | |
| Min Length | |
| Required | No |
| Primary Key | No |
| Precision | |
| Scale | |
| Status | Active |
| Description |
Un-normalized principal component analysis (PCA) axis metric of Poverty: The poverty index highlights the percentage of the total population in poverty (increases vulnerability) as well as the percentage in poverty of other vulnerable groups such as children (under 18; increases vulnerability), families with children under 5 (increases vulnerability), and single-female headed families (increases vulnerability). |
| General Data Type | |
| Unit of Measure | |
| Case Restriction | |
| Display Example | |
| Format Mask | |
| Null Value | |
| Null Value Meaning | |
| Allowed Values | |
| Default Value | |
| Foreign Key Relations | |
| Derivation | |
| Validation Rules |
| Attribute Name | Flag_RegionalReference_Housing.Charcter. |
|---|---|
| Seq. Order | 13 |
| Data Storage Type | NUMBER |
| Max Length | |
| Min Length | |
| Required | No |
| Primary Key | No |
| Precision | |
| Scale | |
| Status | Active |
| Description |
Leveled Housing Characteristic Metric: Housing Characteristic principal component analysis (PCA) data broken into four levels dependent upon the distribution of values within a Census County Division's region: 1, "Low" (values greater than mean plus one standard deviation); 2, "Med-Low" (values falling between the mean and the mean plus one standard deviation); 3, "Med-High" (values falling between the mean minus one standard deviation and the mean); 4, "High" (values less than the mean minus one standard deviation). |
| General Data Type | |
| Unit of Measure | |
| Case Restriction | |
| Display Example | |
| Format Mask | |
| Null Value | |
| Null Value Meaning | |
| Allowed Values | |
| Default Value | |
| Foreign Key Relations | |
| Derivation | |
| Validation Rules |
| Attribute Name | Flag_RegionalReference_Labor.Force |
|---|---|
| Seq. Order | 14 |
| Data Storage Type | NUMBER |
| Max Length | |
| Min Length | |
| Required | No |
| Primary Key | No |
| Precision | |
| Scale | |
| Status | Active |
| Description |
Leveled Labor Force Structure Metric: Labor Force Structure principal component analysis (PCA) data broken into four levels dependent upon the distribution of values within a Census County Division's region: 1, "Low" (values greater than mean plus one standard deviation); 2, "Med-Low" (values falling between the mean and the mean plus one standard deviation); 3, "Med-High" (values falling between the mean minus one standard deviation and the mean); 4, "High" (values less than the mean minus one standard deviation). |
| General Data Type | |
| Unit of Measure | |
| Case Restriction | |
| Display Example | |
| Format Mask | |
| Null Value | |
| Null Value Meaning | |
| Allowed Values | |
| Default Value | |
| Foreign Key Relations | |
| Derivation | |
| Validation Rules |
| Attribute Name | Flag_RegionalReference_Personal.Disruption |
|---|---|
| Seq. Order | 15 |
| Data Storage Type | NUMBER |
| Max Length | |
| Min Length | |
| Required | No |
| Primary Key | No |
| Precision | |
| Scale | |
| Status | Active |
| Description |
Leveled Personal Disruption Metric: Personal Disruption principal component analysis (PCA) data broken into four levels dependent upon the distribution of values within a Census County Division's region: 1, "Low" (values greater than mean plus one standard deviation); 2, "Med-Low" (values falling between the mean and the mean plus one standard deviation); 3, "Med-High" (values falling between the mean minus one standard deviation and the mean); 4, "High" (values less than the mean minus one standard deviation). |
| General Data Type | |
| Unit of Measure | |
| Case Restriction | |
| Display Example | |
| Format Mask | |
| Null Value | |
| Null Value Meaning | |
| Allowed Values | |
| Default Value | |
| Foreign Key Relations | |
| Derivation | |
| Validation Rules |
| Attribute Name | Flag_RegionalReference_Population.Comp. |
|---|---|
| Seq. Order | 16 |
| Data Storage Type | NUMBER |
| Max Length | |
| Min Length | |
| Required | No |
| Primary Key | No |
| Precision | |
| Scale | |
| Status | Active |
| Description |
Leveled Population Composition Metric: Population Composition principal component analysis (PCA) data broken into four levels dependent upon the distribution of values within a Census County Division's region: 1, "Low" (values greater than mean plus one standard deviation); 2, "Med-Low" (values falling between the mean and the mean plus one standard deviation); 3, "Med-High" (values falling between the mean minus one standard deviation and the mean); 4, "High" (values less than the mean minus one standard deviation). |
| General Data Type | |
| Unit of Measure | |
| Case Restriction | |
| Display Example | |
| Format Mask | |
| Null Value | |
| Null Value Meaning | |
| Allowed Values | |
| Default Value | |
| Foreign Key Relations | |
| Derivation | |
| Validation Rules |
| Attribute Name | Flag_RegionalReference_Poverty |
|---|---|
| Seq. Order | 17 |
| Data Storage Type | NUMBER |
| Max Length | |
| Min Length | |
| Required | No |
| Primary Key | No |
| Precision | |
| Scale | |
| Status | Active |
| Description |
Leveled Poverty Metric: Poverty principal component analysis (PCA) data broken into four levels dependent upon the distribution of values within a Census County Division's region: 1, "Low" (values greater than mean plus one standard deviation); 2, "Med-Low" (values falling between the mean and the mean plus one standard deviation); 3, "Med-High" (values falling between the mean minus one standard deviation and the mean); 4, "High" (values less than the mean minus one standard deviation). |
| General Data Type | |
| Unit of Measure | |
| Case Restriction | |
| Display Example | |
| Format Mask | |
| Null Value | |
| Null Value Meaning | |
| Allowed Values | |
| Default Value | |
| Foreign Key Relations | |
| Derivation | |
| Validation Rules |
| Attribute Name | Flag_RegionalReference_Overall_Aggregate |
|---|---|
| Seq. Order | 18 |
| Data Storage Type | NUMBER |
| Max Length | |
| Min Length | |
| Required | No |
| Primary Key | No |
| Precision | |
| Scale | |
| Status | Active |
| Description |
Number of underlying leveled social vulnerability metrics rated as "High". Values range from 0-5. |
| General Data Type | |
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| Case Restriction | |
| Display Example | |
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| Null Value | |
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Support Roles
| * » Support Role | |
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| * » Date Effective From | |
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| * » Contact | |
| * Contact Instructions |
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Extents
| Currentness Reference |
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Extent Group 1
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Extent Group 1 / Geographic Area
| * » W° Bound | |
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| * » E° Bound | |
| * » N° Bound | |
| * » S° Bound | |
| * » Description |
Extent Group 1 / Vertical Extent
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Extent Group 1 / Time Frame
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Access Information
| * » Security Class | |
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| * Security Classification System |
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| Security Handling Description |
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| • Data Access Policy |
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| » Data Access Procedure |
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| • » Data Access Constraints |
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| • Data Use Constraints |
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Distribution Information
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Activity Log
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FAQs
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Child Items
Rubric scores updated every 15m
| Score | Type | Title |
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Related Items
| Item Type | Relationship Type | Title |
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Catalog Details
| Catalog Item ID | 59259 |
|---|---|
| Metadata Record Created By | Annette M DesRochers |
| Metadata Record Created | 2020-04-08 22:48+0000 |
| Metadata Record Last Modified By | SysAdmin InPortAdmin |
| » Metadata Record Last Modified | 2022-08-09 17:11+0000 |
| Metadata Record Published | 2020-06-26 |
| Owner Org | PIFSC |
| Metadata Publication Status | Published Externally |
| Do Not Publish? | N |
| Metadata Workflow State | Published / External |
| Metadata Last Review Date | 2020-06-26 |
| Metadata Review Frequency | 1 Year |
| Metadata Next Review Date | 2021-06-26 |
| Tags |
|---|