Subset

Dataset Title:	VIISTA I VMP JAC CT data
Institution:	Rutgers University (Dataset ID: VIISTAI_2024_06_KM2408_VMP_JAC)
Information:	Summary \| License \| FGDC \| ISO 19115 \| Metadata \| Background \| Data Access Form \| Make a graph

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Select a subset: (Current number of distinct combinations of matching data: 128)
Make as many selections as you want, in any order. Each selection changes the other options (and the map and data below) accordingly.

vmp_no	=	43 options
vmp_prof	=	128 options

View: Map of All Related Data Distinct Data Counts Distinct Data Related Data Counts Related Data

Map of All Related Data

(Refine the map and/or download the image)

To view the map, check View : Map of All Related Data above.

WARNING: This may involve lots of data. For some datasets, this may be slow. Consider using this only when you need it and have selected a small subset of the data.

Distinct Data Counts

To view the counts of distinct combinations of the variables listed above,
check View : Distinct Data Counts above and select a value for one of the variables above.

Distinct Data (Metadata) (Refine the data subset and/or download the data)

vmp_no	vmp_prof

VMP001	VMP001_001
VMP001	VMP001_002
VMP001	VMP001_003
VMP002	VMP002_001
VMP002	VMP002_002
VMP002	VMP002_003
VMP003	VMP003_001
VMP003	VMP003_002
VMP003	VMP003_003
VMP004	VMP004_001
VMP004	VMP004_002
VMP004	VMP004_003
VMP005	VMP005_001
VMP005	VMP005_002
VMP005	VMP005_003
VMP006	VMP006_001
VMP006	VMP006_002
VMP006	VMP006_003
VMP007	VMP007_001
VMP007	VMP007_002
VMP007	VMP007_003
VMP008	VMP008_001
VMP008	VMP008_002
VMP008	VMP008_003
VMP009	VMP009_001
VMP009	VMP009_002
VMP009	VMP009_003
VMP010	VMP010_001
VMP010	VMP010_002
VMP010	VMP010_003
VMP010	VMP010_004
VMP011	VMP011_001
VMP011	VMP011_002
VMP011	VMP011_003
VMP012	VMP012_001
VMP012	VMP012_002
VMP012	VMP012_003
VMP013	VMP013_001
VMP013	VMP013_002
VMP013	VMP013_003
VMP014	VMP014_001
VMP015	VMP015_001
VMP015	VMP015_002
VMP015	VMP015_003
VMP016	VMP016_001
VMP016	VMP016_002
VMP016	VMP016_003
VMP017	VMP017_001
VMP017	VMP017_002
VMP017	VMP017_003
VMP018	VMP018_001
VMP018	VMP018_002
VMP018	VMP018_003
VMP019	VMP019_001
VMP019	VMP019_002
VMP019	VMP019_003
VMP020	VMP020_001
VMP020	VMP020_002
VMP020	VMP020_003
VMP021	VMP021_001
VMP021	VMP021_002
VMP021	VMP021_003
VMP022	VMP022_001
VMP022	VMP022_002
VMP022	VMP022_003
VMP023	VMP023_001
VMP023	VMP023_002
VMP023	VMP023_003
VMP024	VMP024_001
VMP024	VMP024_002
VMP024	VMP024_003
VMP025	VMP025_001
VMP025	VMP025_002
VMP025	VMP025_003
VMP026	VMP026_001
VMP026	VMP026_002
VMP026	VMP026_003
VMP027	VMP027_001
VMP027	VMP027_002
VMP027	VMP027_003
VMP028	VMP028_001
VMP028	VMP028_002
VMP028	VMP028_003
VMP029	VMP029_001
VMP029	VMP029_002
VMP029	VMP029_003
VMP030	VMP030_001
VMP030	VMP030_002
VMP030	VMP030_003
VMP031	VMP031_001
VMP031	VMP031_002
VMP031	VMP031_003
VMP032	VMP032_001
VMP032	VMP032_002
VMP032	VMP032_003
VMP033	VMP033_001
VMP033	VMP033_002
VMP033	VMP033_003
VMP034	VMP034_001
VMP034	VMP034_002
VMP034	VMP034_003
VMP035	VMP035_001
VMP035	VMP035_002
VMP035	VMP035_003
VMP036	VMP036_001
VMP036	VMP036_002
VMP036	VMP036_003
VMP037	VMP037_001
VMP037	VMP037_002
VMP037	VMP037_003
VMP038	VMP038_001
VMP038	VMP038_002
VMP038	VMP038_003
VMP039	VMP039_001
VMP039	VMP039_002
VMP039	VMP039_003
VMP040	VMP040_001
VMP040	VMP040_002
VMP040	VMP040_003
VMP041	VMP041_001
VMP041	VMP041_002
VMP041	VMP041_003
VMP042	VMP042_001
VMP042	VMP042_002
VMP042	VMP042_003
VMP043	VMP043_001
VMP043	VMP043_002
VMP043	VMP043_003

In total, there are 128 rows of distinct combinations of the variables listed above. All of the rows are shown above.
To change the maximum number of rows displayed, change View : Distinct Data above.

Related Data Counts

To view the related data counts,
check View : Related Data Counts above and select a value for one of the variables above.

WARNING: This may involve lots of data. For some datasets, this may be slow. Consider using this only when you need it and have selected a small subset of the data.

To view the related data, change View : Related Data above.

WARNING: This may involve lots of data. For some datasets, this may be slow. Consider using this only when you need it and have selected a small subset of the data.