---
title: "Vector Read Benchmarks"
output: html_document
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

Vector read benchmarks for R package **gdalraster**\
(last updated 2025-12-14)

The following benchmark tests follow the format of benchmarks described in GDAL [RFC 86: Column-oriented read API for vector layers](https://gdal.org/en/stable/development/rfc/rfc86_column_oriented_api.html#benchmarks) using the same dataset. The timings here cannot be compared directly with the GDAL timings due to hardware differences (hardware used for the GDAL benchmarks is not specified). The benchmarks are intended as a sanity check on read performance in the context of ranges seen for two different I/O methods (traditional GetNextFeature() iteration vs. column-oriented ArrowArrayStream), and multiple implementations in both plain C++ and using Python libraries as described for the GDAL benchmarks, and using R packages described here.

The C++ benchmark programs used in RFC 86 are also included here to measure baseline raw performance under the same hardware and software environment. Directly comparing the timings between the .cpp and .R programs in their current forms should consider that the  cpp programs both read the 3.3 million features in the test dataset but do not populate a data structure, while the R programs populate a data frame object and return it.

## Hardware

Dell XPS 13 laptop 9350 (2024 edition), Intel® Core™ Ultra 7 258V x 8 cores up to 4.8 GHz Lunar Lake CPU, 32GB LPDDR5X RAM 8533MT/s integrated, 1 TB SSD

## Software environment

Ubuntu Linux 24.04.3 LTS, R 4.5.2 (2025-10-31), GDAL 3.12.0 (released 2025-11-03) local build, **gdalraster** 2.3.0.9007, **sf** 1.0.23

## Vector data

NZ Building Outlines, <https://data.linz.govt.nz/layer/101290-nz-building-outlines/>, from Land Information New Zealand: "This dataset provides current outlines of buildings within mainland New Zealand captured from the latest aerial imagery."

Tests used the GeoPackage file nz-building-outlines.gpkg (1.5 GB). The layer contains 3.3 million features, each with 13 attribute fields (2 fields of type Integer, 8 of type String, 3 of type DateTime) and polygon geometries.

## Benchmark programs

Each program reads all features from the layer and populates an R data frame. Code for the programs along with output generated by `reprex::reprex()` is given in a separate section further below.

**bench_ogr.cpp**

Benchmark C++ program used in RFC 86, re-run here for comparisons within the same hardware/software environment. Use of traditional `OGRLayer::GetNextFeature()` and related API from C. Reads each feature but does not populate a data structure, representing baseline raw performance.

**bench_gdalraster_fetch.R**

Uses the class method `GDALVector$fetch()` in **gdalraster** for traditional row-level reading done in C++ iterating over features with `OGRLayer::GetNextFeature()` in the GDAL API. The method is an analog of function `DBI::dbFetch()` in the **DBI** R package.

**bench_gdalraster_fetch_conv_to_sf.R**

The same as bench_gdalraster_fetch.R (traditional row-level access) but with conversion to a classed **sf** data frame via `sf::st_sf()` included in the timing.

**bench_sf_read_sf.R**

Traditional row-level read using package **sf** for its function `sf::read_sf()`. Populates a classed data frame, with geometries contained in a classed list column.

**bench_ogr_batch.cpp**

Benchmark C++ program used in RFC 86, re-run here for comparisons within the same hardware/software environment. Use of the `GetNextRecordBatch()` API from C++ with GDAL >= 3.6. Reads each feature but does not populate a data structure, representing baseline raw performance with the Array Stream interface.

**bench_gdalraster_arrow_stream.R** (requires GDAL >= 3.6)

Uses the class method `GDALVector$getArrowStream()` in **gdalraster** to expose an Arrow C stream on the layer as a `nanoarrow_array_stream` object (external pointer to an ArrowArrayStream). Provides direct access to the stream object and retrieves features in a column-oriented memory layout. The required package **nanoarrow** provides S3 methods for `as.data.frame()` to import a `nanoarrow_array` (one batch at a time), or the `nanoarrow_array_stream` itself (pulling all batches in the stream).

**bench_sf_read_sf_use_stream.R** (requires GDAL >= 3.6)

Uses `sf::read_sf()` with argument `use_stream = TRUE`: "use the experimental columnar interface introduced in GDAL 3.6".

## Timings

```{r, echo = FALSE}
bench_program <- c("bench_ogr.cpp (C++ raw perf)",
                   "bench_gdalraster_fetch.R",
                   "bench_gdalraster_fetch_conv_to_sf.R",
                   "bench_sf_read_sf.R",
                   "bench_ogr_batch.cpp (C++ raw perf)",
                   "bench_gdalraster_arrow_stream.R",
                   "bench_sf_read_sf_use_stream.R")

timing <- c(2.63, 11.20, 25.01, 77.24, 0.45, 2.87, 11.17)

df_class <- c("none", "OGRFeatureSet", "sf", "sf", "none", "base data.frame",
              "sf")

geom_col <- c("n/a", "WKB `raw` vectors", "classed sfc", "classed sfc", "n/a",
              "WKB `raw` vectors", "classed sfc")

tbl <- data.frame(Bench_program = bench_program, Time_1s2 = timing,
                  Data_frame_class = df_class, Geom_list_column = geom_col)

col_names <- gsub("[_]", " ", names(tbl))
col_names <- gsub("[1]", "(", col_names)
col_names <- gsub("[2]", ")", col_names)
cap <- "Read nz-building-outlines.gpkg (1.5 GB) and populate a data frame."
knitr::kable(tbl, col.names = col_names, caption = cap)
```

## Code

### bench_ogr.cpp ([RFC86 benchmark](https://gdal.org/en/stable/development/rfc/rfc86_column_oriented_api.html#benchmarks))

```cpp
// https://gdal.org/en/stable/development/rfc/rfc86_column_oriented_api.html#benchmarks

#include "gdal_priv.h"
#include "ogr_api.h"
#include "ogrsf_frmts.h"

int main(int argc, char* argv[])
{
    GDALAllRegister();
    GDALDataset* poDS = GDALDataset::Open(argv[1]);
    OGRLayer* poLayer = poDS->GetLayer(0);
    OGRLayerH hLayer = OGRLayer::ToHandle(poLayer);
    OGRFeatureDefnH hFDefn = OGR_L_GetLayerDefn(hLayer);
    int nFields = OGR_FD_GetFieldCount(hFDefn);
    std::vector<OGRFieldType> aeTypes;
    for( int i = 0; i < nFields; i++ )
        aeTypes.push_back(OGR_Fld_GetType(OGR_FD_GetFieldDefn(hFDefn, i)));
    int nYear, nMonth, nDay, nHour, nMin, nSecond, nTZ;
    while( true )
    {
        OGRFeatureH hFeat = OGR_L_GetNextFeature(hLayer);
        if( hFeat == nullptr )
            break;
        OGR_F_GetFID(hFeat);
        for( int i = 0; i < nFields; i++ )
        {
            if( aeTypes[i] == OFTInteger )
                OGR_F_GetFieldAsInteger(hFeat, i);
            else if( aeTypes[i] == OFTInteger64 )
                OGR_F_GetFieldAsInteger64(hFeat, i);
            else if( aeTypes[i] == OFTReal )
                OGR_F_GetFieldAsDouble(hFeat, i);
            else if( aeTypes[i] == OFTString )
                OGR_F_GetFieldAsString(hFeat, i);
            else if( aeTypes[i] == OFTDateTime )
                OGR_F_GetFieldAsDateTime(hFeat, i, &nYear, &nMonth, &nDay, &nHour, &nMin, &nSecond, &nTZ);
        }
        OGRGeometryH hGeom = OGR_F_GetGeometryRef(hFeat);
        if( hGeom )
        {
            int size = OGR_G_WkbSize(hGeom);
            GByte* pabyWKB = static_cast<GByte*>(malloc(size));
            OGR_G_ExportToIsoWkb( hGeom, wkbNDR, pabyWKB);
            CPLFree(pabyWKB);
        }
        OGR_F_Destroy(hFeat);
    }
    delete poDS;
    return 0;
}
```

```bash
$ g++ bench_ogr.cpp -o bench_ogr -O3 `pkg-config --cflags --libs gdal`
$ time ./bench_ogr '/home/ctoney/data/gis/nz-building-outlines/nz-building-outlines.gpkg'

real  0m2.631s
user  0m2.458s
sys	  0m0.172s
```

### bench_gdalraster_fetch.R

```r
library(gdalraster)
#> GDAL 3.10.3 (released 2025-04-01), GEOS 3.12.2, PROJ 9.4.1

f <- '/home/ctoney/data/gis/nz-building-outlines/nz-building-outlines.gpkg'
(lyr <- new(GDALVector, f))
#> C++ object of class GDALVector
#>  Driver : GeoPackage (GPKG)
#>  DSN    : /home/ctoney/data/gis/nz-building-outlines/nz-building-outlines.gpkg
#>  Layer  : nz_building_outlines
#>  CRS    : NZGD2000 / New Zealand Transverse Mercator 2000 (EPSG:2193)
#>  Geom   : MULTIPOLYGON

lyr$getFeatureCount()
#> [1] 3289574

system.time(d <- lyr$fetch(-1))
#>    user  system elapsed 
#>  10.383   0.702  11.200

(nrow(d) == lyr$getFeatureCount())
#> [1] TRUE

head(d)
#> OGR feature set
#>   FID building_id name     use suburb_locality town_city territorial_authority
#> 1   1     2292051      Unknown          Marton    Marton   Rangitikei District
#> 2   2     2292353      Unknown      Durie Hill Whanganui    Whanganui District
#> 3   3     2292407      Unknown      Durie Hill Whanganui    Whanganui District
#> 4   4     2292675      Unknown        Feilding  Feilding     Manawatu District
#> 5   5     2292771      Unknown        Feilding  Feilding     Manawatu District
#> 6   6     2292825      Unknown        Feilding  Feilding     Manawatu District
#>       capture_method capture_source_group capture_source_id
#> 1 Feature Extraction    NZ Aerial Imagery              1042
#> 2 Feature Extraction    NZ Aerial Imagery              1042
#> 3 Feature Extraction    NZ Aerial Imagery              1042
#> 4 Feature Extraction    NZ Aerial Imagery              1042
#> 5 Feature Extraction    NZ Aerial Imagery              1042
#> 6 Feature Extraction    NZ Aerial Imagery              1042
#>                                       capture_source_name capture_source_from
#> 1 Manawatu Whanganui 0.3m Rural Aerial Photos (2015-2016)          2015-12-27
#> 2 Manawatu Whanganui 0.3m Rural Aerial Photos (2015-2016)          2015-12-27
#> 3 Manawatu Whanganui 0.3m Rural Aerial Photos (2015-2016)          2015-12-27
#> 4 Manawatu Whanganui 0.3m Rural Aerial Photos (2015-2016)          2015-12-27
#> 5 Manawatu Whanganui 0.3m Rural Aerial Photos (2015-2016)          2015-12-27
#> 6 Manawatu Whanganui 0.3m Rural Aerial Photos (2015-2016)          2015-12-27
#>   capture_source_to last_modified                                  geom
#> 1        2016-04-21    2019-01-04 WKB MULTIPOLYGON: raw 01 06 00 00 ...
#> 2        2016-04-21    2019-01-04 WKB MULTIPOLYGON: raw 01 06 00 00 ...
#> 3        2016-04-21    2019-01-04 WKB MULTIPOLYGON: raw 01 06 00 00 ...
#> 4        2016-04-21    2019-01-04 WKB MULTIPOLYGON: raw 01 06 00 00 ...
#> 5        2016-04-21    2019-01-04 WKB MULTIPOLYGON: raw 01 06 00 00 ...
#> 6        2016-04-21    2019-01-04 WKB MULTIPOLYGON: raw 01 06 00 00 ...

lyr$close()
```
<sup>Created on 2025-12-13 with [reprex v2.1.1](https://reprex.tidyverse.org)</sup>

### bench_gdalraster_fetch_conv_to_sf.R

```r
library(gdalraster)
#> GDAL 3.10.3 (released 2025-04-01), GEOS 3.12.2, PROJ 9.4.1

f <- '/home/ctoney/data/gis/nz-building-outlines/nz-building-outlines.gpkg'
(lyr <- new(GDALVector, f))
#> C++ object of class GDALVector
#>  Driver : GeoPackage (GPKG)
#>  DSN    : /home/ctoney/data/gis/nz-building-outlines/nz-building-outlines.gpkg
#>  Layer  : nz_building_outlines
#>  CRS    : NZGD2000 / New Zealand Transverse Mercator 2000 (EPSG:2193)
#>  Geom   : MULTIPOLYGON

lyr$getFeatureCount()
#> [1] 3289574

system.time({
    d <- lyr$fetch(-1)
    d <- sf::st_sf(d, crs = lyr$getSpatialRef())
})
#>    user  system elapsed 
#>  23.533   1.395  25.010

(nrow(d) == lyr$getFeatureCount())
#> [1] TRUE

head(d)
#> Simple feature collection with 6 features and 14 fields
#> Geometry type: MULTIPOLYGON
#> Dimension:     XY
#> Bounding box:  xmin: 1776318 ymin: 5544066 xmax: 1818438 ymax: 5576891
#> Projected CRS: NZGD2000 / New Zealand Transverse Mercator 2000
#>   FID building_id name     use suburb_locality town_city territorial_authority
#> 1   1     2292051      Unknown          Marton    Marton   Rangitikei District
#> 2   2     2292353      Unknown      Durie Hill Whanganui    Whanganui District
#> 3   3     2292407      Unknown      Durie Hill Whanganui    Whanganui District
#> 4   4     2292675      Unknown        Feilding  Feilding     Manawatu District
#> 5   5     2292771      Unknown        Feilding  Feilding     Manawatu District
#> 6   6     2292825      Unknown        Feilding  Feilding     Manawatu District
#>       capture_method capture_source_group capture_source_id
#> 1 Feature Extraction    NZ Aerial Imagery              1042
#> 2 Feature Extraction    NZ Aerial Imagery              1042
#> 3 Feature Extraction    NZ Aerial Imagery              1042
#> 4 Feature Extraction    NZ Aerial Imagery              1042
#> 5 Feature Extraction    NZ Aerial Imagery              1042
#> 6 Feature Extraction    NZ Aerial Imagery              1042
#>                                       capture_source_name capture_source_from
#> 1 Manawatu Whanganui 0.3m Rural Aerial Photos (2015-2016)          2015-12-27
#> 2 Manawatu Whanganui 0.3m Rural Aerial Photos (2015-2016)          2015-12-27
#> 3 Manawatu Whanganui 0.3m Rural Aerial Photos (2015-2016)          2015-12-27
#> 4 Manawatu Whanganui 0.3m Rural Aerial Photos (2015-2016)          2015-12-27
#> 5 Manawatu Whanganui 0.3m Rural Aerial Photos (2015-2016)          2015-12-27
#> 6 Manawatu Whanganui 0.3m Rural Aerial Photos (2015-2016)          2015-12-27
#>   capture_source_to last_modified                           geom
#> 1        2016-04-21    2019-01-04 MULTIPOLYGON (((1796394 556...
#> 2        2016-04-21    2019-01-04 MULTIPOLYGON (((1776394 557...
#> 3        2016-04-21    2019-01-04 MULTIPOLYGON (((1776322 557...
#> 4        2016-04-21    2019-01-04 MULTIPOLYGON (((1818268 554...
#> 5        2016-04-21    2019-01-04 MULTIPOLYGON (((1818172 554...
#> 6        2016-04-21    2019-01-04 MULTIPOLYGON (((1818436 554...

lyr$close()
```
<sup>Created on 2025-12-13 with [reprex v2.1.1](https://reprex.tidyverse.org)</sup>

### bench_sf_read_sf.R

```r
library(sf)
#> Linking to GEOS 3.12.2, GDAL 3.10.3, PROJ 9.4.1; sf_use_s2() is TRUE

f <- '/home/ctoney/data/gis/nz-building-outlines/nz-building-outlines.gpkg'
system.time(d <- read_sf(f, "nz_building_outlines"))
#>    user  system elapsed 
#> 74.969   2.079  77.238

nrow(d)
#> [1] 3289574

head(d)
#> Simple feature collection with 6 features and 13 fields
#> Geometry type: MULTIPOLYGON
#> Dimension:     XY
#> Bounding box:  xmin: 1776318 ymin: 5544066 xmax: 1818438 ymax: 5576891
#> Projected CRS: NZGD2000 / New Zealand Transverse Mercator 2000
#> # A tibble: 6 × 14
#>   building_id name  use     suburb_locality town_city territorial_authority
#>         <int> <chr> <chr>   <chr>           <chr>     <chr>                
#> 1     2292051 ""    Unknown Marton          Marton    Rangitikei District  
#> 2     2292353 ""    Unknown Durie Hill      Whanganui Whanganui District   
#> 3     2292407 ""    Unknown Durie Hill      Whanganui Whanganui District   
#> 4     2292675 ""    Unknown Feilding        Feilding  Manawatu District    
#> 5     2292771 ""    Unknown Feilding        Feilding  Manawatu District    
#> 6     2292825 ""    Unknown Feilding        Feilding  Manawatu District    
#> # ℹ 8 more variables: capture_method <chr>, capture_source_group <chr>,
#> #   capture_source_id <int>, capture_source_name <chr>,
#> #   capture_source_from <date>, capture_source_to <date>, last_modified <date>,
#> #   geom <MULTIPOLYGON [m]>
```
<sup>Created on 2025-12-13 with [reprex v2.1.1](https://reprex.tidyverse.org)</sup>

### bench_ogr_batch.cpp ([RFC86 benchmark](https://gdal.org/en/stable/development/rfc/rfc86_column_oriented_api.html#benchmarks))

```cpp
// https://gdal.org/en/stable/development/rfc/rfc86_column_oriented_api.html#benchmarks

#include "gdal_priv.h"
#include "ogr_api.h"
#include "ogrsf_frmts.h"
#include "ogr_recordbatch.h"

int main(int argc, char* argv[])
{
    GDALAllRegister();
    GDALDataset* poDS = GDALDataset::Open(argv[1]);
    OGRLayer* poLayer = poDS->GetLayer(0);
    OGRLayerH hLayer = OGRLayer::ToHandle(poLayer);
    struct ArrowArrayStream stream;
    if( !OGR_L_GetArrowStream(hLayer, &stream, nullptr))
    {
        CPLError(CE_Failure, CPLE_AppDefined, "OGR_L_GetArrowStream() failed\n");
        exit(1);
    }
    while( true )
    {
        struct ArrowArray array;
        if( stream.get_next(&stream, &array) != 0 ||
            array.release == nullptr )
        {
            break;
        }
        array.release(&array);
    }
    stream.release(&stream);
    delete poDS;
    return 0;
}
```

```bash
$ g++ bench_ogr_batch.cpp -o bench_ogr_batch -O3 `pkg-config --cflags --libs gdal`
$ time ./bench_ogr_batch '/home/ctoney/data/gis/nz-building-outlines/nz-building-outlines.gpkg'

real  0m0.448s
user  0m1.040s
sys   0m0.562s
```

### bench_gdalraster_arrow_stream.R

```r
library(gdalraster)
#> GDAL 3.10.3 (released 2025-04-01), GEOS 3.12.2, PROJ 9.4.1

f <- '/home/ctoney/data/gis/nz-building-outlines/nz-building-outlines.gpkg'
(lyr <- new(GDALVector, f))
#> C++ object of class GDALVector
#>  Driver : GeoPackage (GPKG)
#>  DSN    : /home/ctoney/data/gis/nz-building-outlines/nz-building-outlines.gpkg
#>  Layer  : nz_building_outlines
#>  CRS    : NZGD2000 / New Zealand Transverse Mercator 2000 (EPSG:2193)
#>  Geom   : MULTIPOLYGON

lyr$getFeatureCount()
#> [1] 3289574

lyr$testCapability()$FastGetArrowStream
#> [1] TRUE

options(nanoarrow.warn_unregistered_extension = FALSE)

(stream <- lyr$getArrowStream())
#> <nanoarrow_array_stream struct<fid: int64, building_id: int32, name: string, use: string, suburb_locality: string, town_city: string, territorial_authority: string, capture_method: string, capture_source_group: string, capture_source_id: int32, capture_source_name: string, capture_source_from: date32, capture_source_to: date32, last_modified: date32, geom: ogc.wkb{binary}>>
#>  $ get_schema:function ()  
#>  $ get_next  :function (schema = x$get_schema(), validate = TRUE)  
#>  $ release   :function ()

system.time(d <- as.data.frame(stream))
#>    user  system elapsed 
#>   3.223   0.856   2.870

stream$release()

(nrow(d) == lyr$getFeatureCount())
#> [1] TRUE

head(d)
#>   fid building_id name     use suburb_locality town_city territorial_authority
#> 1   1     2292051      Unknown          Marton    Marton   Rangitikei District
#> 2   2     2292353      Unknown      Durie Hill Whanganui    Whanganui District
#> 3   3     2292407      Unknown      Durie Hill Whanganui    Whanganui District
#> 4   4     2292675      Unknown        Feilding  Feilding     Manawatu District
#> 5   5     2292771      Unknown        Feilding  Feilding     Manawatu District
#> 6   6     2292825      Unknown        Feilding  Feilding     Manawatu District
#>       capture_method capture_source_group capture_source_id
#> 1 Feature Extraction    NZ Aerial Imagery              1042
#> 2 Feature Extraction    NZ Aerial Imagery              1042
#> 3 Feature Extraction    NZ Aerial Imagery              1042
#> 4 Feature Extraction    NZ Aerial Imagery              1042
#> 5 Feature Extraction    NZ Aerial Imagery              1042
#> 6 Feature Extraction    NZ Aerial Imagery              1042
#>                                       capture_source_name capture_source_from
#> 1 Manawatu Whanganui 0.3m Rural Aerial Photos (2015-2016)          2015-12-27
#> 2 Manawatu Whanganui 0.3m Rural Aerial Photos (2015-2016)          2015-12-27
#> 3 Manawatu Whanganui 0.3m Rural Aerial Photos (2015-2016)          2015-12-27
#> 4 Manawatu Whanganui 0.3m Rural Aerial Photos (2015-2016)          2015-12-27
#> 5 Manawatu Whanganui 0.3m Rural Aerial Photos (2015-2016)          2015-12-27
#> 6 Manawatu Whanganui 0.3m Rural Aerial Photos (2015-2016)          2015-12-27
#>   capture_source_to last_modified        geom
#> 1        2016-04-21    2019-01-04 blob[102 B]
#> 2        2016-04-21    2019-01-04 blob[102 B]
#> 3        2016-04-21    2019-01-04 blob[230 B]
#> 4        2016-04-21    2019-01-04 blob[102 B]
#> 5        2016-04-21    2019-01-04 blob[118 B]
#> 6        2016-04-21    2019-01-04 blob[102 B]

lyr$close()
```
<sup>Created on 2025-12-13 with [reprex v2.1.1](https://reprex.tidyverse.org)</sup>

### bench_sf_read_sf_use_stream.R

```r
library(sf)
#> Linking to GEOS 3.12.2, GDAL 3.10.3, PROJ 9.4.1; sf_use_s2() is TRUE

f <- '/home/ctoney/data/gis/nz-building-outlines/nz-building-outlines.gpkg'
system.time(d <- read_sf(f, "nz_building_outlines", use_stream = TRUE))
#>    user  system elapsed 
#>  10.876   1.453  11.168

nrow(d)
#> [1] 3289574

head(d)
#> Simple feature collection with 6 features and 13 fields
#> Geometry type: MULTIPOLYGON
#> Dimension:     XY
#> Bounding box:  xmin: 1776318 ymin: 5544066 xmax: 1818438 ymax: 5576891
#> Projected CRS: NZGD2000 / New Zealand Transverse Mercator 2000
#> # A tibble: 6 × 14
#>   building_id name  use     suburb_locality town_city territorial_authority
#>         <int> <chr> <chr>   <chr>           <chr>     <chr>                
#> 1     2292051 ""    Unknown Marton          Marton    Rangitikei District  
#> 2     2292353 ""    Unknown Durie Hill      Whanganui Whanganui District   
#> 3     2292407 ""    Unknown Durie Hill      Whanganui Whanganui District   
#> 4     2292675 ""    Unknown Feilding        Feilding  Manawatu District    
#> 5     2292771 ""    Unknown Feilding        Feilding  Manawatu District    
#> 6     2292825 ""    Unknown Feilding        Feilding  Manawatu District    
#> # ℹ 8 more variables: capture_method <chr>, capture_source_group <chr>,
#> #   capture_source_id <int>, capture_source_name <chr>,
#> #   capture_source_from <date>, capture_source_to <date>, last_modified <date>,
#> #   geom <MULTIPOLYGON [m]>
```
<sup>Created on 2025-12-13 with [reprex v2.1.1](https://reprex.tidyverse.org)</sup>
