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For the data types boolean, numbers, strings and null it is recommended to log them as given.
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#### Arrays
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It is recommended to summarize arrays as follows:
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```js
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{
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"data": [3,1,6,4,8], // Return a reasonable excerpt of the data, e.g. the first 5 or 10 elements
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"length":10, // Return the length of the array, this is important to determine whether the data above is complete or an excerpt
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"min":0, // optional: Return additional statstics if possible, ideally use the corresponsing openEO process names as keys
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"max":10
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"data": [3,1,6,4,8], // Return a reasonable excerpt of the data, e.g. the first 5 or 10 elements
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"length":10, // Return the length of the array, this is important to determine whether the data above is complete or an excerpt
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"min":0, // optional: Return additional statstics if possible, ideally use the corresponsing openEO process names as keys
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"max":10
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}
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```
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@@ -178,38 +181,38 @@ The top-level object and/or each dimension can be enhanced with additional stats
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```js
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{
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"cube:dimensions": {
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"x": {
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"type":"spatial",
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"axis":"x",
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"extent": [8.253, 12.975],
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"reference_system":4326
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},
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"y": {
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"type":"spatial",
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"axis":"y",
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"extent": [51.877,55.988],
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"reference_system":4326
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},
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"t": {
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"type":"temporal",
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"values": [
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"2015-06-21T12:56:55Z",
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"2015-06-23T09:12:14Z",
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"2015-06-25T23:44:44Z",
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"2015-06-27T21:11:34Z",
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"2015-06-30T17:33:12Z"
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],
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"step":null
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},
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"bands": {
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"type":"bands",
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"values": ["NDVI"]
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}
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},
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// optional: Return additional data or statstics for the data cube if possible (see also the chapter for "Arrays" above).
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"min":-1,
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"max":1
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"cube:dimensions": {
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"x": {
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"type":"spatial",
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"axis":"x",
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"extent": [8.253, 12.975],
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"reference_system":4326
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},
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"y": {
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"type":"spatial",
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"axis":"y",
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"extent": [51.877,55.988],
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"reference_system":4326
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},
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"t": {
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"type":"temporal",
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"values": [
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"2015-06-21T12:56:55Z",
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"2015-06-23T09:12:14Z",
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"2015-06-25T23:44:44Z",
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"2015-06-27T21:11:34Z",
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"2015-06-30T17:33:12Z"
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],
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"step":null
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},
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"bands": {
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"type":"bands",
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"values": ["NDVI"]
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}
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},
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// optional: Return additional data or statstics for the data cube if possible (see also the chapter for "Arrays" above).
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"min":-1,
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"max":1
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}
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```
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@@ -221,8 +224,9 @@ To improve interoperability openEO processes, version 1.2.0 added details about
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A survey has shown that most libraries implement type 7 and as such this was chosen to be the default.
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We have found some libraries that can be used for an implementation:
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- Java: [Apache Commons Math Percentile](http://commons.apache.org/proper/commons-math/javadocs/api-3.6/org/apache/commons/math3/stat/descriptive/rank/Percentile.html), choose the [estimation type `R_7`](http://commons.apache.org/proper/commons-math/javadocs/api-3.6/org/apache/commons/math3/stat/descriptive/rank/Percentile.EstimationType.html#R_7)
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- JavaScript: [d3](https://github.com/d3/d3-array/blob/v2.8.0/README.md#quantile), has only type 7 implemented.
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- Julia: [Statistics.quantile](https://docs.julialang.org/en/v1/stdlib/Statistics/#Statistics.quantile!), type 7 is the default.
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- Python: [numpy](https://numpy.org/doc/stable/reference/generated/numpy.quantile.html), [pandas](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.quantile.html), [xarray](http://xarray.pydata.org/en/stable/generated/xarray.DataArray.quantile.html) - type 7 (called 'linear' for the interpolation parameter) is the default for all of them.
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- Python: [numpy](https://numpy.org/doc/stable/reference/generated/numpy.quantile.html), [pandas](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.quantile.html), [xarray](http://xarray.pydata.org/en/stable/generated/xarray.DataArray.quantile.html) - type 7 (called 'linear' for the interpolation parameter) is the default for all of them.
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- R: [quantile](https://stat.ethz.ch/R-manual/R-patched/library/stats/html/quantile.html) - type 7 is the default.
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