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![[ ] , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ["country", "year", "age", "concept", "sex"] To make sense of this array, dimensions must be ordered.](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-39-2048.jpg)
![["country", "year", "age", "concept", "sex"] Criterion: What does not change, first. To make sense of this array, dimensions must be ordered. (Position of dimensions of size 1 is irrelevant.)](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-40-2048.jpg)
!["value" : [ … ] } { "version" : "2.0", "class" : "dataset", "label" : "Population by sex and age group. Canada. 2012", "source" : "Statistics Canada, CANSIM, table 051-0001", "updated" : "2012-09-27", "id" : [ "country" , "year" , "age" , "concept" , "sex" ], "size" : [ 1 , 1 , 20 , 2 , 3 ], "role" : { "time" : ["year"] , "geo" : ["country"] , "metric" : ["concept"] }, "dimension" : { … }](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-42-2048.jpg)
!["value" : [ … ] } { "id" : [ "country" , "year" , "age" , "concept" , "sex" ], "size" : [ 1 , 1 , 20 , 2 , 3 ], "role" : { "time" : ["year"] , "geo" : ["country"] , "metric" : ["concept"] }, "dimension" : { "country" : { … }, "year" : { … }, "age" : { … }, "concept" : { … }, "sex" : { … } } "version" : "2.0", "class" : "dataset", "label" : "Population by sex and age group. Canada. 2012", "source" : "Statistics Canada, CANSIM, table 051-0001", "updated" : "2012-09-27",](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-43-2048.jpg)
!["value" : [ … ] } { "id" : [ "country" , "year" , "age" , "concept" , "sex" ], "size" : [ 1 , 1 , 20 , 2 , 3 ], "role" : { "time" : ["year"] , "geo" : ["country"] , "metric" : ["concept"] }, "dimension" : { "country" : { … }, "year" : { … }, "age" : { … }, "concept" : { … }, "sex" : { … } } "version" : "2.0", "class" : "dataset", "label" : "Population by sex and age group. Canada. 2012", "source" : "Statistics Canada, CANSIM, table 051-0001", "updated" : "2012-09-27",](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-45-2048.jpg)
!["sex" : { "label" : "sex", "category" : { "index" : ["T", "M", "F"], "label" : { "T" : "Total", "M" : "Male", "F" : "Female" } } }](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-46-2048.jpg)
!["sex" : { "label" : "sex", "category" : { "index" : ["T", "M", "F"], "label" : { "T" : "Total", "M" : "Male", "F" : "Female" } } } {"T" : 0, "M" : 1, "F" : 2}, Also accepted (faster access)* * See “Arrays vs. Objects” http://bl.ocks.org/5708161](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-47-2048.jpg)
![The “unflattening” problem from dimension positions [0,0,7,0,2]](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-49-2048.jpg)
![The “unflattening” problem from dimension positions to value position 44[0,0,7,0,2]](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-50-2048.jpg)
![[ ] , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ["country", "year", "age", "concept", "sex"]](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-51-2048.jpg)
![[ ] , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ["country", "year", "age", "concept", "sex"] 0 1 2 3 4 5… 44 …120](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-52-2048.jpg)
![Persons (thousands) 2012 Canada ["country", "year", "age", "concept", "sex"] 0 0 0 is the first position (first category of the dimension)](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-53-2048.jpg)
![Persons (thousands) 2012 Canada ["country", "year", "age", "concept", "sex"] 0 0 0 1 2 3 4 5 6 7](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-54-2048.jpg)
![Persons (thousands) 2012 Canada ["country", "year", "age", "concept", "sex"] 0 0 0 1 0](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-55-2048.jpg)
![Persons (thousands) 2012 Canada ["country", "year", "age", "concept", "sex"] 0 0 0 0 1 2](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-56-2048.jpg)
![Persons (thousands) 2012 Canada ["country", "year", "age", "concept", "sex"] 0 0 0 [0, 0, 7, 0, 2] → 44](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-57-2048.jpg)
![2012 Canada ["country", "year", "age", "concept", "sex"] 0 0 0 [ 1, 1, 20, 2, 3 ] Persons (thousands) (Size) [0, 0, 7, 0, 2] → 44](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-58-2048.jpg)
![The“unflattening” problem ["country", "year", "age", "concept", "sex"] [ 1, 1, 20, 2, 3 ] [0, 0, 7, 0, 2] → 44](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-59-2048.jpg)
![The“unflattening” problem ["country", "year", "age", "concept", "sex"] [ 1, 1, 20, 2, 3 ] It’s a simple mathematical problem Compute value position using dimension position & size [0, 0, 7, 0, 2] → 44](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-60-2048.jpg)
![Lost in cells? Are you a coder? Do you want to develop your own library? arr2num( [0,0,7,0,2], [1,1,20,2,3] ) 44](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-63-2048.jpg)
![Lost in cells? Here’s a simple solution to the “unflattening” problem. function arr2num( arr, size ){ for(var i=0, num=0, mult=1, ndims=size.length; i<ndims; i++){ mult*=(i>0) ? size[ndims-i] : 1; num+=mult*arr[ndims-i-1]; } return num; } arr2num( [0,0,7,0,2], [1,1,20,2,3] ) 44](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-64-2048.jpg)
![Lost in cells? Or check the sample code section at http://json-stat.org/tools/ function arr2num( arr, size ){ for(var i=0, num=0, mult=1, ndims=size.length; i<ndims; i++){ mult*=(i>0) ? size[ndims-i] : 1; num+=mult*arr[ndims-i-1]; } return num; }](https://image.slidesharecdn.com/json-stat-130712002843-phpapp02/75/JSON-stat-a-simple-light-standard-for-all-kinds-of-data-disseminators-65-2048.jpg)
Uploaded byXavier Badosa
JSON-stat, a simple light standard for all kinds of data disseminators
The document outlines the JSON-stat standard for disseminating data efficiently, which is designed for various stakeholders like national statistical offices and organizations. It emphasizes the use of JSON format to integrate data and metadata, presenting data in a cube model that simplifies usage for both humans and machines. The document also addresses challenges related to data structure and provides methods for organizing multidimensional data effectively.
JSON-stat, a simple light standard for all kinds of data disseminators
- 1. JSON-stat a simple lightstandard for all kinds of data disseminators Xavier Badosa @badosa http://xavierbadosa.com http://json-stat.org December, 2015
- 2. a simple lightstandard for all kinds of data disseminators Who needs to disseminate data?
- 3. Who needs todisseminate data? Nowadays? Everybody! Of course! NSOs* Central Banks Intl. orgs * National Statistical Offices Companies The media Citizens… But also NGOs a simple light standard for all kinds of data disseminators
- 4. How is datausually disseminated? a simple light standard for all kinds of data disseminators
- 5. How is datausually disseminated? intableform
- 6.
- 7. Wherever there’s data addressedto humans there is (usually) a table
- 8. plain old tables Whyare tables so popular?
- 9. Why are tablesso popular? a display device Tablesare
- 10. a display device withanalytical features
- 11. an abbreviation, acompressor a metadata saver
- 12. a cube model thatavoids repeating metadata for every cell an abbreviation, a compressor a metadata saver
- 13.
- 14. Simple, for everybody?How? a simple light standard for all kinds of data disseminators
- 15. Simple, for everybody?How? If you managed to disseminate data for humans in tables, you should be able to do it for machines with no effort! a simple light standard for all kinds of data disseminators
- 16. JSON is adata format used in most APIs. It can include data and metadata in a single doc. Simple, for everybody? How? In JSON.
- 17. Using a verysimple cube model that mimics a plain old table. Simple, for everybody? How? In JSON-stat.
- 18.
- 19.
- 20.
- 21. What’s the simplestway to express these data in JSON?
- 22. [ ] , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , anarray (flat) What’s the simplestway to express these data in JSON?
- 23.
- 24. [ ] , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , "value" : "class" :"dataset", "label" : "Population by sex and age group. Canada. 2012", "source" : "Statistics Canada, CANSIM, table 051-0001", "updated" : "2012-09-27", } {
- 25. [ ] , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , "value" : } { "id": [ "country" , "year" , "age" , "concept" , "sex" ], "size" : [ 1 , 1 , 20 , 2 , 3 ], "class" : "dataset", "label" : "Population by sex and age group. Canada. 2012", "source" : "Statistics Canada, CANSIM, table 051-0001", "updated" : "2012-09-27", "dimension" : { … } id and size are needed to “unflatten” the value array.
- 26. , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , "id" : ["country" , "year" , "age" , "concept" , "sex" ], "size" : [ 1 , 1 , 20 , 2 , 3 ], "dimension" : { … } id and size are needed to “unflatten” the value array. Method: Row-major order In computing, row-major order and column- major order describe methods for arranging multidimensional arrays in linear storage such as memory.
- 27.
- 28.
- 29.
- 30.
- 31.
- 32.
- 33.
- 34.
- 35.
- 37.
- 38.
- 39. [ ] , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ["country", "year", "age","concept", "sex"] To make sense of this array, dimensions must be ordered.
- 40. ["country", "year", "age","concept", "sex"] Criterion: What does not change, first. To make sense of this array, dimensions must be ordered. (Position of dimensions of size 1 is irrelevant.)
- 41. country year age concept sex CA CA CACA CA CA 2012 2012 2012 2012 2012 2012 Total Total Total Total Total Total Persons Persons Persons % % % Total TotalM M FF What does not change, first.
- 42. "value" : [… ] } { "version" : "2.0", "class" : "dataset", "label" : "Population by sex and age group. Canada. 2012", "source" : "Statistics Canada, CANSIM, table 051-0001", "updated" : "2012-09-27", "id" : [ "country" , "year" , "age" , "concept" , "sex" ], "size" : [ 1 , 1 , 20 , 2 , 3 ], "role" : { "time" : ["year"] , "geo" : ["country"] , "metric" : ["concept"] }, "dimension" : { … }
- 43. "value" : [… ] } { "id" : [ "country" , "year" , "age" , "concept" , "sex" ], "size" : [ 1 , 1 , 20 , 2 , 3 ], "role" : { "time" : ["year"] , "geo" : ["country"] , "metric" : ["concept"] }, "dimension" : { "country" : { … }, "year" : { … }, "age" : { … }, "concept" : { … }, "sex" : { … } } "version" : "2.0", "class" : "dataset", "label" : "Population by sex and age group. Canada. 2012", "source" : "Statistics Canada, CANSIM, table 051-0001", "updated" : "2012-09-27",
- 44. country year age concept sex CA CA CACA CA CA 2012 2012 2012 2012 2012 2012 Total Total Total Total Total Total Persons Persons Persons % % % Total TotalM M FF
- 45. "value" : [… ] } { "id" : [ "country" , "year" , "age" , "concept" , "sex" ], "size" : [ 1 , 1 , 20 , 2 , 3 ], "role" : { "time" : ["year"] , "geo" : ["country"] , "metric" : ["concept"] }, "dimension" : { "country" : { … }, "year" : { … }, "age" : { … }, "concept" : { … }, "sex" : { … } } "version" : "2.0", "class" : "dataset", "label" : "Population by sex and age group. Canada. 2012", "source" : "Statistics Canada, CANSIM, table 051-0001", "updated" : "2012-09-27",
- 46. "sex" : { "label": "sex", "category" : { "index" : ["T", "M", "F"], "label" : { "T" : "Total", "M" : "Male", "F" : "Female" } } }
- 47. "sex" : { "label": "sex", "category" : { "index" : ["T", "M", "F"], "label" : { "T" : "Total", "M" : "Male", "F" : "Female" } } } {"T" : 0, "M" : 1, "F" : 2}, Also accepted (faster access)* * See “Arrays vs. Objects” http://bl.ocks.org/5708161
- 48.
- 49.
- 50. The “unflattening” problem from dimension positions tovalue position 44[0,0,7,0,2]
- 51.
- 52. [ ] , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ["country", "year", "age","concept", "sex"] 0 1 2 3 4 5… 44 …120
- 53. Persons (thousands) 2012 Canada ["country", "year","age", "concept", "sex"] 0 0 0 is the first position (first category of the dimension)
- 54. Persons (thousands) 2012 Canada ["country", "year","age", "concept", "sex"] 0 0 0 1 2 3 4 5 6 7
- 55. Persons (thousands) 2012 Canada ["country", "year","age", "concept", "sex"] 0 0 0 1 0
- 56. Persons (thousands) 2012 Canada ["country", "year","age", "concept", "sex"] 0 0 0 0 1 2
- 57. Persons (thousands) 2012 Canada ["country", "year","age", "concept", "sex"] 0 0 0 [0, 0, 7, 0, 2] → 44
- 58. 2012 Canada ["country", "year", "age","concept", "sex"] 0 0 0 [ 1, 1, 20, 2, 3 ] Persons (thousands) (Size) [0, 0, 7, 0, 2] → 44
- 59. The“unflattening” problem ["country", "year","age", "concept", "sex"] [ 1, 1, 20, 2, 3 ] [0, 0, 7, 0, 2] → 44
- 60. The“unflattening” problem ["country", "year","age", "concept", "sex"] [ 1, 1, 20, 2, 3 ] It’s a simple mathematical problem Compute value position using dimension position & size [0, 0, 7, 0, 2] → 44
- 61. Lost in cells? Method:Row-major order In computing, row-major order and column- major order describe methods for arranging multidimensional arrays in linear storage such as memory.
- 62. Lost in cells? There’sa Javascript library that takes care of this.
- 63. Lost in cells? Areyou a coder? Do you want to develop your own library? arr2num( [0,0,7,0,2], [1,1,20,2,3] ) 44
- 64. Lost in cells? Here’sa simple solution to the “unflattening” problem. function arr2num( arr, size ){ for(var i=0, num=0, mult=1, ndims=size.length; i<ndims; i++){ mult*=(i>0) ? size[ndims-i] : 1; num+=mult*arr[ndims-i-1]; } return num; } arr2num( [0,0,7,0,2], [1,1,20,2,3] ) 44
- 65. Lost in cells? Orcheck the sample code section at http://json-stat.org/tools/ function arr2num( arr, size ){ for(var i=0, num=0, mult=1, ndims=size.length; i<ndims; i++){ mult*=(i>0) ? size[ndims-i] : 1; num+=mult*arr[ndims-i-1]; } return num; }
- 66.
- 67.
- 68. all pictures from Blockspicture in slide 1: Soma, by Dru! (CC BY-NC) Cubic head in slide 13: Portrait by Thomas Leth-Olsen (CC BY) Rubik’s Cube in slide 18: BW Rubik’s Cube, by Gerwin Sturm (CC BY-SA) Shiny cube in slide 48: SONY DSC, by Javier Manso (CC BY-NC-SA) Walking girl in slide 61: Sterile, by Lee Nachtigal (CC BY) Atomium in slide 66: Fighting Gravity – Atomium, Brussels, by Jan Faborsky (CC BY-NC-ND) Eggs in slide 77: Eggs n. 3, by Leonardo D’Amico (CC BY-SA-ND)