JSON-stat, a simple light standard for all kinds of data disseminators

JSON-stat
a simple light standard
for all kinds of data disseminators
Xavier Badosa
@badosa
http://xavierbadosa.com
http://json-stat.org
December, 2015

Who needs to disseminate data?

Who needs to disseminate data?
Nowadays? Everybody!
Of course!
NSOs*
Central Banks
Intl. orgs
* National Statistical Offices
Companies
The media
Citizens…
But also
NGOs

How is data usually disseminated?

How is data usually disseminated?
intableform

Wherever there’s data
addressed to humans
there is (usually) a table

plain old tables
Why are tables so popular?

Why are tables so popular?
a display device
Tablesare

a display device
with analytical features

an abbreviation, a compressor
a metadata saver

a cube model
that avoids
repeating
metadata
for every cell
an abbreviation, a compressor
a metadata saver

Cubic
Thinking
Describe data
in dimension terms

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!

JSON is a data format used in
most APIs. It can include data
and metadata in a single doc.
In JSON.

Using a very simple cube model
that mimics a plain old table.
In JSON-stat.

What’s the simplest way to express these data in JSON?

[
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anarray
(flat)
What’s the simplest way to express these data in JSON?

[
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Basic metadata?

[
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"value" :
"class" : "dataset",
"label" : "Population by sex and age group. Canada. 2012",
"source" : "Statistics Canada, CANSIM, table 051-0001",
"updated" : "2012-09-27",
}
{

[
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"value" :
}
{
"id" : [ "country" , "year" , "age" , "concept" , "sex" ],
"size" : [ 1 , 1 , 20 , 2 , 3 ],
"updated" : "2012-09-27",
"dimension" : { … }
id and size are needed to “unflatten” the value array.

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"size" : [ 1 , 1 , 20 , 2 , 3 ],
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.

value
note/source/updated
label

age 20 categories
dimension
Size

age
Role
20 class
dimension
Size

age
concept
20
2
class
metric
dimension
RoleSize

age
concept
sex
20
2
3
class
metric
class
dimension
RoleSize

age
concept
sex
country
20
2
3
1
class
metric
class
geo
dimension
RoleSize

age
concept
sex
country
year
20
2
3
1
1
class
metric
class
geo
time
dimension
RoleSize

JSON-stat, a simple light standard for all kinds of data disseminators

Persons (thousands)
2012
Canada

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To make sense of this array, dimensions must be ordered.

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["country", "year", "age", "concept", "sex"]

Criterion:
What does not change, first.
(Position of dimensions of size 1 is irrelevant.)

country
year
age
concept
sex
CA CA CA CA 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.

"value" : [ … ]
}
{
"version" : "2.0",
"updated" : "2012-09-27",
"size" : [ 1 , 1 , 20 , 2 , 3 ],
"role" : { "time" : ["year"] , "geo" : ["country"] , "metric" : ["concept"] },

"value" : [ … ]
}
{
"size" : [ 1 , 1 , 20 , 2 , 3 ],
"role" : { "time" : ["year"] , "geo" : ["country"] , "metric" : ["concept"] },
"dimension" : {
"country" : { … },
"year" : { … },
"age" : { … },
"concept" : { … },
"sex" : { … }
}
"version" : "2.0",
"updated" : "2012-09-27",

country
year
age
concept
sex
CA CA CA CA CA CA
2012 2012 2012 2012 2012 2012
Total Total Total Total Total Total
Persons Persons Persons % % %
Total TotalM M FF

"sex" : {
"label" : "sex",
"category" : {
"index" : ["T", "M", "F"],
"label" : {
"T" : "Total",
"M" : "Male",
"F" : "Female"
}
}
}

"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

The “unflattening” problem

from
dimension
positions
[0,0,7,0,2]

from
dimension
positions
to value
position
44[0,0,7,0,2]

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[
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0 1 2 3 4 5…
44
…120

Persons (thousands)
2012
Canada
0
0
0 is the first position
(first category of the dimension)

Persons (thousands)
2012
Canada
0
0
0
1
2
3
4
5
6
7

Persons (thousands)
2012
Canada
0
0
0 1
0

Persons (thousands)
2012
Canada
0
0
0
0 1 2

Persons (thousands)
2012
Canada
0
0
0
[0, 0, 7, 0, 2] → 44

2012
Canada
0
0
0
[ 1, 1, 20, 2, 3 ]
Persons (thousands)
(Size)
[0, 0, 7, 0, 2] → 44

The“unflattening” problem
[ 1, 1, 20, 2, 3 ]
[0, 0, 7, 0, 2] → 44

The“unflattening” problem
[ 1, 1, 20, 2, 3 ]
It’s a simple
mathematical
problem
Compute value
position using
dimension
position & size
[0, 0, 7, 0, 2] → 44

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.

Lost in cells?
There’s a Javascript library that
takes care of this.

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

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

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;
}

The JSON-stat
Ecosystem
format
libs
conn.
schema

all pictures from
Blocks picture 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)

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