OrderedCollection [
	GrafoscopioNode {
		#header : 'Panama Papers visual explorer',
		#key : '',
		#body : 'This grafoscopio notebook',
		#children : OrderedCollection [
			GrafoscopioNode {
				#header : 'Quick start',
				#key : '',
				#body : 'This notebook gives you a way to explore a particular visualization using Panama Papers data,
and is a working prototype of reproducible research and data activims.
For a detailed explanation see:

http://mutabit.com/offray/blog/en/entry/panama-papers-1

To explore the notebook select each node at the left and press
the green \"play\" button that will appear above this frame once you 
have selected an executable node.

Start with the node called \"Choropleth Map Quick\".',
				#tags : 'invisible',
				#children : OrderedCollection [
					GrafoscopioNode {
						#header : 'How many offshore by country? (quick)',
						#key : '',
						#body : '\"This visualization runs with a data view that was exported from
the database, so you don\'t need to dowload the full database. 
To execute it, press the green \'play\' button above this frame\"
OffshoreLeaksDB choroplethWorldMapQuick 
',
						#tags : 'c\u00F3digo',
						#children : OrderedCollection [ ],
						#parent : @4,
						#level : 3
					},
					GrafoscopioNode {
						#header : 'How many offshore by country? (deep)',
						#key : '',
						#body : 'Run this steps in order to replicate the data visualization with the full database.
Expand this node clicking on the small triangle at the left of this node\'s name.',
						#children : OrderedCollection [
							GrafoscopioNode {
								#header : 'Download and install the database engine (SQLite)',
								#key : '',
								#body : 'You will need to download and install for your particular platform (Windows, Mac, Gnu/Linux)
to query directly the data.
This part is not made automatically and we are making some  advances there,
but getting SQLite running is pretty straight forward in most platforms.
Look at http://sqlite.org/download.html to and choose the proper one or
use your package installer for this.
',
								#children : OrderedCollection [ ],
								#parent : @8,
								#level : 4
							},
							GrafoscopioNode {
								#header : 'Download the Panama Papers ICIJ database',
								#key : '',
								#body : 'OffshoreLeaksDB downloadDatabase ',
								#tags : 'c\u00F3digo',
								#children : OrderedCollection [ ],
								#parent : @8,
								#level : 4
							},
							GrafoscopioNode {
								#header : 'Unzip database',
								#key : '',
								#body : 'OffshoreLeaksDB unzipDatabase',
								#tags : 'c\u00F3digo',
								#children : OrderedCollection [ ],
								#parent : @8,
								#level : 4
							},
							GrafoscopioNode {
								#header : 'Run the visualization',
								#key : '',
								#body : 'OffshoreLeaksDB choroplethWorldMapFull ',
								#tags : 'c\u00F3digo',
								#children : OrderedCollection [ ],
								#parent : @8,
								#level : 4
							},
							GrafoscopioNode {
								#header : 'Dive into the live coding environment',
								#key : '',
								#body : 'OffshoreLeaksDB class browse',
								#tags : 'c\u00F3digo',
								#children : OrderedCollection [ ],
								#parent : @8,
								#level : 4
							}
						],
						#parent : @4,
						#level : 3
					}
				],
				#parent : @2,
				#level : 2
			},
			GrafoscopioNode {
				#header : 'Updating',
				#key : '',
				#body : '\"To update the code for Grafoscopio run:\"

GrafoscopioBrowser updateDataviz.
GrafoscopioBrowser updateGrafoscopio.

\"For updating the main documentatio run:\"

OffshoreLeaksDB updateIntroNotebook.

\"And remember to visit the projects repositories for
last information at:

- http://mutabit.com/repos.fossil/panama-papers
- http://mutabit.com/repos.fossil/grafoscopio
\"',
				#tags : 'c\u00F3digo',
				#children : OrderedCollection [ ],
				#parent : @2,
				#level : 2
			},
			GrafoscopioNode {
				#header : 'Reach and Limits',
				#key : '',
				#body : 'Each model has its limitations and this is not the exception.
The children nodes here explain wich are the limits and reach
of this visualization',
				#children : OrderedCollection [
					GrafoscopioNode {
						#header : 'Database metrics',
						#key : '',
						#body : '\"To know the total amount of records in each table run:\"
OffshoreLeaksDB databaseMetrics',
						#tags : 'c\u00F3digo',
						#children : OrderedCollection [ ],
						#parent : @22,
						#level : 5
					},
					GrafoscopioNode {
						#header : 'Unmapped territories',
						#key : '',
						#body : '\"Not all territories mentioned in Panama Papers are in the visualization.
This node shows the discrepancies.

Hightlight each line and 
- Print it (press \'ctrl p\' or \'cmd p\')
- or execute it: (press \'ctrl g\' or \'cmd g\')\"

\"Original countries in Roassal:\"
(RTSVGPath class allSelectorsInProtocol: #countries) size.

\"Countries in the Panama Papers SVG Map:\"
OffshoreLeaksDB mappedTerritories.

\"Ummaped territories:\"
OffshoreLeaksDB unmappedTerritories.',
						#tags : 'c\u00F3digo',
						#children : OrderedCollection [ ],
						#parent : @22,
						#level : 5
					}
				],
				#parent : @2,
				#level : 2
			},
			GrafoscopioNode {
				#header : 'Appendix',
				#key : '',
				#body : '',
				#tags : 'invisible',
				#children : OrderedCollection [
					GrafoscopioNode {
						#header : 'For the blog entry',
						#key : '',
						#body : '',
						#children : OrderedCollection [
							GrafoscopioNode {
								#header : 'Initial draft',
								#key : '',
								#body : 'Panama Papers are reported to be the biggest leak in the leaks history[1][https://en.m.wikipedia.org/wiki/Panama_Papers]:
11.5 million confidential documents, 2.5 Terabytes of information, 
over 214.000 offshore companies, 400 journalists, 107 media organizations 
and planet wide implications.
The scale and complexity goes beyond other famous leaks by single
individuals (Snowden) or organizations (Wikileaks).

Despite all of that, 


For the previous reasons, Panama Papers could be an interesting case for and empowering
combination: reproducible research, data activism and frictionless data.
I will show this case on this blog post, while advocacing some technologies and practices
that favor this combination and could help citizen and journalist in keeping the powerful
(politicians, public figures and companies with government contracts) accountable.
Some technologies are widespread but invisible (SQLite), some of them keep
a dialogue between a mostly uknown past and the possible brigther future (Pharo) and 
all could be part of the set of practices and techniques available to the majority
(including data provenance, agile visualization and data packages).
I hope this helps in a conversation that is becoming more urgent and important
and needs more actors in it and shows a more inclusive and plural path that
the popular but complex/opaque one of (too-focused) mobile apps and 
(too layered) web portals.

So lets start by a example that is the product of such technologies combination, 
a graph that uses the released data to show how much off-shore companies are registered 
around the world:

%embed offshores worldmap

Some of that maps have been released in other places (i.e wikipedia and ...), 
but they\'re opaque.
You can\'t see the link between the depicted map and the released data.
You can\'t follow the logic behind the server, only enter particular data and see the 
particular output.
That keep you focused, but limits exploration and makes reproducibility almost
impossible.

But suposse that this static graph is only the end result of another escenario: 
You start with a dynamic environment where you bootstrap
a particular knowledge domain, for example the Panama Papers, and it comes with
a Domain Specific Language (DSL) that let\'s you explore that domain, interactively, 
dinamically, visually.
You have an environment with a continum between code, data, documents, visuals,
and apps and you can see how all whats done.
All is embedded in a single self-contained software artifact and when it talks to external ones, 
that conversation is auditable.
By design the external artifacts are also simple (data packages for describing data, 
SQLite for data bases and fossil for source code management, colaboration and traceability).
In this escenario, the interactive notebook, instead the mobile app or web portal, is the guiding
experience, because it connects our narrative ways of understanding the world (oral, printed and web), 
with visual and numerical ones (binded by data) and because is a gate to others kinds of stories
created by ourselves.
Web/mobile apps could be used for \"zooms\" into certain parts of the interaction/exploration/presentation 
of the visuals, data and the story and could be integrated/exportated from our interactive environment.

This is the video demo for this kind of experience:

Some practices to take into account:

  - Publish small meaniful data. The CVS by the ICIJ is a good starting example.
    Because it is just megabites long, it can be downloaded easily, used for interactive
    exploration, for data workshops and learning and processed almost everywhere.
    Make your data available in community places like datahub.io, that provide solid
    infrastructure, taking care of complexities and giving you a complete API with all
    the metadata
  - SQLite as a file format: This is a powerful [idea by the SQLite author](), which has
    overlooked in the world of big data, clusters, NoSQL and your next trendy word
    here.
    For just 2 mb you get a powerful portable SQL engine for most of your tabular data,
    and providing SQLite files with importations of your CVS files only changes the size
    a couple of megabytes while leveraging a lot of query capabilites on the data.
  - Provide elements for data provenance and integrity: What you do with data needs
    to be traceable. That means making more visible stuff like the integrity codes for
    the files (their associated SHA1/MD5, which by the way are in a meta.xml file provided
    by ICIJ, but not highlighted enough in the main download) and also showing the
    queries and other operations/transformations your doing with the data, by puting
    them into the source code and under proper revision control.
    DVCS like fossil make a really good job for keeping collaboration simple and portable,
    without the complexities of the GitHub and giving you all the metadata.
  - Use interactive envionments for the exploration: You don\'t know ahead what you\'re
    going to find in the data. 
    So the more dynamic and flexible the environment can be, the better. 
    If you can establish a \"continum\" between data and code and visuals even better,
    making the tree talk and encompas each other fluidly.
    The mature Jupyter notebook or the young Grafoscopio are good candidates for this. 
    I used the first one (well its predecessor, IPython) for long time and started the second one 
    over the powerful dynamic foundations of Pharo/Moose/Roassal.
 
If you\'re interested in the ideas/technologies showed in this blog post, I would like to
hear from you.
We can start the conversation right now, in my personal mail or in the Open Knowledge
Foundation community space for that.',
								#children : OrderedCollection [
									GrafoscopioNode {
										#header : '%embed offshores-worldmap',
										#key : '',
										#body : '',
										#children : OrderedCollection [ ],
										#parent : @32,
										#level : 3
									},
									GrafoscopioNode {
										#header : 'mapas de base',
										#key : '',
										#body : 'This notebook part shows how the example visualization was done.
I started with a prebuild [example visualization for world population](https://dl.dropboxusercontent.com/u/31543901/AgileVisualization/BuilderComposition/0204-BuilderComposition.html#compoWorldPopulation) 
of the Agile Visualization Book and change the data for the 
one in the CVS released by ICIJ.
This is not exported in the final html /pdf version of this document,
but mades the process understandable for interesed readers and
beacause there is no gap between document, visualization, data
and app in Pharo/Smalltalk, you can look the code behind this
modificactions.',
										#children : OrderedCollection [
											GrafoscopioNode {
												#header : 'Soporte para SQLite',
												#key : '',
												#body : 'Gofer it
\tsmalltalkhubUser: \'TorstenBergmann\' project: \'UDBC\';
\tconfiguration;
\tload.
(Smalltalk at: #ConfigurationOfUDBC) loadBleedingEdge',
												#tags : 'c\u00F3digo',
												#children : OrderedCollection [ ],
												#parent : @36,
												#level : 3
											},
											GrafoscopioNode {
												#header : 'Profiling',
												#key : '',
												#body : '\"[RTSVGPath countries collect: [ :currentCountry | PanamaPapers totalOffshoresFor: currentCountry ]] timeToRun.  185 segs\"
\"[PanamaPapers totalOffshoresByCountry] timeToRun --> 1 seg\"
\"[PanamaPapers countriesWithOffshores] timeToRun  --> 1 seg\"
\"[PanamaPapers totalOffshoresFor: \'Chile\'] timeToRun --> 1 seg\"
\"[PanamaPapers totalOffshoresByCountry detect: [ :entry | (entry at: \'country_name\') = \'Chile\' ]] timeToRun --> 1 seg\"
\"[PanamaPapers worldMap] timeToRun --> 301 seg, before optimization\"
\"[PanamaPapers worldMap] timeToRun --> 186 seg, after optimization\"',
												#tags : 'c\u00F3digo',
												#children : OrderedCollection [ ],
												#parent : @36,
												#level : 3
											},
											GrafoscopioNode {
												#header : 'Bordes de territorios',
												#key : '',
												#body : '  - [Kartograph](http://wiki.openstreetmap.org/wiki/Kartograph).
  - [Guernsey vs jersey](https://www.wolframalpha.com/input/?i=Guernsey+vs+jersey).
  - [Macau](https://upload.wikimedia.org/wikipedia/commons/3/39/Macau_locator_map.svg)',
												#children : OrderedCollection [ ],
												#parent : @36,
												#level : 3
											},
											GrafoscopioNode {
												#header : 'Panama Papers countries  not present in RTSVGPath',
												#key : '',
												#body : 'PanamaPapers countriesWithOffshores reject: [:eachCountry | 
RTSVGPath countries includes: (eachCountry copyWithout: Character space) ]',
												#tags : 'c\u00F3digo',
												#children : OrderedCollection [ ],
												#parent : @36,
												#level : 3
											},
											GrafoscopioNode {
												#header : 'Countries not present in the Panama Papers',
												#key : '',
												#body : 'RTSVGPath countries select: [ :currentCountry | (PanamaPapers totalOffshoresFor: currentCountry) = nil ]',
												#tags : 'c\u00F3digo',
												#children : OrderedCollection [ ],
												#parent : @36,
												#level : 3
											}
										],
										#parent : @32,
										#level : 3
									}
								],
								#parent : @30,
								#level : 3
							},
							GrafoscopioNode {
								#header : 'Draft alternative 1',
								#key : '',
								#body : 'i belive is a platform particularly suited for reproducible research, exploratory computing and live coding, because it provides a unique continuous experience between data, development environment, interactive documentation, and application. so you can explore a domain/problem and share your insights to let others dive into them. ',
								#children : OrderedCollection [
									GrafoscopioNode {
										#header : 'Possible ending',
										#key : '',
										#body : 'At the beginning of this month (April 3rd), what is called as the biggest leak in history and know as the Panama Papers, 
was revealed and the first batch of public data was released to the public.
At the beginning of the next one (May 9th) the second batch of data will be released.

May be you read your favorite papers coverage on this issue, but at some point you 
and future readers surely will geta panoramic view of whats happening, with the 
[Wikipedia page on Panama Papers](https://en.wikipedia.org/wiki/Panama_Papers).
As all encyclopedias, this is a secondary source, but this article points to almost 400 external
sources to backup its claims, and gives a world map:',
										#children : OrderedCollection [ ],
										#parent : @48,
										#level : 3
									}
								],
								#parent : @30,
								#level : 2
							},
							GrafoscopioNode {
								#header : '%idea Final draft > Panama Papers: a case for reproducible research, data activism and frictionless data ',
								#key : '',
								#body : '---
layout: post
title: \"Panama Papers: a case for reproducible research, data activism and frictionless data\"
description: | 
    Despite being the biggest leak in history upto now in size, reach and complexity, the data released 
    to the general public in this first phase is pretty small (~20 Mb of compressed data). 
    This could open an oportunity for a more democratic comprenhension and participation of the interested 
    citizens with and approach that combines reproducible research, data activims and frictionless data and 
    draw some insights even when more information becomes available soon (May 9, 2016)
taxonomy:
  tag: [data visualization, grafoscopio, roassal, data activism, data journalism, accountability]
image: 
date: \"2016-05-01\"
---',
								#children : OrderedCollection [
									GrafoscopioNode {
										#header : 'Story of two maps',
										#key : '',
										#body : 'Look at the two simple maps above. Both referred to the Panama Papers, but with two visible differences:

- The left one answers to which countries have politicians involved in the Panama Papers and comes from 
  [Wikipedia](https://en.wikipedia.org/wiki/Panama_Papers). 
  The right answers to how many offshore companies are registered by country and was made by me.
- The left  one cannot be reproduced with the public data released when the map was shared.
  The right one can be.

To be able to make the left one reprocible we would need to start by adding two single extra tables in that data, 
that would contain public information, that was shared with the release of the data, just not in tabular form.
In database parlance the first table would be a table of  entities (in this case politicians) and the
second one would be a table of relationships (mapping the onwers of ofshores companies and
those politicians).
This would be the \"data way\" of expressing this medological approach by the ICIJ researchers:

[Miramos los conocidos]

But even adding those tables (or others to come) doesn\'t make those maps easily reproducible.
We need to know the queries used to cross the data and produce aggregated views of the
it, and the code that takes that aggregated data and create the map visualization.

There are several ways of approaching this research reproducibility & participation problem: 
one is complicated, multilayered, requiring a lot of large team expertise and big machines; 
the other is simple, engage small groups/communties, could lead to individual mastery 
(but don\'t start there) and use your common personal computer.
Telling data stories today and *releasing them to the public*, means to traverse the bridge
that joins these two ways, so our research become more open, participative and reproducible.
Let\'s call it the *Big Bridge*.

ICIJ has made a lot of work and we could take a constructive approach to understand, 
complement, enhance and criticize it.
The question I will address is: what could be done to make the Panama Papers research bridge 
the previous reproducibility and participation gap, specially regarding \"data artifacts\" 
(tables, queries, visualization, code)?
That is the focus of the next section, taking into account the experience of working with what 
has been released until now to produce the map and then finishing some future scenarios.',
										#children : OrderedCollection [ ],
										#parent : @52,
										#level : 4
									},
									GrafoscopioNode {
										#header : 'An environment for reproducible participary research',
										#key : '',
										#body : 'Data provenance is a formal way to answer *where this data representation comes from*?
Taken in a broader sense, the question can refer to a table, a query answer, a data visualization.
and the operationsa between and behind all of them.
But also it could be extended to include the social actors behind of and affected by the data: 
funding, spending, instruments methodologies and so on, would be part of the answer.

One example on the social issues comes from several campaigns on Twitter, organized mainly
for  Panamanians after the leaks, to show that 
[Panama is more than Papers]()
and that this should be called 
[Mossack Fonseca Papers](),
because it creates an stigma over all the country and leaves out of radar
others tax heaven countries with similar practices and a problem that goes beyond Panama.
There have been also questions about who funded this long complex investigative effort
and who benefits from the scandal, or how it can improve democracy and accountability.

These are important issues that should be addressed, including to release as much data 
metadata as possible about the research and the entities behind, while protecting the privacy 
and integrity of the people involved.
Also ICIJ has adopted a gradual liberation strategy that keep the balance between what is
released and what is protected[^privacy-fredom-balance] and have showed aspects of their 
methodology
(I have no data about funding sources  and amounts, at least in a place provided by
ICIJ, but could be just that I miss it).

The Big Bridge, refered before, that will help the readers and citizens in making 
sense of complex data stories and participate actively of them requires to bridge 
several gaps, one of them is the one beween almost raw data on one extreme and 
(complex) visualizations on the web and print on the other.
I will use the [released data] and [the choropleth map] as a way to illustrate
one example of suchs bridges, that could help in shielding  the research while 
opening its data and findings for interested parties and citizens.
For that, I will focus next on two complementary approaches and tools:
The first is what we could call *frictionless  data and metadata*, to extend the 
Open Knowledge Foundation term;
and the second is what we could call *data continoum environments*, that bind data, 
with its representations, transformations and processes in a simple, affordable, 
transparent, explorable and continuos (eco)system.',
										#children : OrderedCollection [
											GrafoscopioNode {
												#header : '%footnote privacy-freedom-balance',
												#key : '',
												#body : 'International Consortium of Investigative Journalist (ICIJ) has
chosen a multi-release strategy to curate the data and to keep the balance between
freedom of important information and protection of sensible personal information (like email
and phisical addresses).',
												#children : OrderedCollection [ ],
												#parent : @56,
												#level : 5
											},
											GrafoscopioNode {
												#header : 'Frictionless (meta)data',
												#key : '',
												#body : '(https://offshoreleaks.icij.org/about/download)

Part of what makes the choropleth map visualization possible is the data release strategy  
followed until now by ICIJ: small chunks of important data in standard simple formats.
In this case, a zip file of comma separated values stored in plain text (CSV) of just 14 Mb with 
four files (called  \u0300countriesNW.csv \u0300,  \u0300edges_1DNW.csv \u0300,  \u0300node_countriesNW.csv \u0300 and  \u0300nodesNW.csv \u0300).

You can quickly download it; import it into the simple, ubiquous and powerful sqlite database;
republish it to a community data repository (like [this one in datahub.io]()) 
to make your new and more convenient  data format traceable and available,
and start to explore and query the data to make sense of it.

[1a DataHub screenshot]

Once you have some interesting query and result, you can share it on twitter or with a little more time 
start to bind the data to other environments as show in the picture (1b) (but we will come
to that in the next section).

[1b Pharo Query Smalltalk]

So there is a lot of what you can do even with this small data release. 
And this idea of small significant and nicely operable data chunks resonates with the 
idea of frictionless data of the OKFN, but we need more to make the exploration of the 
data easier:

- *Add metadata about the structure of the data*: Instead of putting your user to reverse engineer
  what tables and columns represent, state this explicitly, maybe using
  [data packages](http://data.okfn.org/doc/data-package) or
  [tabular data packages](http://data.okfn.org/doc/tabular-data-package).
- *Use signatures to verify the integrity of data*: As the source of data, put SHA or MD5
  alike codes that let the user know that download complete and data integrity at their end is the
  same that at the source.
- *Versioning and API:* A way to know the history of the data and a way to interact with it,
  even if you have not downloaded the complete database (like in my case) as this may become 
  more difficutl as the data increases.
  What I did to provide this features was to [republish the data using datahub.io] 
  that provides both, versioning and API (even if I\'m using it now only as a storing/sharing
  utility).

The technology stack that ICIJ is using is pretty solid and pretty complicated, as 
[you can see](https://panamapapers.icij.org/blog/20160425-data-tech-team-ICIJ.html).
Could an alternative technology stack empower citizens, individuals and small entities to
work with the data? 
The example of the choropleth map shows this is possible.
Next section will deal with the details.',
												#children : OrderedCollection [ ],
												#parent : @56,
												#level : 5
											},
											GrafoscopioNode {
												#header : 'Data continuoum environment: data <-> queries <-> code <-> visuals',
												#key : '',
												#body : 'Bulding a affordable continous environment for reproducible research (and data activism), 
that blends data, code, dev environment and tools and interactive documentation in a fluid, explorable,
modifiable and traceable way is part of the goal that I showcase in a separate project
below, which is still in alpha status (click in the image or its description to know the details):
I\'ll talk here about what makes this possible now and what needed.

[Panama Papers Page]',
												#children : OrderedCollection [ ],
												#parent : @56,
												#level : 5
											}
										],
										#parent : @52,
										#level : 4
									},
									GrafoscopioNode {
										#header : 'What\'s next: data activism tools, practices & citizen partnerships to keep the powerful accountable.',
										#key : '',
										#body : 'On an small scale this is what I will focus next:

- Heavy refactoring of the grafoscopio\'s notebook: Notebooks are the way 
  of making data storytelling and presenting data visualizations, queries and
  other software artifacts to the readers/explorers.
  They let me structure the drafts of the story in dialog with the software
  visualization and the live coding environment, so I can write/think in 
  prose, code and visuals, switching from one to another.
  This whole blog post was in fact wrote as part of a interactive notebook
  and next exported to the web.
  Other parts of the notebook let the explorers to follow the steps of the
  \"Quick start\" and being inicited in the live coding environment and what
  is behind the visualizations.
  But the experience is not friendly enough and there is a lot of rought edges
  everywhere, as you can see in the screenshot below or experience by yourself
  if you\'re playing with the prepackaged image for the environment.
  Because grafoscopio and its notebooks are an important part of my PhD research,
  I will focus on making the experience of writing/reading them smoother and friendlier.

On a bigger scale, Panama Papers could become and important exemplar of new
citizen and jornalist partnerships  where data activism and data journalims inform each 
other, to keep the powerful accountable,
What we have seen until now is a partnership of goverment with private interest
to make the rich richer and even helping the powerful to evitate social redistribution
of wealth that is at the core of taxing.
Tax heavens have important implications that reach lives of common people everywhere
and probably next to you.
This means that we, as a civil society, need to reimagine new ways of participation in dialogue
with the goverment and hopefully with their support for a more just and equitative society.
Technology could play an important role in this escenario, but only if it enables us to participate
in a plural understanding and building of this shared complex world we inhabit, that is
mediated by data.

%% Open Data needs jornalism?',
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						],
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					GrafoscopioNode {
						#header : 'Others',
						#key : '',
						#body : 'Notes for alternative stuff I was working on while making the Panama Papers reproducible data visualization.',
						#children : OrderedCollection [
							GrafoscopioNode {
								#header : 'Installing Spec Glamour Binding',
								#key : '',
								#body : 'Gofer it
    smalltalkhubUser: \'jfabry\' project: \'Playground\';
\t package: \'Spec-Glamour\';
    load',
								#tags : 'c\u00F3digo',
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								#parent : @66,
								#level : 3
							},
							GrafoscopioNode {
								#header : 'PublishedMedInfo',
								#key : '',
								#body : '',
								#children : OrderedCollection [
									GrafoscopioNode {
										#header : 'Viaualizaci\u00F3n de pruebas sobre moose 6.x',
										#key : '',
										#body : '| dataFile medInfo  | 
dataFile := FileLocator documents asFileReference / \'Grafoscopio\' / \'Projects\' / \'InfoMed\' / \'DataAndVisuals\' / \'rituximab-data-sunburst.csv\'.
medInfo := PublishedMedInfo new loadDataFromCSV: dataFile usingDelimiter: $;.
medInfo arcWidth: 16.
medInfo matrixSunburstForAdminDataByCountry',
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