COVID-19 Data Meet-Up - Barcelona - Directorate General for Transparency and Open Data + International Open Data Charter - Govern obert
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COVID-19 Data Meet-Up
Barcelona
Directorate General for Transparency and Open Data
+ International Open Data Charter
Date: 22 September 2020
1Contents
Introduction
Fourth session of the COVID-19 Data Meet-Up
- Technical information
- Agenda
- Conclusions of the working groups
o Economic impact
Proposals for opening up data
Links
o Social impact and vulnerable groups
Proposals for opening up data
Links
o Gender impact
Proposals for opening up data
Links
Final notes
Summary for the Open Data Charter (English)
2COVID-19 Data Meet-Up
Barcelona
INTRODUCTION
The COVID-19 pandemic has highlighted the urgent need to improve our
preparedness if we are to tackle a human crisis on a global scale. It has also
highlighted the need to plan how public health data should be collected, and
how this data should be processed and communicated to the public. As we
have seen during the initial months of this planet-wide emergency, every country
- without exception - has faced numerous obstacles with regard to the collection
of real data with which to develop a response and implement measures to tackle
the crisis. The general conclusion has been that it is necessary to publish more
data, in response to the demands of different professional and citizens’ groups
and in relation to different contexts.
The Government of Catalonia’s Directorate General for Transparency and Open
Data (DTDO) wants to open up data to more professional sectors in order to help
overcome the health-related, employment-related and economic crises that
have been caused by COVID-19. For its part, the Open Data Charter (ODC) is an
international organisation that promotes the opening up and usage of data in a
way that is transparent and inclusive. The ODC is aware of the importance of
monitoring the ways in which governments are responding to the pandemic and
the steps they are taking to recover from it. In order to achieve this recovery, we
need reliable, disaggregated, complete data that will enable us to determine
what resources the government has and how to tackle the public health crisis.
With this aim in mind, in September 2020 the Government of Catalonia and the
ODC organised the COVID-19 Data Meet-Up.
International cooperation 1
As part of the joint response to COVID-19, international meetings have taken
place in a number of different countries. Producers and users of data have come
together in order to identify the data that is already open and to articulate the
need to open up the data that is not.
These meetings also aim to define which datasets need to be published in order
to provide a holistic view of the impacts of COVID-19; which datasets need to be
published or improved in order to best tackle the economic, social and public
health crisis; the criteria for standardising the collection, publication and analysis
of COVID-19 data; the drawing up of user guides and recommendations for
comparing and cross-referencing data at the international level; identifying
successful examples of the use of open data in relation to COVID-19; and
1Data Readiness, Response, Recovery and Reform. Open Data Charter
https://medium.com/opendatacharter/data-readiness-response-recovery-and-reform-
c8ce819230c
3proposing a taxonomy of the metadata that is required in order to construct a
useful, operational dataset designed to serve citizens’ needs.
These meetings between professionals have previously been organised in
conjunction with the governments of Canada, Mexico and New Zealand.
FOURTH SESSION OF THE COVID-19 DATA MEET-UP
The fourth session of the COVID-19 Data Meet-Up was jointly organised by the
Government of Catalonia’s DTDO and the ODC. The Meet-Up focused on three
key areas:
- Economic impact
- Social impact and vulnerable groups
- Gender impact
The purpose of this coming-together of professionals was to:
- Discuss the main shortcomings in the collection and processing of data.
- Build resources based on recommendations adapted to suit different
contexts.
- Discuss how to obtain reliable, comparable, high-quality data.
Technical information:
Date of the event: 22 September 2020
Organisers: The Government of Catalonia’s Directorate General for
Transparency and Open Data and the International Open Data Charter
(https://opendatacharter.net/)
Number of participants: 35
Areas of focus: Economic, social and gender impact
Duration: 1h 30m (4:00 - 5:30 p.m.)
Computer tool: Zoom
Agenda:
4:00 - 4:10 p.m.
- Welcome address and introduction to the session by Núria Espuny,
Director General for Transparency and Open Data.
- Presentation on the COVID-19 Meet-Up initiative by Agustina de Luca,
Director of the International Open Data Charter.
4:10 - 4:15 p.m. Logistical and technical arrangements for the participants, led
by Karma Peiró, the host of the event.
4:15 - 4:20 p.m. Introductions for the facilitators of the various working groups:
Clara Torras, Jordi Barquinero and Mar Fernández.
4:20 - 5:15 p.m. Group discussions in three separate rooms (Social, Gender and
Economy).
5:15 - 5:30 p.m. Presentation of the conclusions of each group.
5:30 p.m. Closing address and messages of thanks to the participants.
4CONCLUSIONS OF THE WORKING GROUPS
GROUP: ECONOMIC impact
Facilitator: Mar Fernàndez, Economist and Project Manager, Knowledge
Innovation Market (KIM).
It was an extremely productive discussion, with 14 experts from a number of
different fields (health, architecture, communication, business, etc.). This
enabled us to explore the subject of the economy from a holistic perspective.
To date, the data used has painted a picture of conditions at the societal level
(GDP, employment, etc.). However, the participants agreed that different inputs
are now needed. In order to respond to this crisis, we need ‘high-frequency data’,
because macro-level information will not help us improve business models.
We want data related to utilities (e.g. telephony use due to working from home,
energy consumption, etc.), official government loans from the National Credit
Institute (ICO), temporary employment-reduction/furlough plans (ERTEs),
property rental, companies that have ceased trading, and so on. In other words,
data that can help us to understand how each sector is coping and, in
consequence, address any shortcomings.
The greatest challenge when searching for data is immediacy and
georeferencing. However, it is important to remember that simply having of a
large amount of data does not necessarily equate to better information. The
data needs to be organised and converted into useful information.
There were no disagreements over privacy, as it is understood that there are
mechanisms to anonymise the data. However, the point was made that if the
data is collected by a private company, we cannot be sure of what will be done
with it. This led to a discussion on who should be responsible for collecting more
sensitive data. Some participants felt it should be public bodies: specifically,
statistical institutes, as they have the capacity to do so. However, the Statistical
Institute of Catalonia (Idescat) cannot offer the required immediacy.
In terms of ultimate benefit, the group was clear: all citizens would benefit,
whether due to improved quality of life, or - in more specifically economic terms
- through the creation of businesses that will generate employment and meet
their needs.
DATA required:
- Sector-specific surveys of the business climate.
- The liquidity of local companies, in order to gain a more frequent and
detailed view of their situation.
- Data on utilities (e.g. telephony use due to working from home, energy
consumption, etc.).
- ICO loans: amounts, payment terms.
5- Working from home: telephony operations that have ceased due to
working from home.
- Geolocation.
- ERTE data: by sector and in greater detail (i.e. by category).
- Commercial activity: how many businesses and commercial premises
have closed, how much rent has gone unpaid.
- Permits granted (men/women).
- Types of employment by healthcare district: district-based differences.
- Temporary incapacity benefit (ITE) in the healthcare sector: how many
have claimed it, whether numbers are rising or falling, number and location
of employees quarantining.
- Data on property rented, purchased (m2).
- What new business models are emerging? Ideas for the future.
- Economic impact on the business ecosystem: positive, in light of the
creation of new companies, but also negative, because it may affect
sectors we are not aware of.
- Region-wide perspective in order to empower municipalities
(disaggregated data).
- Data on energy consumption, tourism, changes in purchase methods
(variations in online purchases, buying local, etc.).
- Google Analytics: may provide data on searches for companies or social
networks.
LINKS provided:
- Government Agreement 154 of 20 December 2018 approving the
Government of Catalonia’s open data strategy and its membership of the
International Open Data Charter
http://governobert.gencat.cat/ca/detalls/article/Acords-de-govern-
00002#bloc1
- The Barcelona Chamber of Commerce Business Barometer examines how
COVID-19 is affecting the economy
http://premsa.cambrabcn.org/content/el-barometre-cambra-analitza-
com-esta-afectant-la-covid-19-a-leconomia/
- Economic and social indicators
http://economia.gencat.cat/ca/ambits-actuacio/economia-catalana/conjuntura-
economica/indicadors-economics-i-socials/index.html
- The Government of Catalonia’s open data portal
http://governobert.gencat.cat/ca/dades_obertes/
- COVID-19- An online space containing information, measures and
resources, in a number of different subject areas, that the Government of
Catalonia has made available in relation to the COVID-19 pandemic
http://governobert.gencat.cat/ca/transparencia/transparencia-i-covid-
19/
6GROUP: SOCIAL impact and vulnerable groups
Facilitator: Jordi Barquinero, Head of Studies and Statistics, Government of
Catalonia.
With regard to vulnerable groups, there are two things that should be pointed
out. First, there are groups that do not generate data, whether due to the
exceptionally precarious nature of their circumstances, or for other reasons (e.g.
homelessness, severe poverty, etc.). Second, there is a need for data on
resources and (in particular) on professionals in the sector.
In terms of improving datasets, the issue of cross-referenced disaggregation was
raised, especially in relation to gender. In other words, the provision of data not
only by gender, but also by gender and age and other variables. Mention was
also made of the need for greater territorial disaggregation, especially at the
sub-municipal level, in order to learn about specific realities.
Regarding the question of who should be responsible for collecting the data, the
idea of citizens as a source of data was mooted. In other words, instead of relying
exclusively on the public sector as a data provider, we could move towards
initiatives that enable citizens to share data, thereby generating large datasets
(particularly in relation to social networks, Big Data, etc.).
Lastly, in terms of challenges, particular emphasis should be placed on those
related to the logic of data collection systems. In many cases, these systems have
their origins in applications or records that are geared towards management,
rather than analysis. In turn, this makes it harder to generate datasets.
Participants also mentioned the need to improve data mapping: “often, the
data is there, but it is difficult to find”.
DATA required:
- Diverse groups.
- The importance of resources and (in particular) professionals; identify
needs.
- Identify who is the beneficiary of the resources; citizens as a source of data.
- The problem of groups living under exceptionally precarious
circumstances, who do not generate data. We only analyse what we are
able to analyse. Examples: the homeless; LGBTI (no data for these groups);
the disabled; the elderly; children (family relationships); level of education,
etc.
- Often, the data is there, but we do not know that it is there. Knowing how
to map the data presents a challenge.
- The problem of how to extract information from documents and
parametrise it. Technological challenges.
- Systems designed for management, rather than analysis, which makes the
data difficult to open up.
- Lack of disaggregation: data is needed for the sub-municipal level,
otherwise we cannot learn about specific realities.
7CHALLENGES: technological issues (computer systems that have not been
adapted to automate the process); collecting data from social services
portfolios.
LINKS provided:
- Saluscoop.org: a citizen data cooperative for research into health.
- Accessible open data portal and a study on the incidence of
occupational segregation in relation to the prevalence of SARS-CoV-2 and
COVID-19 by healthcare district: an analysis from a gender intersectional
perspective. Lidia Arroyo (IP), Open University of Catalonia (UOC) and the
Gender and ICT Research Group, Internet Interdisciplinary Institute (IN3).
https://www.uoc.edu/portal/ca/news/actualitat/2020/300-covid-
genere.html
- Social services portfolio
https://treballiaferssocials.gencat.cat/web/.content/01departament/08p
ublicacions/ambits_tematics/serveis_socials/25segonacartera/carterass.p
df
- Study reveals that 20% of LGBT individuals have lost their jobs
https://www.lavanguardia.com/vida/20200505/48989152797/un-estudio-
desvela-que-un-20-de-personas-lgtb-han-perdido-su-empleo.html
8GROUP: GENDER impact
Facilitator: Clara Torras, Coordinator of the Gender Equality Observatory,
Catalan Women’s Institute.
In Catalonia there is an extremely significant lack of data from a gender
perspective in any format, along with a lack of open data from a gender
perspective both in general and with specific regard to COVID-19.
There is still insufficient awareness of the potential of open data and little
knowledge of what open data can do. Nor is there sufficient awareness of the
need to incorporate a gender perspective into all social research data.
The participants agreed that data is needed in the following six areas related to
COVID-19 and gender:
- Income
- Health
- Balancing paid and unpaid work
- Male violence against women
- Work
- Areas that are particularly hard-hit
The data should be analysed not only in relation to gender, but also in relation to
other discriminatory factors that intersect with gender, such as nationality, health
status, age, risk of social exclusion, sexual orientation, etc.
The participants all agreed that the gender perspective of employment data
could also be improved. In terms of data on health, questions were raised with
regard to comparability over time, as the process of measuring this data has
undergone a series of changes.
The group also discussed the need for metadata to accompany the open data
and help to explain it, or some form of service to address queries. Additionally,
the participants agreed that responsibility for the data’s quality and for opening
it up should lie with the producers of said data, rather than with an outside agent.
Now that the lockdown is over, and in light of the general lack of data to reflect
what has happened during this period, the participants suggested that we
evaluate the impact of COVID-19 from a gender perspective by examining how
government assistance was distributed, whether the women who were placed
on furlough (ERTE) subsequently became unemployed or returned to work, and
comparing women’s financial circumstances before and after the pandemic.
9CHALLENGES
- Although data on health has been utilized, the way in which this data is
measured has changed periodically, making it difficult to compare data
over time.
- In many cases, employment data did not even have a minimal gender
perspective, e.g. cross-referencing by gender.
- COVID-19 data is not available by territory.
- There is a lack of data on the reduction in social services geared towards
protecting women.
- The participants also pointed out the need to demonstrate the effect of
COVID-19 on the loss of female talent, with specific regard to female
scientists and scientific researchers.
- Who has had access to the ICAS loans? We need transparency for the
data provided by the Bank of Spain.
- There is no data on the effect on COVID-19 on the mental health of women
and girls. COVID-19 itself is discussed, but its other impacts on health are
not.
- More responsibility is assigned to the custodians of the data than to any
organisations that might manage all of the data from a cross-cutting
perspective. In any case, there should be a body to make sure the data is
unified, and/or that there is coherence between datasets.
- The participants proposed that in addition to sharing open data, there is a
need for a consultation service to help people use the open data, or a user
guide or metadata.
- Who would benefit most from the use of this data? Professionals in the field
of communication, academics, and those studying the position of women
in society within the context of the COVID-19 pandemic. And, of course,
women themselves.
LINKS provided:
- Tracking the Gender Impact of COVID-19: An Indicator Framework
https://drive.google.com/drive/folders/19Xw9CECuF2Qq3PnVsmvM_GRP
PQ71P7ge
- The Impact of COVID-19 on Women
https://drive.google.com/file/d/1RzuuNzMUsYuS1MWYwGBm0hILF5_IYGE9
/view
- ILO Monitor: COVID-19 and the world of work. Fifth edition
https://drive.google.com/file/d/1uWaxHxFwE5JVB8zGip7Xgs8RBNm8G3G
N/view
- Report on UN indicators:
https://docs.google.com/spreadsheets/d/1YPxXNowXgERt5lbaG6FpybFdl
YOaeY8zGP7hA8nyZWE/edit?usp=sharing
- COVID-19: Emerging gender data and why it matters
https://data.unwomen.org/resources/covid-19-emerging-gender-data-and-why-it-
matters
- Tackling coronavirus (COVID-19): Contributing to a global effort
https://www.oecd.org/coronavirus/country-policy-tracker/
- The COVID-19 Sex-Disaggregated Data Tracker
10https://globalhealth5050.org/the-sex-gender-and-covid-19-project/the-
data-tracker/?explore=country&country=spain#search
- What Do We Know About the Impact of Gender on the COVID-19
Pandemic?
- https://www.isglobal.org/ca/-/-que-sabemos-del-impacto-de-genero-en-
la-pandemia-de-la-covid-19-
- Gender and COVID-19 project
https://www.genderandcovid-19.org/resources-page/
- Study shows the impact of quarantine on Colombians’ mental health
https://www.elpais.com.co/salud/estudio-muestra-impactos-de-la-cuarentena-en-
la-mental-de-los-colombianos.html
11Final NOTES:
Participants and facilitators alike found the COVID-19 Data Meet-Up to be
of great interest, given the importance of improving the data collection
process in order to enable the analysis of said data and to aid the
identification of problems and solutions.
Likewise, the groups highlighted the value of bringing together
professionals from different disciplines and knowledge areas to discuss the
urgent need to improve the open data ecosystem.
However, the time assigned to this discussion was far too short (just one and
a half hours) for a deep-dive into each of the areas in question. If the
organisers wanted an overview of the needs and demands of different
sectors, this objective was achieved comfortably (as demonstrated by the
summaries provided by each working group). The organisers should
consider holding a follow-up session, with a duration of between four and
six hours, in order to continue following the thread of the contributions that
have been summarised in this report.
12RESUMEN para la CARTA INTERNACIONAL DE DATOS ABIERTOS
Impacto económico
El debate "ha sido un debate muy productivo”, donde hemos podido concluir
que “como resultado de esta crisis se necesitan ‘datos de alta frecuencia’, ya
que los macrodatos no sirven para mejorar los modelos de negocio”.
Son necesarios datos sobre el mundo de los suministros (telefonía para el
teletrabajo o consumo energético). Pero también los datos referentes a los ERTE,
del Instituto de Crédito Oficial (ICO), alquileres y empresas que han
desaparecido durante la pandemia. Si bien se destaca que para el conjunto de
todos ellos el mayor es la inmediatez y la georreferenciación.
Al mismo tiempo, se señala que tener muchos datos no significa tener mejor
información. Necesitamos más análisis y más pedagogía (alguien que
transforme estos datos en información útil).
El punto clave es quien recogerá los datos, ya que si es una empresa privada
surge la pregunta de ¿quién debería ser el responsable de los datos más
sensibles? Hay quienes argumentan que el responsable final son los organismos
públicos, especialmente los institutos de estadística, pero estos no siempre
responden con inmediatez.
En suma, los principales beneficiarios de los datos públicos son los ciudadanos.
Ya que su calidad de vida puede mejorar o, en el caso de la economía, pueden
crear empresas que ocupen espacios y así solucionar ciertas necesidades."
Impacto social
"Los grupos vulnerables no generan datos, ya sea por su situación
particularmente precaria o por otros motivos (sin hogar, pobreza extrema, etc.).
Existe una necesidad de tener más datos y recursos en este campo.
Con respecto a la mejora en los conjuntos de datos (datasets), ha surgido el
problema de la desagregación cruzada, especialmente sobre género.
Necesitamos datos sobre género y edad, además de otras variables. Asimismo,
ha surgido la necesidad de una mayor desagregación territorial, especialmente
a nivel municipal, para conocer algunas realidades.
En relación a quién debería ser el responsable de recoger los datos, queremos
considerar la ciudadanía como una fuente de datos, para así no quedarnos
solamente en el sector público como proveedor de datos. De ese modo se
podrá avanzar hacia iniciativas que permitan a los ciudadanos compartir datos
y generar grandes conjuntos de datos (especialmente en las redes sociales).
Finalmente, se debe destacar la lógica de los sistemas de recolección de datos.
A menudo, provienen de aplicaciones o de registros centrados en la gestión, no
en el análisis. Este hecho dificulta la generación de los conjuntos de datos.
13También, mencionar la necesidad de mejorar el "mapa de datos": "muchas
veces los datos están allí, pero es difícil encontrarlos".
Impacto en el género
En Cataluña, hay una escasez muy significativa de datos con perspectiva de
género en cualquier formato, de datos abiertos con perspectiva de género, en
general, y concretamente, en referencia a la COVID-19.
Todavía no existe suficiente conciencia sobre el gran potencial de los datos
abiertos y, además, hay una falta de conocimiento de lo que se puede hacer
con ellos. Al mismo tiempo no existe suficiente conciencia sobre la necesidad
de incorporar la perspectiva de género dentro de los datos de investigación
social.
Se han identificado seis dimensiones de datos de la COVID-19 y de género que
son necesarias, y en las que se pusieron de acuerdo todos los participantes.
- Renta.
- Salud.
- Conciliación de trabajo remunerado y no remunerado.
- Violencia de género.
- Trabajo.
- Territorios gravemente castigados.
Los datos se tendrían que analizar no solamente por género, sino también por
otras características de discriminación en intersección con el género, como la
nacionalidad, el estado de salud, el riesgo de exclusión social, la orientación
sexual, etc.
También existe el consenso de que la perspectiva de género de los datos del
lugar de trabajo se puede mejorar. Se ha cuestionado la comparabilidad en el
tiempo de los datos de salud, ya que la manera en la que se mide ha cambiado.
La necesidad de hacer que los metadatos acompañen a los datos abiertos y
los expliquen o de crear un servicio para resolver dudas está sobre la mesa. Los
productores de datos públicos deberían tener la responsabilidad de compartir
datos con calidad, en lugar de dejar esta tarea para alguien externo.
Hay una falta de datos que reflejen lo sucedido en este confinamiento. Se ha
propuesto evaluar el impacto de la COVID-19 en el género y cómo se distribuirá
la ayuda en los próximos meses; además de los ERTE en mujeres, si se quedarán
sin trabajo o si volverán a trabajar con la misma situación económica que había
antes de la pandemia.
14NOTAS finales
Los participantes y facilitadores consideran que el MeetUp Data COVID-19 ha
sido un evento muy interesante debido a la importancia que tiene seguir
mejorando en la recolección de datos y su análisis. Los objetivos de estas
reuniones deben permitir una mejor identificación de problemas y soluciones,
especialmente durante una crisis económica y social.
Asimismo, se ha destacado el valor de reunir a profesionales de distintas
disciplinas y conocimientos para reflejar la urgente necesidad de mejorar el
ecosistema de datos.
Sin embargo, el tiempo asignado ha sido breve (1 hora y media) y no se pudo
profundizar en cada una de las áreas. El objetivo del MeetUp Data COVID se
cumplió sobradamente si lo que la organización buscaba era conocer lo que
se reclama desde los distintos sectores (como puede verse en los resúmenes
proporcionados por cada grupo de trabajo). Pero sería una buena opción
plantear una segunda parte, con una duración de entre 4 y 6 horas, donde se
pudiera profundizar más en las aportaciones que se han recogido aquí.
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