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M. J. C. van den Homberg et al.
mation from the D form is available within three weeks, but the lower government
levels often do not have clear guidelines and resources for adequate data collection.
NGOs that are part of the Local Consultative Group often do their own assessments,
such as in 2014 via a Joint Needs Assessment, creating in fact a new process with
different indicators that is only aligned with the government process to a very limited
extent. Once the information is collected at central level, support is mobilized for the
response, making the response largely a top-down mechanism. Both the NGO and
government information architecture are not specifically geared toward coordination
and action planning at Community, Union, and Upazilla level, forming a stumbling
block for effective local response. To tackle the issues mentioned above, data preparedness activities should become an integral part of the preparedness phase.
First, we propose to organize regular multi-institutional mapping cycles of data
sets on information requirements. These cycles should not only consist of keeping
an up-to-date inventory of available data sources and providers, but also of regular
consultations with responders as to what their information needs are. When the
interviewees validated the information needs framework, this sparked their creativity.
We got reactions like: “wow, if this is possible, we could also really benefit from X
information”. It is important hence to keep on evolving the requirements and to use
these requirements to shape the information products that providers are creating so
that they meet the decision-maker’s needs. These mapping cycles will also benefit
from advances countries make in terms of open data. Open data can promote inclusion
and empowerment, as it has the potential to remove power imbalances that result from
asymmetric information, and can give marginalized groups a greater say in policy
debates (Davies and Perini 2016).
Second, coordination needs to be improved. A Coordinated Data Scramble (Campbell 2016) can be a very effective way to reach a higher level of coordination in
the data collection process, avoiding duplicates, increasing quality, and promoting
coherence. It basically means having a multitude of organizations use collaborative
platforms and closed digital communication groups for “bounded crowdsourcing”
(Meier 2015). Also, specific platforms for managing and sharing the different data
sets can be used. Geodash, making use of Geonode, is such a collaborative geospatial
platform that was the started up by the World Bank and is now taking over by the
Government of Bangladesh (Geodash 2017). UN OCHA deploys the Humanitarian
Data Exchange (HDX), more specifically targeting humanitarian data (Keßler and
Hendrix 2015).
Third, to facilitate the sharing and exchange of data, standards are being developed and used—to varying degrees—ranging from P-codes for unique geographic
identification codes up to the Humanitarian Exchange Language (HXL). Lastly, it
will be key to develop capacities of the different stakeholders in parallel to the above
activities enhancing their data literacy and access to digital technologies. Especially
at the local level, many respondents were, for example, not aware of all the existing
data sets nor were they trained in data collection and analysis.
M. J. C. van den Homberg et al.
mation from the D form is available within three weeks, but the lower government
levels often do not have clear guidelines and resources for adequate data collection.
NGOs that are part of the Local Consultative Group often do their own assessments,
such as in 2014 via a Joint Needs Assessment, creating in fact a new process with
different indicators that is only aligned with the government process to a very limited
extent. Once the information is collected at central level, support is mobilized for the
response, making the response largely a top-down mechanism. Both the NGO and
government information architecture are not specifically geared toward coordination
and action planning at Community, Union, and Upazilla level, forming a stumbling
block for effective local response. To tackle the issues mentioned above, data preparedness activities should become an integral part of the preparedness phase.
First, we propose to organize regular multi-institutional mapping cycles of data
sets on information requirements. These cycles should not only consist of keeping
an up-to-date inventory of available data sources and providers, but also of regular
consultations with responders as to what their information needs are. When the
interviewees validated the information needs framework, this sparked their creativity.
We got reactions like: “wow, if this is possible, we could also really benefit from X
information”. It is important hence to keep on evolving the requirements and to use
these requirements to shape the information products that providers are creating so
that they meet the decision-maker’s needs. These mapping cycles will also benefit
from advances countries make in terms of open data. Open data can promote inclusion
and empowerment, as it has the potential to remove power imbalances that result from
asymmetric information, and can give marginalized groups a greater say in policy
debates (Davies and Perini 2016).
Second, coordination needs to be improved. A Coordinated Data Scramble (Campbell 2016) can be a very effective way to reach a higher level of coordination in
the data collection process, avoiding duplicates, increasing quality, and promoting
coherence. It basically means having a multitude of organizations use collaborative
platforms and closed digital communication groups for “bounded crowdsourcing”
(Meier 2015). Also, specific platforms for managing and sharing the different data
sets can be used. Geodash, making use of Geonode, is such a collaborative geospatial
platform that was the started up by the World Bank and is now taking over by the
Government of Bangladesh (Geodash 2017). UN OCHA deploys the Humanitarian
Data Exchange (HDX), more specifically targeting humanitarian data (Keßler and
Hendrix 2015).
Third, to facilitate the sharing and exchange of data, standards are being developed and used—to varying degrees—ranging from P-codes for unique geographic
identification codes up to the Humanitarian Exchange Language (HXL). Lastly, it
will be key to develop capacities of the different stakeholders in parallel to the above
activities enhancing their data literacy and access to digital technologies. Especially
at the local level, many respondents were, for example, not aware of all the existing
data sets nor were they trained in data collection and analysis.