[CODATA-international] Call for expression of interest for contribution to the Linked Open Data for Global Disaster Risk Research

[Asha CODATA]

The CODATA Task Group on Linked Open Data for Global Disaster Risk Research
<https://codata.org/initiatives/task-groups/linked-open-data-for-global-disaster-risk-research/lodgd-membership/>
(LODGD)
will be working with the Integrated Research on Disaster Risk (IRDR)
<http://www.irdrinternational.org/what-we-do/overview/>, the Institute of
Remote Sensing and Digital Earth  <http://english.radi.cas.cn/>(RADI) of
the Chinese Academy of Sciences (CAS), Tonkin+Taylor International
<https://www.tonkintaylor.co.nz/>, and LODGD partners, to produce a series
of policy briefs on disaster risk reduction in 2020.  The first policy
brief is expected to be released in August 2020. The global pandemic is a
powerful reminder of the necessity of the international community’s
intensified and sustained commitment to emergency preparedness.

We are thus inviting experts in disaster risk reduction data and policy
issues to collaborate on preparing these documents.  Please follow the link
below for the EOI.

https://www.surveymonkey.com/r/RYXPPLQ

Important dates:

Expression of interest:       15 April 2020
Draft contributions:             30  May 2020
Review by ISC/CODATA:   15  June 2020
Final policy brief:                30 June 2020
Publishing:                         15 August 2020

   - *Policy and challenges in **disaster risk reduction** and data:* Informed
   decision making and coordinated action for effective disaster risk
   reduction require timely and reliable data and information. Due to
technological
   advances, previously unknown relationships or patterns in all aspects of
    nature and society can now be quickly established. However, despite
   these discoveries and even with the guidance from the Sendai Framework,
   the Paris Agreement and the Sustainable Development Goals (SDGs),
many countries
   are still facing numerous challenges using different data for decision
   making, which ultimately increases fatalities and causes enormous
   financial losses due to disasters. The COVID-19 pandemic is a good
   example how some countries learned from others and how data could assist
   in slowing down the disease spread. It is necessary to identify what
   challenges are faced by the government,  nongovernmental organisations
   and policy users in using data for disaster risk reduction and how the
   FAIR principle could be applied at all government levels.
   - *Interoperability and interdependency o**f data for disaster risk
   reduction**:* There are a number of factors that act as barriers to data
   interoperability and interdependency. These factors are caused by local and
   international limitations, which affect or compromise the effectiveness
   of disaster risk reduction. It is proposed to develop a guideline that
   breaks down these barriers and focuses on how to make domain-specific
   data/metadata be transformed in a way that cross-domain approaches
   regarding discovery and analysis can be supported for disaster risk
   reduction.
   - *Policy brief on data to accelerate the transition from disaster
   response to recovery:* A number of challenges are usually faced
   post-disaster, including ineffective coordination between parties at both
   local and international levels, limited resources and financial
   constraints. These challenges have numerous complex factors, which  lead to
   long response times and even longer recovery times, causing a great deal of
   tension, conflict in addition to other cascading problems in the
   communities affected by the disaster. It is proposed to set up a baseline
   data with integrated data repository for disaster response to accelerate
   transition between the response and recovery phase. This would enable the
   world to better understand the health, social, economic, environmental, and
   other problems that arise when we fail to invest adequately in
combating natural
   hazards. Using different domain-data could enhance better management to
   deal with the emergency response process and a swift transition from the
   response to the recovery phase.


   - *Policy brief on agriculture loss modelling using big data:*It is
   likely that climate change will lead to an increased frequency and
   intensity of weather-related natural disasters such as floods, storms and
   droughts. These events require the need to evacuate livestock to housing or
   flood-free areas as well as to address damage of pastures, drainage systems
   and field infrastructure, reduction in crop yields, loss of soil
   biodiversity and an increased risk of animal disease. It is proposed that
   big data is used in a climate forecast application to inform decision
   making and adaptation options, aiming to better prepare farmers and
   agricultural companies to reduce damages and increase productivity by
   adopting adaptation options.

*Guidance for the policy briefs:  *

The policy brief would be a summary document (6 pages maximum) containing
current status, challenges, good practices and recommendations.


Thanks,

Asha

-- 
___________________________

Asha Law | Program Assistant, CODATA | http://www.codata.org

E-Mail: asha at codata.org
Tel (Office): +33 1 45 25 04 96

CODATA (Committee on Data of the International Council for Science), 5 rue
Auguste Vacquerie, 75016 Paris, FRANCE
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