243
Therefore, it is necessary to identify relevant data types to facilitate the development and tracking of metrics. As a general rule, sources must (1) provide information in global, national, and local contexts; (2) be systematically collected and
follow standardized guidelines and protocols of data collection and processing
such that a comparative analysis of high-quality data will reflect real trends at different spatial and temporal scales; (3) provide sufficient details of metadata; (4)
include all pertinent knowledge systems; and (5) be reported consistently, and collected at regular intervals; and (6) be made accessible to all stakeholders or groups
of interest. As this will require the combination of many different types of datasets
and information, it reinforces the need for collective participation at the design,
implementation, monitoring, and evaluation stages, to define the questions, needs,
and interests to be addressed; select data and analytic tools, and in particular work
with local communities to bolster their involvement during the whole process
including data collection, and in the subsequent interpretation and application of
findings (Maaroof 2015).
By nature, complex systems display non-linear features. This is particularly true
for such systems as drylands, for which it would be unwise to assume that human
behavior will be predictable and follow simple and linear patterns. A number of
gaps in the knowledge base can be identified, most notably: (1) a limited understanding of barriers and challenges; and (2) the want of metrics to evaluate the state
of the system, and to assess its progress and effectiveness. Consequently, while
most data is technically public, navigating the means of access to it can prove a
challenge in itself, and mining it for relevant insights often requires technical expertise and training that organizations and governments with limited resources cannot
systematically afford.
Efficient use of data can only be effected through the collaboration of many
actors, including scientists and those with on-the-ground experience, leveraging
their strengths to plumb the technical possibilities and the context in which this
knowledge can be implemented. The various stakeholders, those who own data and
those who depend on it, should ideally coalesce into a data ecosystem that will stoke
the development and implementation of various policies. Among the main stakeholders we find: (1) governments and public institutions; (2) international and
regional organizations; (3) philanthropy; (4) charities; (5) the private sector and
industry; (6) academics and scientists; and (7) civil society as a whole. The challenge will be to bring together these different actors, as stakeholders tend to act
within rather than among systems and procedures, and it will be crucial that platforms are developed and managed effectively so that the availability of data benefits
integrated approaches to sustainability.
Data-driven development strategies, as tools for formulating policy, can greatly
facilitate the implementation of SDGs. However, many emerging and developing
countries are still struggling to collect and manage much smaller datasets and
statistics, where data is still largely unintegrated, fragmented, or of poor quality, and
statistics are often top-down without feedback to communities. New forms of interinstitutional relationships must arise before data, resources, human talent, and
14 The Agadir Platform: A Transatlantic Cooperation to Achieve Sustainable Drylands
Therefore, it is necessary to identify relevant data types to facilitate the development and tracking of metrics. As a general rule, sources must (1) provide information in global, national, and local contexts; (2) be systematically collected and
follow standardized guidelines and protocols of data collection and processing
such that a comparative analysis of high-quality data will reflect real trends at different spatial and temporal scales; (3) provide sufficient details of metadata; (4)
include all pertinent knowledge systems; and (5) be reported consistently, and collected at regular intervals; and (6) be made accessible to all stakeholders or groups
of interest. As this will require the combination of many different types of datasets
and information, it reinforces the need for collective participation at the design,
implementation, monitoring, and evaluation stages, to define the questions, needs,
and interests to be addressed; select data and analytic tools, and in particular work
with local communities to bolster their involvement during the whole process
including data collection, and in the subsequent interpretation and application of
findings (Maaroof 2015).
By nature, complex systems display non-linear features. This is particularly true
for such systems as drylands, for which it would be unwise to assume that human
behavior will be predictable and follow simple and linear patterns. A number of
gaps in the knowledge base can be identified, most notably: (1) a limited understanding of barriers and challenges; and (2) the want of metrics to evaluate the state
of the system, and to assess its progress and effectiveness. Consequently, while
most data is technically public, navigating the means of access to it can prove a
challenge in itself, and mining it for relevant insights often requires technical expertise and training that organizations and governments with limited resources cannot
systematically afford.
Efficient use of data can only be effected through the collaboration of many
actors, including scientists and those with on-the-ground experience, leveraging
their strengths to plumb the technical possibilities and the context in which this
knowledge can be implemented. The various stakeholders, those who own data and
those who depend on it, should ideally coalesce into a data ecosystem that will stoke
the development and implementation of various policies. Among the main stakeholders we find: (1) governments and public institutions; (2) international and
regional organizations; (3) philanthropy; (4) charities; (5) the private sector and
industry; (6) academics and scientists; and (7) civil society as a whole. The challenge will be to bring together these different actors, as stakeholders tend to act
within rather than among systems and procedures, and it will be crucial that platforms are developed and managed effectively so that the availability of data benefits
integrated approaches to sustainability.
Data-driven development strategies, as tools for formulating policy, can greatly
facilitate the implementation of SDGs. However, many emerging and developing
countries are still struggling to collect and manage much smaller datasets and
statistics, where data is still largely unintegrated, fragmented, or of poor quality, and
statistics are often top-down without feedback to communities. New forms of interinstitutional relationships must arise before data, resources, human talent, and
14 The Agadir Platform: A Transatlantic Cooperation to Achieve Sustainable Drylands