{"id":2072,"date":"2018-03-15T11:38:12","date_gmt":"2018-03-15T11:38:12","guid":{"rendered":"http:\/\/labs.webfoundation.org\/id\/data-for-development-whats-next-new-research\/"},"modified":"2018-03-19T11:40:20","modified_gmt":"2018-03-19T11:40:20","slug":"data-for-development-whats-next-new-research","status":"publish","type":"post","link":"https:\/\/labs.webfoundation.org\/id\/data-for-development-whats-next-new-research\/","title":{"rendered":"Data for Development: What\u2019s next? [New Research]"},"content":{"rendered":"

\"\"<\/p>\n

Digital data offers a great many opportunities for development by enabling actors to strengthen decision-making processes, improve service delivery, elicit meaningful citizen participation, and increase responsiveness in humanitarian services. At the same time, it can generate new forms of exclusion, new methods of surveillance and threatens individual privacy.<\/p>\n

In a new report,\u00a0Data for Development: What\u2019s next<\/a>, we investigate how organisations working in international development can leverage the growing quantity and variety of data to improve their investments and projects so that they better meet people\u2019s needs.<\/p>\n

The report, commissioned by the\u00a0Deutsche Gesellschaft fuer Internationale Zusammenarbeit<\/a>(GIZ) and conducted in collaboration with the\u00a0Institute of Development Studies<\/a>\u00a0(IDS), investigates the state of data for development, identifies emerging data trends, and provides recommendations to support German development cooperation actors seeking to integrate data strategies and investments in their work.<\/p>\n

The research considers four types of data: (1) big data, (2) open data, (3) citizen-generated data and (4) real-time data, and examines how they are currently being used in development-related policy-making and how they might lead to better development outcomes.<\/p>\n

<\/b>Our research uncovered six key trends:<\/b><\/h2>\n
    \n
  1. More data and new data sources<\/b>. The quantity of data available is increasing at an exponential rate due to increased computing power and broadband speed, as well as the emergence of new data sources such as drones, nano-satellites and the Internet of Things.<\/li>\n
  2. Powerful new technologies<\/b>. Artificial intelligence has come of age and algorithms have improved autonomous data analytics tremendously, increasing the speed at which data is processed to make sense of development challenges.<\/li>\n
  3. New actors<\/b>, such as data innovation labs and data analytics companies,\u00a0and new partnerships,<\/b>\u00a0like data philanthropy arrangements and data collaboratives, play an increasingly important role in the development sector.<\/li>\n
  4. Balancing access to data and privacy<\/b>\u00a0is likely to receive growing attention in the coming years with key players realising that protecting individual privacy while using personal data to tackle development challenges is extremely difficult.<\/li>\n
  5. There is a\u00a0growing recognition of the value of contextual, granular information<\/b>\u00a0and of the need to integrate local and qualitative knowledge into data for development initiatives.<\/li>\n
  6. Information inequality is likely to persist or increase,<\/b>\u00a0as data production and ownership continues to rest primarily in the hands of government and a handful of private sector players \u2014 both of which are in a better position than others to harness the benefits arising from data.<\/li>\n<\/ol>\n

     <\/p>\n

    For German \u2014 and other \u2014 development organisations to further strengthen their work around data for development, we recommend that they:<\/b><\/p>\n

      \n
    1. Maximise the potential of data, but don\u2019t treat it as a silver bullet<\/b>. The availability of data alone does not guarantee use; an enabling environment to incorporate data into policy-making and programming is needed.<\/li>\n
    2. Build internal data capacities by investing in internal data literacy<\/b>\u00a0based on an assessment of current capacities to determine the need for data scientists and technologists.<\/li>\n
    3. Leverage partnerships for a strategic advantage<\/b>\u00a0by, for example, participating in the Global Partnership for Sustainable Development Data, endorsing the International Open Data Charter, and working with new and emerging actors to form data collaboratives.<\/li>\n
    4. Support strong legal and technological data privacy frameworks<\/b>\u00a0in partner countries to mainstream responsible and secure data practices, champion responsible data approaches, and actively shape the debate around artificial intelligence and privacy.<\/li>\n
    5. Be experimental and focus on a few sectors and geographies<\/b>\u00a0instead of investing in cross-cutting data initiatives; help nurture data ecosystems in sectors like procurement, extractives and health.<\/li>\n
    6. Tackle data inequalities through targeted research and empowerment of local stakeholders<\/b>\u00a0by investing in the capacity development of local actors, and in the infrastructure needed to enable widespread data access and use.<\/li>\n<\/ol>\n

       <\/p>\n

      To explore these recommendations and find out more about current trends in data for development, download the full report:\u00a0Data for Development: What\u2019s next<\/a>.<\/b><\/p>\n

      \n

      For updates on news and research, follow the Web Foundation at\u00a0<\/i>@webfoundation<\/i><\/a>\u00a0and sign up to receive our\u00a0<\/i>email newsletters<\/i><\/a>.<\/i><\/p>\n","protected":false},"excerpt":{"rendered":"

      Digital data offers a great many opportunities for development by enabling actors to strengthen decision-making processes, improve service delivery, elicit meaningful citizen participation, and increase responsiveness in humanitarian services. At the same time, it can generate new forms of exclusion, new methods of surveillance and threatens individual privacy. In a new report,\u00a0Data for Development: What\u2019s […]<\/p>\n","protected":false},"author":16,"featured_media":2071,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[179,214,175,182],"tags":[630,631,361,632],"class_list":{"0":"post-2072","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-blog-id","8":"category-presentations-on-open-data-id","9":"category-uncategorized-id","10":"category-web-foundation-id","11":"tag-bmz-id","12":"tag-data-for-development-id","13":"tag-giz-id","14":"tag-recommendations-id","15":"entry"},"_links":{"self":[{"href":"https:\/\/labs.webfoundation.org\/id\/wp-json\/wp\/v2\/posts\/2072"}],"collection":[{"href":"https:\/\/labs.webfoundation.org\/id\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/labs.webfoundation.org\/id\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/labs.webfoundation.org\/id\/wp-json\/wp\/v2\/users\/16"}],"replies":[{"embeddable":true,"href":"https:\/\/labs.webfoundation.org\/id\/wp-json\/wp\/v2\/comments?post=2072"}],"version-history":[{"count":0,"href":"https:\/\/labs.webfoundation.org\/id\/wp-json\/wp\/v2\/posts\/2072\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/labs.webfoundation.org\/id\/wp-json\/wp\/v2\/media\/2071"}],"wp:attachment":[{"href":"https:\/\/labs.webfoundation.org\/id\/wp-json\/wp\/v2\/media?parent=2072"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/labs.webfoundation.org\/id\/wp-json\/wp\/v2\/categories?post=2072"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/labs.webfoundation.org\/id\/wp-json\/wp\/v2\/tags?post=2072"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}