20
Oct 17

Can Big Data Help Feeding The World?

Aymen, October 20.

Big Data goes beyond just the existence of data. The ability of Big Data techniques to generate insights through synthesizing data from a range of sources may hold the greatest potential and carry the greatest risks of all. On one hand, Spratt and Baker, in their report “Big Data and International Development: Impacts, Scenarios and Policy Options”, explain that Big Data can be manipulated to promote certain political agenda or increase the possibilities for governments and large corporations to discriminate against certain groups or individuals.

big data feeding world

On the other hand, Big Data may have a positive environmental impact as well as a great potential in agriculture and rural development. It can bring new insights and decision points that lead to product/service innovations. This potential touch on, for example, precision farming with very efficient water and fertilizer use, food security coordination through tracking, tracing and transparency and personalized health and nutrition advice. The availability of easily accessible data plays a major role in documenting quality standards of agricultural products, saving time and improving productivity.

Several projects launched by development organizations rely on Big Data to optimize agriculture. For example, FAO launched in more than 10 countries in Africa, Asia, Eastern Europe, Latin America and Near East the Virtual Extension and Research Communication Network (VERCON). According to FAO, VERCON is a conceptual model that employs internet-based technologies and Communication for Development methodologies to facilitate networking, knowledge sharing and interaction among agricultural institutions, producer organization and other actors of the agricultural innovation system.

In Egypt for instance, where the first project was launched in early 2000, 100 VERCON access points had been installed in various places, such as extension units, agricultural directorates, research institutions and stations, and Development Support Communication Centers. They were connected to the internet to allow farmers to access to an agricultural economic database as well as news and bulletins that help them in solving their problems. In addition, the platform was useful to share ideas and experience of local farmers and monitor the whole project.

The VERCON project was successful since it relied on existing organizational structures and links. Also, the platform ensured rapid response to user feedback thanks to regular monitoring and access to monitoring results. It used rural and agricultural appraisals at the field level to ensure that the virtual network would be accurately focused on the information and knowledge needs of the larger agricultural community.

The project was successful and the Rural and Agricultural Development Communication Network (RADCON) was set up to engage with a wider range of rural and agricultural development issues and to extend the VERCON network to a wider range of stakeholders, including farmer organizations, youth centres, universities, and NGOs.

However, the challenge that the project must take is the use of ICTs by farmers themselves.  Despite the success of projects that imply Big Data for rural development, developing world-based farmers often face difficulties in meeting the quality and safety standards set by the developed world. The conditions that stimulated the growth of Big Data in the farming industry in the global north such as the widespread adoption of mechanized tractors; genetically modified seeds, computers, and tablets for farming activities are less prevalent in developing countries. While large growers can afford specialized machinery, small farmers do not have this opportunity. As a result, they can neither access the data nor interpret it.

Big Data for rural development can help analyzing large amounts of information related to rainfall data or the pest vector could give valuable insights into important issues such as climate change, weather patterns and disease and pest infestation patterns. However, this valuable information largely benefits the Big Data industry in the Global North. It can have a positive impact on big farmers in the global south, but rural communities might be excluded as they still have little or no access to ICTs.

Nowadays, as evoked by Spratt and Baker, those who are in favour of Big Data adopt an evangelical tone to argue for its benefits; while those who are against it tend to stress its dystopian nature. It is important to remember that Big Data is a very recent phenomenon; according to sciencedaily.com, a full 90 percent of all the data in the world has been generated since 2011. In practice, we don’t have the necessary distance to evaluate its real impact.

When it comes to agriculture, farmers all over the world must produce more to feed world’s rapidly expanding population in the coming decades. Will big data help feeding nine billion people by 2050? Time will tell…

 


10
Oct 17

Big Data Visualization: A Big Asset for decision making

Aymen, October 10.

As defined in a previous article by Feinleib, Big Data is the ability to capture, store, and analyze vast amounts of human and machine data, and then make predictions from it. On the other hand, Beyer and Laney, in their definition of Big Data, stress that it useful for an enhanced insight and decision-making.

Indeed, stocking large amounts of information is not useful by itself, but the main goal, in this case, is the way to use and combine this stock of data to facilitate decision making. For example, financial markets increasingly rely on Big Data to trace stock prices and refine predictions for computer-based trading. From a development perspective, Big Data can be useful to follow the development of projects and better understand the needs and expectations of beneficiaries.

Still, when thinking of Big Data, large SQL or Excel tables or algorithms for instance usually come to our minds. Although these two tools require a certain expertise to have the ability to “read between the lines,” they remain incomprehensible for the ordinary person. In his book “The Promise and Peril of Big Data,” David Bollier explains that Big Data usually rely on powerful algorithms that can detect patterns, trends, and correlations over various time horizons in the data, but also on advanced visualization techniques as “sense-making tools”.

In this sense, it is equally important to present eye-catching visualizations of the results extracted from Big Data. They will firstly contribute to making a large amount of information understandable and accessible, in addition to the dissemination of the findings through academic publications, reports, presentations, and social media. In his book “Data Visualization with JavaScript”, Stephen A. Thomas defines Data Visualization as the way to visualize large amounts of data in a format that is easily understood by viewers. The simpler and more straightforward presentation, the more likely the viewer will understand the message.

Indeed, Data Visualization is an important feature of Big Data analytics, as it can provide new perspectives on findings that would otherwise be difficult to grasp. For example, “word clouds”, which are a set of words that have appeared in a certain body of text – such as blogs, news articles or speeches, for example – are a simple and common example of the use of visualization, or “information design,” to unearth trends and convey information contained in a dataset, but there exist many alternatives to word clouds, such as geographic representation.

For instance, the infographic here below, based on large amounts of information, explains how mobile technology is used worldwide as a tool to improve health care, education, public safety, entrepreneurship, or the environment. These worldwide initiatives are part of the 9th Sustainable Development Goal (SDG), which aims to “Build resilient infrastructure, promote inclusive and sustainable industrialization, and foster innovation.”

big data visualization

In this example, Big Data is doubly useful as it is the base of projects launched in the various countries represented on the map. Concretely, it contributes to reducing maternal deaths from placenta praevia in Moroccan rural areas. Furthermore, the simple visualization of this large volume of information facilitates its analysis and can consequently help decision makers to track the progress of projects and can be used as benchmark data to reproduce the same successful initiatives in other countries.

Geographic representation of Big Data is used in the various field, especially in monitoring migration movements. In this sense, almost 200 academic studies involving big data and migration had been published between 2007 and 2016. The Syrian refugees’ crisis is a significant example of the use of Big Data to visualize migration flows. The infographic here below from the New York Time explains in a clear way how nearly half of Syria’s entire population was displaced due to the civil war.

big data visualization

In a wider context, the geographic representation of migration flows between 2000 and 2016 based on Big Data gathered by the UN Refugee Agency (UNHCR) summarizes in a clear and synthetic way the countries of origins and of residence/asylum of migrants.

These are two examples of how geographic visualization of Big Data can – through the historical track record – predict more accurately how many more refugees could be expected over coming years into which points of entry. As a result, military, police, and humanitarian efforts be more coordinated and pre-emptive based on this information.

It is important to take into consideration that stocking large amounts of information is not useful by itself, but its main goal is to use and combine this stock of data to facilitate decision making and create added value. The analysis of Big Data is a big asset as it might facilitate tracking the progress of projects, understand migration trends or allow a better-coordinated mapping of conflict or adversity and delivery of aid to people in dire circumstances.

However, we must remember that Big Data also enable strategies of surveillance, control, and population management. Big Data involves the quantification, classification, and construction of individuals and populations, and categories that are never impartial or objective but embedded in socio-political contexts. It is the researcher’s ethical role to keep these crucial points in mind when deciding what data to use, how to get it, treat it, store it, and share it. In the UK for instance, the manipulation of data and statistics has played a major role in bolstering anti-immigration narratives and xenophobic political agendas. This is to say that raw Big Data or visualized one are not themselves harmful, but the way they are used is indeed dangerous.


30
Sep 17

Big Data: a Tool to Improve Local Governments

Aymen, September 30.

Nowadays, data is everywhere around us, from our Smartphone to our tablet, to that laptop or PC on our desks; data is pervasive and plentiful. Indeed, as reported by the Economist, “The world’s most valuable resource is no longer oil, but data”. Big Data may create risks with respect to rights, as surveillance opportunities are increased, and the growth in e-waste creates environmental risk, but it also generates a wealth of opportunities.

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21
Sep 17

Big Data and Development: Challenges and Opportunities

Aymen, September 21.

Even though algorithm, coding, Big Data is becoming part of our daily life; these technical terms remain complicated for us, common mortals. What is Big Data for instance?

In his book “Big Data Demystified: How Big Data Is Changing The Way We Live, Love And Learn,” David Feinleib defines it as the ability to capture, store, and analyze vast amounts of human and machine data, and then make predictions from it.

Big Data is used for various purposes, for example, to understand online consumers’ behaviour and orient advertisements to their specific needs, and is the base of the predictive power of search engines. It is transforming the nature of business and profits worldwide and is gaining in importance in the development sector.

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