Dear Chipo,

Thank you for bringing this up. I feel honored to have been among the authors of the specific publication, and indeed the Discussion Paper aims to provide some examples where the use of open data in agriculture and nutrition made an impact. There are different application presented, and of course there are many more that we could not include for various reasons (the total length of the publication being one of them). 

The use of ICT tools facilitated various aspects of the process, ranging from the production and collection/recording of the data, to their management, sharing and exploitation. I find a connection with previous week's topic here: The more adapted the ICT tools are to specific applications, the higher the impact is. THe applications are numerous and I will not focus on any specific one.

What I would like to contribute, as a general message, is that we have all the components out there, such as the open data, the applications and ICT tools, the developers, the SMEs that work on data-powered solutions and of course the expected end users. What we need is to provide the mean for connecting all these different parts and stakeholders so that we will manage to come up with meaningful outcomes for the  end users, providing added value to the open data and the efforts of those working with them. As a final result, ICTs and open data should be used for improving food production and addressing the nutritional needs of the constantly increasing global population.

The evoloution of technology has led to an abundance of ICT tools (such as agriculture-focused apps for smartphones, as you mention in your post). However, it seems that not all of them take into consideration the needs of the potential end users (e.g. farmers) so it is hard for them to use. For example, if there is no provision for offline data recording using smartphones in the field, then even a willing farmer (but with no internet connection in the field) will not be able to make the most out of it.

The design of ICT tools should follow a bottom-up approach, so farmers should be the ones providing the requirements that will drive the design and development of apps. Validation of the apps (and other ICT tools) is also a crucial factor, in order to ensure that apps work as expected under various different conditions and with minimum effort from the end user. Last but not least, training on the use of the apps is an important factors, so that end users will fully understand what they can do with an app and how to do it.

Of course, these conditions are hard to apply in the case of individual app (or ICT tools) developers, how do not have the capacity (e.g. financial) to ensure the applicability of these different aspects of their (usually free) apps.

This is a really interesting point, and highlights the role of agricultural extension and training services (as you already mentioned) in developing countries. In such cases, ICT tools tend to be as simple as possible (e.g. based on the use of phones and GSM networks) and end users usually need more guidance and support. I believe that in such cases, ICTs and the exploitation of opean data available in these areas will have greater impact, due to the fact that farming / food production can be significantly enhanced even in a simple (but still effective way).

The challenge is to find the most appropriate and sustainable way to record data from such cases, which will be then reused under the same conditions (in the same of similar areas) to further improve the farming practices.

If we want to succeed in improving food production in developing countries through the integration of ICTs (and making use of open data), then a good candidate would be smart farming (not to be confused with precision farming) - low cost, high efficiency hardware, minimum infrastructure needed and numerous possibilities of making use of open data.

That's a point that should draw our attention: Data acquisition is the first step in the whole data management and exploitation process and in this context, it should be carefully designed and implemented in all data-powered applications. While some types of data used in the agridfood sector are automatically recorded (e.g. sensor, remote sensing etc.), in many cases, the quality of the data depends on the knowledge of the person responsible for the recording.

An interesting example is the concept of CABI's PlantWise programme, where Plant Doctors (see for example here) are carefully trained individuals who have the knowledge to support the needs of the programme. In a similar way, those involved with data recording should also be trained to do so in the best possible way (thus minimizing possible errors).