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In many areas, there is a false belief that the primary sector is a technologically backward sector that is not involved in digitization. Perhaps because throughout history, as economic development indicators progressed, their weight in GDP and employment rates has been decreasing in favor of other sectors.
However, the agricultural sector is once again gaining prominence, as it currently faces a set of challenges that are closely related to the future of humanity. Climate change, food security and population growth are just some of the most challenging. The European Commission itself, through the Horizon 2020 program, is allocating important research resources to the social challenge of food security, sustainable agriculture, marine and maritime research, and bioeconomy.
As in other industries, digital transformation is helping to change the operating bases of the agricultural sector, giving rise to what is already known as smart agriculture or precision agriculture, which is also a very important part of the solution to the mentioned challenges.
The agricultural sector is increasingly combining technologies, such as geolocation, soil and environmental conditions monitoring, artificial intelligence, cloud computing and Internet of Things (IoT), to accurately measure the variations of numerous variables in the crop fields and thus improve the quantity and quality of agricultural products.
As in many other industries, the base of digital transformation is data: open, private or enriched with each other, with data science in a leading role. Data science helps farmers see and understand what is happening in their fields with unprecedented precision, allowing them to make much more sustainable decisions to get an efficient production.
From seeds genetics to environmental conditions -and not only weather, but also any issue that affects agricultural production- can be measured and analyzed in order to make sustainable decisions.
Since we know that small variations in the quantities of materials selectively used at specific times and places can generate huge differences in crop yields, farmers can use data science to decide the right amount of seeds that should be planted in a field or the amount of water, fertilizers or pesticides needed to maximize the seeds yield and minimize environmental damage.
To be real, these applications need to combine open data with internal data coming from the sensorization of the crop fields or aerial images from drones or satellites.
Given the importance of the topic, the Open Data Charter, through the Global Open Data for Agriculture and Nutrition (GODAN) initiative, and as part of the Agriculture Open Data Package (AgPack), has classified the key datasets that public administrations handle and whose opening would have an important impact for the agricultural sector into 14 categories, which are explained in the following figure.
In the figure we find from evident data sets, such as those that contain meteorological, hydrological or geographical data, to others that are useful for multiple sectors besides agriculture, such as imports, exports, prices or quality standards of agricultural products. And of course, data on allowed pesticides, inspections or legislative texts related to one of the most regulated sectors of our economy. GODAN has produced important informative material like this or this webinar about Agpack.
| Main group | Category | Description | Example |
|---|---|---|---|
|
Administration and legislation
data
|
Government, agricultural law and regulations
|
Policy and legislation texts relevantfor the agricultural sector
|
Subsidy schemes; animal health and welfare regulations; import/export regulations; environmental regulations; (phyto) sanitary regulations
|
| Official records |
Lists of organisations, people or products officially registered,permitted or restricted as a resultof legislation
|
Permitted pesticides; (import/export) tariffs; (safety) inspectionresults; approved permits; licensed organisations(corporations, businesses, NGOs); land registration
|
|
|
Government finance data
|
Data on the financial management of the government, budgets, spending
|
Penalties given to agricultural actors; agriculture-related tax income; agricultural subsidy expenditure
|
|
|
Rural development project data
|
Data describing rural development (RD) projects funded by a government. This may be the local government or a donor government (aid)
|
Rural development project documents; rural development project baseline and survey data; rural development project output, outcome and impact; general information on a rural development project
|
|
|
Socio-economic data
|
Land use data and productivity data
|
Data describing the land use, crop types and production of an area or region
|
Biomass; crop yield; cultivated crops and livestock; land use data
|
| Value chain data |
Data describing the value chain and its activities
|
(Food) product data; company profiles of groups of value chain actors or organisations; (food safety) inspection results
|
|
| Infrastructure data |
Data describing national networks for roads, water, ICT, including their condition and maintenance
|
Internet coverage; waterways; road management
schedules; mobile telephone coverage; road network |
|
| Market data |
Data on the location of markets, market prices, market standards
|
Import/export volume; lists of markets and auctions; market prices; global food prices; location of markets; standards, grades, labelling; market management and rules
|
|
|
Natural resources, earth and
environment data
|
Meteorological data
|
Quantitative data on weather and climate
|
Climate change predictions; climate zones; observations
archives; real-time observations; short-term weather forecast |
| Elevation data |
Data describing the elevation of the
terrain and its derivates |
Digital elevation model; height points; slope data;
aspect data
|
|
|
Hydrological data
|
Data describing the state and dynamics of ground and surface water
|
Water management; water tables; water quality; real-time water levels; historical records on flooding; flood zones; water balance; location of water sources
|
|
| Soil data | Data describing soil properties | Soil classes; soil samples; soil maps | |
|
Agronomic data, agricultural technologies
|
Production advice
|
Data related to crop selection, crop and land management
|
Fertilizer recommendations; intercropping, relay cropping and rotations; agronomic practice recommendations; crop calendars; data on cultivars, land races and farmer varieties including new releases
|
|
Pest and disease management data
|
Data on the distribution of pests and diseases and their treatment
|
Occurrences and distribution of plant diseases; treatment of plant diseases; recommended pesticides
|
To interpret this table to design appropriate policies, it is necessary to bear in mind that we are faced with very diverse data sets. In some countries, these data sets are managed by public administrations, while in others they could be in the hands of private initiatives, because agricultural data are not exclusive to public or private organizations.
Like the big companies that operate in different parts of the sector''s value chain, such as John Dere or Monsanto (now Bayer), which have been working for years to create tools to collect and analyze data on farmland and resources, Public administrations also have a possible roadmap to plan their data opening policies in the agricultural sector.
Undoubtedly, the combination of public and private efforts to advance the collection, opening and enrichment of data with impact on the agricultural sector activities will contribute to the development of a greater number of applications that can be used to improve the productivity of the sector, the food security and the environmental sustainability.
Content prepared by Jose Luis Marín, Head of Corporate Technology Startegy en MADISON MK and Euroalert CEO.
Contents and points of view expressed in this publication are the exclusive responsibility of its author.
Documentación
A few months ago we published a compilation of the main reports, studies, success stories and courses published by the Global Open Data for Agriculture and Nutrition (GODAN). This body seeks the proactive sharing of freely accessible data to make information on agriculture and nutrition available, accessible and usable.
To achieve this goal, GODAN has different teams that work in a coordinated manner for a common goal. One of them is the Capacity Development Work Group, focused on promoting open data knowledge (ongoing initiatives, innovations and good practices), as well as the development of new capacities. All of them to guarantee a more effective accessibility, use, engagement and understanding of open data.
In 2017, this group launched Godan webinar services, in order to offer a series of webinars organized in collaboration with the Technical Centre for Agricultural and Rural Co-operation (CTA). The videos, which last between 40 minutes and one hour, help to delve into different concepts: they explain how an open data initiative on agriculture should work, or how to tell stories with data to raise organizations and citizens’ awareness. Some of the organizations that have participated in the preparation of the contents are the Open Data Institute (ODI), Wageningen UR or The Land Portal Foundation, among others.
Here are some of the resources that can be found in Godan webinar services:
| Title | Content |
|---|---|
| Publishing open data from an organisational point of view | This webinar tries to answer a series of basic questions: Why is it necessary to publish open data? What benefit can publishing open data bring to the organization? Why are licenses important? How to start with publishing open data? |
| The Agriculture Open Data Package (AgPack) | In 2016, 4 agencies (GODAN, ODI, Open Data Charter and OD4D) developed the Agricultural Open Data Package (AgPack), which included 14 categories of datasets whose opening could have an important impact for the agricultural sector. This webinar shows detailed examples and use cases of governments that have achieved success in this area. |
| Effective data communication using data visualisations | Visualizations can help reveal, in a simple way, agriculture and nutrition trends to support decision making. This webinar explains the process of creating a good infographic, demonstrate some visualization software and reflects on how infographics are being applied for open data for agriculture and nutrition. |
| The Gender and Open Data Intersection | This webinar provides an analysis of open data from a gender perspective: from the current state of the question, to the challenges to overcome. The webinar ends with a series of recommendations to pave the way forward. |
| Agricultural Development: Role of Open Data in Ending Poverty | Open data can help end extreme poverty, end hunger and reduce inequalities. This webinar seeks to boost the capacity of states to openly share data and statistics for decision making. |
| Facilitating Standards and Impact Webinar | This webinar addresses the standards and impact evaluations of open data, with a special focus on weather data. Among other topics, the speakers analyse the trends and major gaps in the availability and use of weather data standards, followed by recommendations on how to make existing data standards more usable or how to develop services that facilitate the use of standards. All this through examples and success stories. |
| Farmers rights on data and ownership issues | Data ownership and privacy are two of the challenges of smart agriculture. This webinar tries to inform farmers about their rights from a legal perspective. |
| Unlocking the Potential of Blockchain for Agriculture | This webinar provides an overview of blockchain and analyzes its impact on agriculture, through examples and success stories in specific areas. The webinar also explains what capabilities people need to work with this technology. |
| Measuring the impact of open data initiatives in agriculture & nutrition | This webinar explains the methodology that GODAN uses to measure the impact of an open data initiative. Its evaluation framework focus on earlier stage assessment, as this offers better options to design new and, monitor and steer ongoing initiatives. |
In addition to these more general webinars, Godan webinar services also offers specific resources, where different initiatives tell their experience when publishing or reusing open data on agriculture and nutrition. An example is the Regional Centre for Mapping of Resources for Development (RCMRD), which shows some of the projects in which it is involved in one of the videos.
In short, whether you are a public body that wants to start or consolidate an open data initiatives on agriculture, or a reuser looking for examples and success stories to inspire you, Godan webinar services can provide resources and information of interest.
Documentación
The Global Open Data for Agriculture and Nutrition Initiative, known by the acronym GODAN, aims to support "the proactive sharing of open data to make information about agriculture and nutrition available, accessible and usable." To this end, GODAN fosters dialogue and cooperation in agricultural activities between more than 760 members, including governments, private companies, international organizations or NGOs.
Through different working groups, GODAN contributes to share ideas and experiences to solve key problems and challenges in the agriculture and nutrition sectors, using open data. Some of these challenges are ridding the world of famine, ensuring food security, improving nutrition or facilitating sustainable agriculture.
In order to help more companies, organizations and citizens to be aware of the importance of open data to solve these challenges, GODAN promotes the creation and dissemination of resources that drive both providers and users reflection on agricultural open data. Among these documents, we can find:
- Reports, which analyze different challenges and include recommendations or good practices aimed at enriching the available information about agriculture and nutrition, encouraging their analysis and reuse.
- Success stories, which can be used as an example for those organizations interested in being part of this ecosystem, but do not know how to take advantage of open data to generate new initiatives that add value to the sector and solve the aforementioned challenges.
- Courses aimed at strengthening data producers and consumers capacity to manage and use open data in agriculture and nutrition sector.
We have compiled some of these resources, described in the following table:
| Document type | Title | Content |
|---|---|---|
|
Reports |
Ownership of Open Data: Governance Options for Agriculture and Nutrition |
Moving to a model where data is open as a standard requires a change in legal, social and technological context, and this will have an impact on data ownership. To achieve this goal, the report analyzes the underlying rights and possible governance systems, such as the inter-organizational statute of open data, laws and policies, social certification schemes, etc. |
| A Global Data Ecosystem for Agriculture and Food | This study tackles open data sourcing and handling cycle, from the point of view of both users and providers, analyzing the challenges to be solved and the roadmap to build an ecosystem for global agricultural data. Among the proposals included in the report, we can find the provision of incentives and the promotion of trust between providers and users. To achieve this goal, a cultural and technological change will be necessary, as well as improvements in data quality, origin and access. | |
| Responsible Data in Agriculture | The report explores how inequalities between large agricultural corporations and small local producers could be reduced, to guarantee fair access to information. With this objective, they spoke to 14 individuals with different perspectives to understand their main challenges. The report concludes with a series of good practices, which include education and awareness actions, policies reviews or the prioritization of contextual considerations. |
|
| Success Stories | GODAN Success Stories - Issue 1 |
This report, published in 2016, explains different examples of open data projects and initiatives linked to agriculture and nutrition field. Through different stories, we can learn how to extract value from satellite images or how to improve land registration transparency, among other issues. |
| GODAN Success Stories - Issue 2 | The second part of the report was published one year later, with new success stories. In this case, we can find examples as FOODIE, a European initiative that seeks to solve agriculture challenges thank to geospatial data, or BOER & BUNDER, a web application that uses algorithms to extract data value, using simple visualizations to show the results. | |
| Curses | Open Data Management in Agriculture and Nutrition | Free online course with different calls throughout the year. Its objective is to promote agricultural and nutritional knowledge networks in different institutions, raise awareness of different types of data formats, explain possible use cases and highlight important it is for data to be reliable, accessible and transparent. |
To learn more about GODAN resources, you can visit their website publications section. In this section, which is periodically updated with new publications, users will find more documents and reports related to open data in agriculture. The dissemination of these contents can help develop high-level policies, and support the private sector for opening more data, which is fundamental to overcome important challenges for humanity.