A Shared Global Data Ecosystem for Agriculture and the Environment


The executive summary of GODAN’s recent discussion document ‘A Global Data Ecosystem for Agriculture and Food’, (the cover of which manages to somewhat capture the problem with the modern agricultural environment), calls for:

..a common data ecosystem, produced and used by diverse stake-holders, from smallholders to multinational conglomerates, a shared global data space..

The report identified stakeholder engagement, provenance in data sourcing and handling, sharing, and collaborative frameworks as key components in developing a global data ecosystem.

Stakeholder Engagement and Data Integrity

However within the agricultural sector “many groups might not have obvious motivation to participate in data sharing and use…” and that “..in order to get trust-worthy data, there has to be a direct reward to the data supplier.” The authors further state that “a large part of the motivation for data sharing has to do with how widely it will be shared, with whom and under what conditions.

There is, justified or otherwise, suspicion that data may be misappropriated to the provider’s dis-advantage or provide disproportionate advantage to others. The perceived risk of negative unforeseen consequences can outweigh any potential benefits of sharing data, particularly when those benefits can not be so readily quantified or realized in the short term.

Stakeholders may develop a big brother mentality where they respond by withholding data or deliberately providing inaccurate data in the belief they are better served. This problem is amplified in the provenance of agricultural products, which “undergo a chain of transformations and pass through many hands on their way to the final consumer”. One drop in the veracity of data at any point in the chain potentially undermines all the data in that chain. These issues are sadly though not just relevant to small farmers and supply chain operators but are as prevalent and strongly held by many of the big data holders such as trans-national corporations, governments and academic institutions.

Informed Consent

Whilst the integrity of the source and the veracity of the data are important factors in building a global data ecosystem the authors further identified ‘documentation, support and interaction’ as key to fostering trust. Data providers and users need to interact so as to serve each others needs better and ensure that stakeholders feel included not just sampled. Stakeholders need to be confident that there are no negative consequences or disproportionate benefits from sharing data to the whole ecosystem.

Sharing Frameworks

Where the data is held, who maintains it, the veracity, accessibility and availability to the whole ecosystem as well as who pays to deliver those services are issues that also need to be addressed. A global data ecosystem cannot rely on single large repositories to act as data silo’s or individual data providers to maintain data crucial for network function. Data needs to be distributed and maintained across the system to prevent bottle necks and failure points . The concept of the ADS (application database storage) network  which exploits the distributed network concept could potentially offer resolutions to many if not all these issues.

Data Conformity and Convention

Whilst stakeholders need an environment that is transparent, robust and secure, the data, as does all the documentation and support in that environment, needs to conform to certain conventions. The ‘five star open data maturity model (available, structured, non-proprietary format, referenceable and linked)’ lays out a basic checklist but these properties themselves need to further conform to taxonomies and naming conventions (controlled vocabularies) that are inter disciplinary and facilitate data from different sources being easily related. Conventions which must themselves be explained in and applied to any documentation and support.


In order to get trust-worthy data, there has to be a direct reward to the data supplier

For large stakeholders, governments and corporations that reward may come from the need to provide proof in meeting sustainable development goals and climate commitments, but with smaller stakeholders the same incentives may not apply. The question needs to be asked “what’s the data worth?” or more importantly “what is the cost of not having the data?” Can we achieve global sustainability goals and climate objectives without the majority of stakeholders taking part? If we can’t, is it worth weighting benefits in the short term to favour the smaller stakeholders to encourage them? Even weighting that benefit in the form of payment for engaging, and if so can technologies such as blockchain be used to verify data and facilitate those payments? One possible use for such a mechanism would be for the annotation of data such as satellite imagery.

Collaborative Frameworks

The authors draw attention to the fact that sharing data is only the start; “It is one thing to share data, but to achieve the desired gains from a data ecosystem for agriculture, to draw conclusions across the globe to guide decision making, it is necessary to exploit synergy between datasets efficiently.

Such synergies however arise out of a framework that extends beyond purely agricultural data to one that includes all environmental data. It is a framework that similarly needs to be able to seamlessly integrate with more mundane economic, sociopolitical and legal data and frameworks, an integration that will itself give rise to greater synergies between our economic activities and their environmental consequences. Di-Functional Modelling (DFM), what most of this site is dedicated too, is one such framework.

agricultue-zero-emission02Di-Functional Modelling (DFM)

Designed around the concept of soil fertility DFM was created to model the processes and resources that contribute to the sustainable management of an environmental project. In the normal course these would be the soils of an agricultural unit, a group of units or a component in a unit such as a field, forest or grassland.

However DFM is not restricted to modelling soil fertility and can be used to model other mechanisms in the agricultural and wider environment. [Agriculture in a Zero Emissions Society]

DFM is not though a database, blockchain or application but a framework or ‘ecosystem’ within which the inter-dependencies of the whole system can be more easily visualized. DFM can thus assist in the development of databases, blockchains and applications that are inter-operable and can exchange and verify environmental and agricultural data [Data Databases and Distributed Networks].

agricultue-zero-emission-economicDFM similarly models the processes and functions of an agricultural system relative to the whole. A whole that further extends to the interactions and exchanges that occur between natural systems and the socioeconomic systems they support. These sociopolitical, economic and legal system are themselves nested within the model.

These inner mechanisms are connected to the environment by existing supply chain mechanisms, data from which can reveal the true sustainability or carbon footprint of agricultural goods [TRASE]. Further enhancement of these mechanisms with relevant data should make it possible to trace the ingredients of a chocolate bar from field to retail outlet, every step and any within to give a grand total of the true cost of the indulgence in terms of carbon, habitat or social impact. Once calculated the totals could be added to your own personal tally of GHG emissions, habitat loss and social deprivation. [strengthening the food chain with the block chain]


DFM was though conceived for and is best used to help determine localized land use, crop choices and management strategies based on the available resources and the soil, habitat and hydrological properties. It was not envisaged as a top down tool but as a tool to be applied at the farm end; to provide a means to both audit the farm and it’s resources, and structure that audit in a way that facilitates integrating scientific data. By repeating the process on successive farms and linking those farms through a content management system each audit could contribute to a greater one permitting each unit to enhance it’s own data with that of neighbouring farms. Extended over a region and the framework would help to manage and allocate resources, plan crop choices and integrate with the natural environment: A Shared Global Data Ecosystem that mirrors the Shared Global Ecosystem we call home.


Towards a Data Ready Farm




 The Sustainable Farm

The sustainable farm and by extension a sustainable agricultural sector and planet, is one underpinned by knowledge and driven by data. Knowledge and data that can contribute to crop and livestock choices, resource management and ultimately reveal the sustainability, or not, of an enterprise.

The data ready farm is thus aware of it’s own resources, the resources of the surrounding environment and the relationship it has with those resources and the markets it supplies.




Local Knowledge: A Land Use Inventory

Whilst technology has a significant role to play, the data ready farm begins with knowledge of itself, the land use (woodland, cultivated, grassland), the inherent properties (soil and water resources), as well as the livestock and crops that depend on those resources. It is a simple inventory at the local scale; one which requires no equipment to perform.

Land Use                       Woodland, Cultivated, Grassland
Inherent Properties    Soil Texture and Water Resources
Land Dependants        Livestock and Crop Choices

The inventory should distinguish land use according to basic habitat criteria: woodland, grassland and cultivated. As this is a farm the cultivated habitats further differentiate into arable (short rotation), permanent (orchards, vineyards, etc) or heterogeneous (covered crops, flowers, etc). The woodlands and grasslands similarly differentiate but at this point only grasslands land connected with farming, pasture and rough grazing, need to be differentiated. The boundaries between and within the habitats, along with any hedgerows, fences or banks on those boundaries, and the position of any wells, standing or running water within them should also be recorded and mapped. Even if the farm appears homogeneous, has only one land use, crop or livestock, it is still likely made up of several parcels of land with varying properties; properties that are not easily visible in themselves but can be revealed by the recording and analysis of simple data, such as soil texture.

hand textural chart by S Nortcliff and JS Lang from Rowell (1994)

hand textural chart by S Nortcliff and JS Lang from Rowell (1994)

Soil Texture

Soil texture, a property that arises out of the relative proportions of sand silt and clay strongly influences the hydrological and nutrient characteristics of the soil. Variations in soil texture across a field or farm can thus reveal changes in the hydrology or nutrient status of the soil.

Soil texture can be measured by taking a small sample of soil from just below the surface (10cm). Moistened with water or spit the sample is then moulded with the hands into a ball. The ball is then deformed and it’s malleability noted and checked against a chart. The sample is usually taken along a ‘W’ transect positioned across the face of a field and the data bulked to provide a single textural class for that field/plot. All that now remains is to quantify the livestock and crop choices that depend on the land; at this point it is jut to list the type, number and location of stock and crops. This basic reconnaissance map, which needs no equipment to create, can be drawn onto a piece of paper to identify the land use, crop choices, soil texture, location of water and number of livestock.


A Local Inventory in a Global Context

With remote sensing and mobile technology the inventory and soil data could be annotated directly onto a map from the field. Coupled with Geo-statistical strategies this could be further developed to create complex contour maps of textural variation across the agricultural landscapes. With additional external scientific, environmental and economic data this local inventory could be qualified relative to a global economy


data-ready-farm-02science-dataScientific Data

Into this inventory scientific data relevant to the sustainable management of resources and the husbandry of crops and livestock can be appended.

Meteorology           Quarterly precipitation figures.
Crop Data                Nutrition, culture, pest and disease, 
Livestock Data       Nutrition, stocking numbers, general husbandry.
Soil Mineral data   345 nutrient model



Environmental Data

data-ready-farm-02environmentsIntegration of environmental data can help the farm be sympathetic to the needs of the natural environment and the species that inhabit it. Aware of the environments and species around it the data ready farm can identify synergies and conflicts and then use that data to find resolutions to conservation, pollution and emissions issues.

Conserve habitats and species
Prevent pollution from soil erosion and nutrient leaching
Reduce emissions from livestock and management practices



Market Data

To meet global sustainability goals the data ready farm must link and integrate with the ‘wider’ economic, sociopolitical and legal frameworks. Data from supply chain mechanisms, political policies, and legal and administrative bodies must integrate seamlessly with data from the agricultural and natural environments to meet SDG’s and climate change objectives.

Supply Chains               TRASE and the blockchain
Legal Frameworks       COP22 Objective
Political policy              Paris Agreement

A Local Data Hub

A farm that is aware of itself, the environment and the markets it supplies has the means to measure it’s sustainability relative to the environment and the markets. However a farm integrated with neighbouring farms can improve it’s sustainability. A locally connected farm has greater resilience and can better manage and share resources, integrate crop and livestock choices, and supply markets more efficiently. A local data hub can connect remote farmers and help to build trust and educate in using and sharing data.

Applications and Databases

To move beyond a simply inventory and into a sustainable data driven future requires the development of applications and databases that compliment the framework. Some such as TRASE already exist but local databases and applications to share data within a comprehensive and structured framework still needs development. [Data Databases and Distributed Networks]

The Global Carbon Footprint

Fossil Fuels 

Since 1751 approximately 392 billion metric tonnes of carbon have been released to the atmosphere from the consumption of fossil fuels and cement production. Half of these fossil-fuel CO2 emissions have occurred since the mid 1980s.[Carbon dioxide information analysis centre]

carbon-footprint-globeIt’s widely reported that the World emitted another 38.2 billion tonnes of CO2 in 2015, an 8% increase on 2014’s 35.6 billion tonnes, raising the global average of CO2 from fossil fuel burning to 5.3 tonnes per person and adding another 10% to the 392 billion tonnes released over the last 200 years.

In 2014 the top five CO2 emitting nations, responsible for 2/3rds of all fossil fuel carbon emissions, were China (10.5bt), USA (5.3bt), European Union (3.4bt), India (2.3bt) and Russia (1.7bt).

Whilst five of the biggest emitters relative to population were Gulf states: Qatar (39.13t), Kuwait (28.33t), United Arab Emirates (21.3t) Oman (18.92t) and Saudi Arabia (16.8t).

Australia (17.3t), The USA (16.5t) and Canada (15.9t) came next whilst Kazakhstan (14.2t) and Russia (12.4t) came 9th and 10th in per capita emissions.

China in 20th (7.6t) whilst the European Union, which came 23rd (6.7t) carried some big emitters such as the Netherlands (9.4t), Germany (9.3t), Belgium (8.7t) and Poland (7.8t). Only Spain and France’s emissions matched the global average of 5 ton. India, the 4th largest emitter by country, produced only 1.8t per head putting it in 42nd place, 5th from bottom and beaten only by Indonesia, Philippines, Pakistan and Nigeria. [wikipedia]


So whilst the industrialised nations are the principal emitters of CO2 from fossil fuels, the residents of the Gulf states have a bigger carbon footprint than any other geographical region. Qataris in particular have 2½ times the carbon footprint of American’s and 43 times that of Pakistanis.

Land Use and Managementgreenhouse-gas-dfm

Land use changes, in particular deforestation, where 2/3rd’s occurs to supply just five global commodities [cant see the woods for the trees], contributes a further 6.5 billion tonnes (11%) to global GHG emissions. Methane from livestock contributes a further 16% whilst Nitrous Oxide from fertilizer use contributes another 6%. [EPA]

So whilst fossil fuel burning (65%) remains the main contributor to GHG emissions, land use changes and management practices are responsible for 33% of global GHG emissions. When added together, fossil fuels and land use GHG emissions raise the average global carbon footprint to 7 ton per person per year.

The Paris Agreement: 20/20 vision

If global emissions continue to increase at 7% per year, as developing nations catch up on the industrialized; then by 2020, when most nations expect to start implementing the Paris agreement, global emissions will be at 65 billion tons a year and global per capita footprints at 8.5t per person. We will have added another 250 billion tons of carbon to the atmosphere pushing the planet towards if not over the long term temperature goal of Article 2:

holding the increase in the global average temperature to well below 2°C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5°C above pre-industrial levels,

Article 4 of the Paris agreement states that “In order to achieve the long-term temperature goal set out in Article 2, Parties aim to reach global peaking of greenhouse gas emissions as soon as possible.” However even if the World went on to reduce it’s net emissions to zero by 2050, it will have added a further 900 billion tons of CO2 to the atmosphere in the process: sufficient to double atmospheric concentrations and cause a mean global temperature rise of 3-6 degrees Celsius by the end of the century. Such a scenario would lead to accelerated melting of the Worlds glaciers and cause a global sea level rise in the tens of metres. It is similarly, based on the evidence to date, the most likely scenario.

To avoid catastrophic climate change the World must significantly reduce the use of fossil fuels with immediate effect. It must develop and deploy, on a grand scale, alternative renewable solutions (wind, solar, water, biomass) and it must actively restore the tropical forests lost since 1990. It must further increase global forest extent by at least another 10% and it must continue to do so for the rest of this century and beyond.

It must do this because it did not act to arrest the problem 30 years ago and if it waits another 30 it will be too late.. Admittedly climate was not on the international agenda but deforestation, habitat loss and species extinction were [Our Common Future 1987]. Despite the warnings of the Bruntland report and the the subsequent 1992 Rio Declaration from Earth Summit I, over a third of global deforestation has occurred during this period and the World is on the brink of the biggest extinction event since the dinosaurs. What to do?

A 75% reduction in fossil fuel use

If we cut our current fossil fuel emissions (38.2 billion tons CO2) to reach a net emissions target of 10 billion tons CO2 by 2030: a global carbon footprint of < 1.5t per capita. This would result in the emission of 200 billion tons of CO2, and we might meet the Paris agreement threshold of 2 degrees C. If we take till 2040 to reach the baseline of 10 billion tons then 350 billion tons of CO2 emissions will result and we will likely miss the 2 degree threshold. Wait till 2050 however and 500 billion tons of CO2 emissions will occur, we will not be able to keep global mean temperate increase below 2 degrees C and in all probability it will have already reached and exceeded that by 2050. We will still need strategies to mitigate the 10 billion tons we produce as a base line as well as the 400 billion historical emissions but the longer we delay, the more difficult and painful it will become.


Deforestation and Agriculture

The EPA estimate that one third of GHG emissions originate from agriculture; 6 billion tons as CO2 (11% GHG emission), whilst methane from livestock production contributes another 16%(UNFAO estimate 14.5%) and Nitrous Oxide from fertilizer use 6%. In total Agriculture contributes the equivalent of 18 billion tons of CO2 per year to GHG emissions.post-paris-co2

The largest single cause of CO2 emissions is tropical forest deforestation. The UNFAO estimates that in the last 27 years 1.29 million km2 of forest, an area equivalent to France, Spain and Portugal combined, has been lost. Much of this forest has been felled to grow soybean, palm oil and beef to supply global markets.

An end to deforestation would thus dramatically reduce the CO2 contribution of Agriculture bringing it down to or even below a billion tons per year. A 50% reduction in the beef and dairy industries would similarly reduce  agricultural GHG emissions by another 8%.

Together with reducing Fossil fuel emissions to 10 billion tons these measures would bring global GHG emissions to under 25 billion tons. We would still be adding to atmospheric concentrations of GHG’s, but at half the rate we are now, so still sufficient to maintain our course towards a climate catastrophe. A catastrophe we cannot avoid until we reduce our net emissions to zero and take steps to recapture and store the 400 billion tons of historical carbon emissions.

Reforestation and Afforestation

To recover the 129 million hectares of forest lost since 1990 in the same number of years would require planting a new forest the size of Switzerland every year for the next thirty. A forest that would, in 100 years, recapture most of the carbon emission from the original deforestation (200 billion tons).

Afforestation, the creation of new forests on agricultural and other land would also capture some of the carbon emissions derived from the burning of fossil fuels during the same period. However as afforestation is not as effective as reforestation a plantation of 260 million hectares, the size of the Kazakhstan, would be requires to capture the same 200 billion tons of CO2.

Over a 100 year period these two forests projects, which collectively would cover an area the size of India and Pakistan, would recapture the 400 billion tons of historical CO2 emissions. world-map

However even with these massive mitigation projects in place, a 75% reduction in fossil fuel emissions and a 50% reduction in methane emissions (an outcome that requires 50% of the World that is not vegetarian to become so) by 2030, the World will still go on to produce 1.5 trillion tons of GHG emissions during the 21st Century.

This is the reality of our 21st Century Global Carbon Footprint.

Climate Catastrophe Time Line

2030…. The World has cut its fossil-fuel emissions by 75% to 10 billion tons a year. Similarly 50% of the World’s meat eaters have become vegetarian and we have stopped all deforestation and bought all commercial forests into zero carbon management: our emissions are down to 20 billion tons a year…

forests-carbon01We will have reforested enough of the tropics to cover Portugal and the Spanish region of Galicia  and similarly planted new forests across the World’s other regions which would collectively cover Germany. However none are established sufficiently to make any significant contribution to mitigation, so the global temperature is still rising and we are, despite these efforts, 50% worse off than when we started: we now have 600 billion tons of carbon in the atmosphere to deal with and are adding another 20 billion every year.



2040…  The tropical forests  have expanded and now cover the plains of Spain whilst the new forests has grown to cover an area encompassing Germany and Poland. The good news is the earlier forests are now capturing carbon: perhaps 10%, so 4 billion tons of the 40 billion they will eventually capture. The bad news is global emissions now top 800 billion tons.



2050… Despite having now reforested the tropics with sufficient wood to cover Portugal and Spain, we are but halfway there, there is still the equivalent of France to plant before we recover what was lost in the last two decades of the 20th century. Similarly the new forests now cover an area that swallows the Czech Republic, Slovenia, Hungary and Austria. As with the tropical forest we are still not there, there is still Belarus, Ukraine and Romania to plant.

If our fossil fuel emissions are still at 10 billion tons a year then another 100 billion tons of CO2 will have been added to the 800 billion already in the atmosphere. If meat eaters are still insisting they would rather eat their bacon than save it, then they will have similarly added another 100 billion tons in the form of methane. On the plus side the first of the forests will likely have captured 25% (10 billion tons) of their carbon potential and the second 10% ( 4 billion tons), so our efforts may have been sufficient to keep the total global carbon emissions from fossil fuel burning and deforestation below the one trillion tons mark but by 2099 another 500 billion tons of GHG’s will have been added to the atmosphere.


 The End of the Fossil Fuel age

However; if  on reaching 2030 the World has achieved a 75% reduction in fossil fuel emissions,  adopts a zero emissions target for the next ten years, and similarly a vegetarian diet, then by 2040 the fossil fuel age will come to an end leaving a 700 billion ton carbon footprint on the atmosphere. As long as the World continues with the reforestation and afforestation programs then by the end of the 21st century this could be down to 400 billion tons.. but then pigs might fly

The Green Data Revolution

sentinel-2aFrom Satellites to Termites…

Flying high above the Earth’s poles are the two satellites of the European Space Agency’s Sentinel-2 program. Part of the Copernicus initiative  they are mapping Africa at 10m, 20m and 60m resolutions so as to  provide data to facilitate the creation of accurate maps for environmental management and to study the effects of climate change.

Root zone, Soil Moisture http://www.esa.int/

For more than 30 years the ESA’s Living Planet Programme (Explorer missions, Earth Watch and Copernicus Sentinel missions) has remotely sensed and created a data archive on the Earth’s  climates, biomes and the processes that operate within them.

Mapping Africa’s Habitats

AfSISThese satellite archives are now being utilized by  The African Soil Information Service (AfSIS)  to describe Africa’s soil and landscape resources. It’s a project that will contribute to the development of sustainable agricultural systems that can feed the populace and co-exist with Africa’s wildlife.

Mapping 30 million km2 of the Earth’s terrestrial surface at a resolution of 250m2 is though a mammoth task that can only succeed with the effort of the crowd. So if you care about the elephants and lions, lend AfSIS your eyes, map a few km of Africa and help to make the World sustainable.  Join the crowd and map Africa’s habitats.

Digitizing the Herbarium 

Sustainable agricultural strategies need to be comprehensive and include details of the plants and animals that inhabit the land. This is particularly so for agricultural where poor crop choices and cultivation techniques can quickly and irreversibly rob the land of it’s soil, and water.  A situation that forces farmers to fell virgin forest and plough up natural grasslands in a repetition of the exercise. Many of the World’s deserts, including the largest, the Sahara, have been significantly expanded by this process of agricultural degradation.

Solanaceae-sourceProjects such as the International Plant Names Index, the World Flora online and the Solanaceae source are in the process of constructing comprehensive botanical databases for the 350,000 plant species that inhabit this planet.

Accessing Crop Data

With less than 100 plant species responsible for over 80% of the World’s raw material and food production, the digitization and access to bibliographic and research data on crops is essential if we are to achieve any semblance of agricultural sustainability. To this ends The ODI (Open Data Institute)  and GODAN (Global Open Data for Agriculture and Nutrition) are both exploring what the challenges are and what the global priorities should be.

A Digital Zoo

nhmThe Natural History Museum are digitizing over 80 million specimens from their avian, entomological ,and botanical collections. Many of these collections include additional physiological and habitat data such as the Hostplants and Caterpillars  and the Host-Parasite databases.

Animal Husbandry 

Just as we cultivate a fraction of the Earth’s plants so we have domesticated fewer than 30 of its animals. The agriculturally significant have though been diversified into many and varied breeds each with it’s own characteristics and habitat requirements. I know of no plans to digitize and make details on the requirements, management, or impact of different livestock breeds and husbandry methods on the environment despite this information existing in abundance.

Crop Pests

plantwiseCABI (Centre for Agriculture and Biosciences International) is the secretariat for GODAN and manages the plantwise project. Through the plantwise project CABI run clinics on pest and disease management and have similarly developed a searchable knowledge bank for pest identification.

Smart Data

Making use of this data and turning into something practical and useful was the remit of smartopendatathe smartopendata project. However both the web site and the final report are littered with unexplained acronyms [wtf?] and composed in a language that could well have been uttered by a Lewis Carroll character: “Hereafter, using this central core, the pilots extended the SmartO penData vocabulary to take into a account their own singularities. ”

That said, a Singularity, as in a technological/ digital singularity, is perhaps the correct adjective and conceptual framework to ‘think’ in when talking about smartdata for Agriculture and the Environment.

Let the Data Make the Decisions?

The Singularity in this sense is not an AI (artificial intelligence) but a singular objective [sustainability], within a single integrated application environment. An application environment that extends beyond basic crop and animal husbandry advice into a fully integrated service that can calculate and allocate water resources, greenhouse gas emissions or the potential for erosion. Services that can be further integrated with economic and socio-political objectives so that land and crop choices are efficiently made to meet market needs without over and under production. The same mechanism could be used to reward/compensate for mitigation strategies in the name of climate change and biodiversity objectives.

A digital singularity doesn’t  have a persona, a corporate or a national identity. With no concept of self it seeks the optimum solution based on the data supplied. The more comprehensive and far reaching that data the better the decisions that can be made using the singularity. A singularities decisions are however only as good as the data supplied; inaccurate, incomplete or misleading data, just as it does in real life, can lead to a catastrophe.

The Need for Education

Supplied with comprehensive and accurate data, a digital singularity can encourage sustainable practices, but for them to be adopted correctly a farmer needs to understand the reasoning behind the action. If global targets for climate change and habitat preservation are to be met then farmers need to be informed of the significance, understand the logic and gain tangible benefit from implementing a given strategy. Strategies that similarly require feedback (data input) from the farmers and that can only be achieved with the informed cooperation of those farmers, many if not most of which are illiterate.


Next Part II