Cant See the Woods for the Trees

Can’t See The Woods For The Trees

If my internet connection is working then I listen, most days, to Radio 4. I start at 5:45am with Farming Today and then stream through until the shipping forecast. So when I awoke on the 7th December I was surprised to hear the program open with fears that England was suffering from deforestation.

The Deforestation of England


The Woodland Trust, and Confor, the confederation of forest industries, a UK trade organisation,  argued that England, which has just “10% forest cover compared to the 38% average for Europe,” is suffering from deforestation. The government, which is committed to planting 11 million trees over the next forty five years, planted only 700 ha of the 5000ha needed to meet that target in 2015. The Woodland Trust, who are themselves planning on planting 64 million trees over the next ten years, argue more needs to be done to protect ancient woodland and hedgerows “which are being lost to roads, quarries and housing”. There is currently no national logging of this loss with the trust relying on a network of volunteers to spot negative impacts at the local planning level. The trust argues that these woodlands and hedgerows need to be buffered, extended and connected to other woodland through gaping and hedgerow maintenance if the government is to meet it’s own targets.

Protecting Forests Through Global Supply Chains


AS I am in Morocco and it is just a bus and a train ride down from the mountains, so not a big load onto my carbon footprint, I made a brief visit to the COP22 in Marrakesh last month. I went primarily to attend the climate law and governance day but I also attended the launch of TRASE ( Transparency for Sustainable Economies) a new online open-access tool that uses publicly available data to unravel supply chains and reveal the origin of commodities such as soybean, beef, palm oil and timber.


One of the ten most important agricultural crops soybean production reached 336 million tons in 2015 making it the 7th most important crop globally. The USA, the largest single producer, was responsible for 118 million tons (35%) whilst South America (Brazil, 102 million tons, Argentina, 57 million tons and Paraguay, 10 million) was responsible for 169 million tons (50%) of global soybean production. With Canada’s contribution (2%) the America’s are responsible for 87% of the Worlds soybean production; much of it however on deforested land. The TRASE platform addresses this through the “use of trade and customs data to identify the producers, traders and transporters involved in the flow of globally-traded commodities” to bring transparency to the global supply chain so that business can identify commodities originating from deforested land.

Palm Oil


The situation is mirrored in Indonesian where deforestation for palm oil production has put the orangutan on the critically endangered list. The clearing, draining and setting alight to the peat of the Indonesian swamp forests in preparation for palm oil plantations in 2015 further led to 100,000 deaths across Asia from the thick belching smoke. Releasing over a billion tons of CO2 in the process and pushing Indonesia into 4th place behind the USA, China and India as the Worlds leading greenhouse gas emitter. [Costing the Earth]

The Starling project, a collaborative venture between The Forest Trust, Airbus, and SarVision uses “high-resolution optical satellite and radar imagery to monitor forest cover in real time” and provide the tools “to enable companies to provide evidence of how they are implementing their No Deforestation Commitments.” As with TRASE the Starling project seeks to provide transparency in global supply chains; supply chains in which just four products, beef, palm oil, timber and soybean are responsible for two thirds of global deforestation . In addition to habitat and species loss the deforestation undertaken to grow these crops is responsible for over 10% of global greenhouse gas emissions.


Another major deforestation crop is Cocoa, produced by just six million smallholders worldwide it is a global crop controlled by less than a dozen companies. In West Africa, the source of 68% of the Worlds chocolate and home to four million cocoa farmers, cocoa is the principal cause of deforestation.

Logging and Land Tenure

Subsistence farmers are blamed for much of the remaining deforestation and whilst they undeniably contribute, in a recent report from the Congo researchers identified logging and land tenure rather than farming as the principle cause of deforestation. Tropical forests are the most diverse ecosystems on planet Earth, they store and clean water, influence the climate and act as large reservoirs for carbon that has accumulated over the lifetime of the forest. When the forest is removed that diversity is lost, the ground dries up and the carbon stored in the forest and it’s soils is released. Over 65% of tropical deforestation and 7% of global carbon emissions now result from the cultivation of less than a dozen crops.

A Carbon Neutral Future From Forests?

Old Forests, be they ancient English woodland, Indonesian swamp forests, or Amazonian rain forest are all bigger carbon sinks than what can be captured in new plantations. It’s likely that for every hectare of old forest felled two hectares or more of new forest are needed to offset the carbon released. New forests that similarly don’t have the diversity or provide the habitat of the ones lost.

In a recent Inside Science program it was claimed that to reach a negative carbon balance; where carbon captured as biomass is used to fuel an energy plant, and the CO2 produced is then captured and stored; would require an area of land 1-2 times the size of India (3-6 million km2) to grow the biomass. The idea is somewhat over complicated and risks turning captured carbon into the climate equivalent of nuclear waste as we struggle to store billions of tons of CO2. If instead that energy was produced by other carbon neutral sources (i.e. solar, wind and water) and the biomass grown as both the carbon capturing and carbon storing device, we would not require a network of silo’s storing ‘dry ice’ or it’s equivalent, but the World would still need to plant a forest the size of India to capture and store the carbon the 20th century has released.

Restoration and Regeneration

Whilst stopping deforestation completely would be the best course of action, restoring recently deforested land would result in capturing more carbon than planting a new forest on agricultural or marginal land. The Amazon has lost 20 %, one million km2, over the last 40 years and whilst it is unlikely that all that loss can be recovered, with strategic planting perhaps 20% of what has been lost could be recaptured. If the same strategy could be applied to West Africa, the Congo and Indonesia; perhaps as much as ½ million km2 of tropical forest could be restored within 50 years. It is though just 10% of what is needed. If Europe were to similarly increase it’s forest cover by 10% then that rises to 20% of what is needed but again will take 50 years to reach fruition.


The UK has 450,000km of hedgerow but ,as a consequence of the plough up policy of 1948, has lost 121,000km.  Gap filling the existing and reducing field sizes to recreate the hedgerows lost could increase the UK’s wood cover by as much as 5%; more than meeting the UK governments target of 2% over the next forty five years.

Whilst deforestation and afforestation are the key issues in Africa, South America and Asia, hedgerow planting could similarly contribute the equivalent of a billion km2 or more of new forests in agricultural regions of the tropics. In many instances planting could encourage diversification with trees and shrubs for the production of fruit and nuts, oilseed for bio-fuel production, biomass for energy or trees for soil remediation and erosion prevention. Such diversification provides commercial value and resilience as well as contributing to climate mitigation.

Monitoring Restoration

Whilst projects such as TRASE and Starling are providing the tools for businesses to identify commodities originating from deforested land or to verify no deforestation commitments, there needs to be additional tools to further monitor and measure restoration and afforestation strategies. If deforestation was to end tomorrow, the World would sill need to create 5 million km2 of new forest and woodland if it is to meet its commitment to prevent global temperatures rising above the 2 degrees C threshold agreed in Paris. It is not enough just to arrest the damage, we must repair it too.

However there are no supply chains, no customs or logistics data to mine to see if a forest or a hedgerow has been replanted or is being maintained. Satellite data, a resource the Starling project has utilized to reveal changes in forest canopy in palm oil production could similarly be utilized to monitor afforestation efforts. An approach that applies as much to reafforestation strategies in the UK as it does to the tropics. However monitoring is only half the story and whilst carbon sequestration and habitat creation are important global functions of trees they are not their sole function. Trees are a commodity, we need the wood but they also perform other crucial functions within the local environment, be it improving flood defences, arresting soil erosion, removing air and noise pollution or just providing beauty and enjoyment; trees are an integral part of the human landscape.

Human Beings and Climate Mitigation Strategies

The first principle of the Rio Declaration was that “human beings are at the centre of concerns for sustainability”. [Earth Summit I, 1992 ]. Keeping human beings at that centre should similarly be the first principal of all future environmental and climate mitigation strategies. The people whose lifestyles need to change need to be involved in that change; for whilst human beings are at the centre, they are also the cause, our environmental and climate crisis is a problem of our our making and it is within our own humanity that the solutions similarly lie.

The world has similarly changed considerable since 1992, there was no remote sensing, the internet had not yet gone ‘viral’ and Glastonbury would have been regarded as the centre of the Gig economy. However somethings have not changed; we have continued to lose habitats at an alarming rate and have bought more species to the brink of extinction over the last twenty four years than since the demise of the dinosaurs. If we continue on this trend for another twenty four years there may well be nothing left to save.

The Satellite’s Eye: Remote Sensing

The Forestry Commission’s Corporate plan for England identified it’s priorities for English Woodland as to “protect, improve and expand”. Seeking to “bring two thirds of all woodland under management by 2018” and to create a total of 2600km2 of new woodland by 2060. The plan further commits to provide “support for mechanisms and payments for ecosystem services” and calls for “more trees and woodlands in and around towns and cities.

In order to meet those targets the commission needs to know the real time state of Woodland across England. As only 57% of England’s woodland is currently sustainably managed and the commission has prioritised bringing only 2/3rd’s under management by 2018, a significant proportion of Woodland will remain without any mechanism to assess threats to it for the foreseeable future. Unprotected it is, as the Woodland Trust identified, “at threat of being lost to roads, quarries and housing” as well as to the disease and climate threats the Forestry Commission prioritise in their plan. With no mechanism in place to record these losses the trust has resorted to relying on a network of volunteers to spot negative impacts at the local planning level. However with the advent of satellite imagery and the internet the ability to log and record existing woodland remotely and to similarly record any impending changes to it now exists.

All land use management strategies, at both the planning and monitoring stages rely on maps. Maps that can be greatly enhanced with the use of satellite imagery. In some instances, as with the Starling project those images are used to identify deforestation and species changes in tropical forests; it is a specific task that can and is performed by machine learning, but in many others, particularly mapping trees in complex environments such as cities and towns, the process still requires human intervention.

Crowd Sourcing The Map: A Place To Plant Your Tree

AfSIS (African Soil Information Service) and their partner QED  have been using satellite imagery to map land use in Africa for the last year. The process relies on volunteers, ‘citizen scientists’ to annotate images to identify buildings, cultivated land and forestry in a 250m2 grid. The same method could be used for England, if not the whole of the UK, to map the current state of woodland and land use in general [Mapping UK Habitats] Done correctly such a map could not only identify existing woodland by when interpolated with other data such as soil maps, hydrological or species distribution could identify where the benefits of planting new woodland and restoration of existing woodland can be best realized. The same map could also be used to monitor the health and, with weather maps, predict the movements of threats to woodland from pests or diseases.

A single map into which all environmental data can be interpolated so as to give a complete and accurate reflection of the state of the environment at any scale and to any stakeholder who needs it. [DFM]

Such a map would be the means to calculate the quantitative and qualitative benefits and cost of a given action to the environment. To build such a map at a working resolution requires a large network of volunteers, the same network that will later be required to monitor and update the map. It may be possible to develop machine learning but in the interim, and to give the machines something to learn from, the map requires human input. That input similarly performs another crucial function; it engages the very people it needs to change.

Citizen scientists have and continue to contribute to many existing mapping projects but in reality relying on volunteers to create and maintain critical environmental maps in order to meet our climate objectives is perhaps a policy that is as likely to succeed as relying on governments to voluntarily abide to environmental agreements. It is doomed to failure for there are not enough volunteers to provide the level of coverage needed to map and then monitor global land use and climate mitigation strategies to the extent required to achieve COP22 objectives.

The Gig Economy: A Tree Hugger’s Paradise?

Paying stakeholders to both maintain and monitor climate mitigation strategies is likely the only viable way of bringing about the level of change and monitoring that is required to meet our climate objectives. If we are to plant a forest the size of India we will need a lot of spades to do so. In this respect the gig economy may well come to the rescue, for we do not have a lot of time in which to raise the number of tree huggers needed to plant all the forests and woodland needed to replace what has been lost. In England an army will be needed to both identify and plant the 13000km2 of land required for the 64 million trees the Woodland trust aim to plant. Five times more ambitious than the Forestry Commission, if successful the Woodland Trust’s plan would double the UK’s woodland cover but it is similarly a plan that will need a radical new approach to be successful.

Carbonizing the Blockchain

The block chain and the concept of smart contracts makes paying a large number of individuals to plant and maintain a framework of new forests possible. It also offers the means, with satellite and drone imagery to make it possible to employ an equally large number of people to analysis and annotate maps to confirm that trees have been planted and carbon is being sequestered. It further offers the potential to automate payments for carbon mitigation efforts. Using smart contracts carbon credits could be earned by farmers and landowners. This could then be verified by employing others to analysis and annotate satellite and drone imagery. Using quantifiable metrics the amount of carbon sequestered could be regularly qualified triggering regular payments depending on the extent and increase in canopy cover. A trickle system that ensures trees and plantations are not only planted but maintained to achieve the environmental and climate objectives. A three point verification system between the farmer, the satellite and the gig economy. Such a mechanism is not limited by scale , an individual planting a single tree in a garden or a landowner planting a 1000 ha stand; each would be paid according to the benefits achieved by their efforts. Nor to just the gig economy for annotating maps is something that could be done by refugees; providing them with both an income and a role in repairing planet Earth. A plan to build such a system was previously proposed to Ethereum and whilst it was well received no developers stepped forward to help build it.

Developing New Technology 

Whilst much of the technology already exists, the satellite images, the software to annotate those images and the smart contracts to pay the cartographers and monitors: new apps for phones that allow for newly planted trees to be quickly recorded and uploaded along with the gps co-ordinates need to be created. Satellite imagery could then be used to confirm the work with human verification or machine learning used to measure the canopy cover and the amount of carbon sequestered estimated. This could be performed over the lifetime of the tree or stand and used to adjust and refine payments to ensure carbon mitigation strategies are maintained.

The use of new technologies such as blockchain, machine learning and remote sensing offer real opportunity to make climate mitigation strategies a reality that works at the local and global scale. The World though has a tough hill to climb, not only must it plant a forest the size of India but it must similarly cease from decimating the existing forests. It must also find a solution to our addiction to fossil fuels, as we to our consumerism, as it is these habits that are the root cause of our environmental and climate woes. There is though no such thing as a free lunch or a technological fix for greed; each and everyone of us needs to reduce our own personal carbon footprint, our own personal consumption of fossil fuels and forest products: for this is not only the most effective way but similarly essential if we are to mitigate climate change and arrest deforestation.

Data Databases Distributed Networks

Random Thoughts on Cargo, Ships and Oceans

(Data, Databases and Distributed Network)


We tend to regard data as if it were a thing with dimensions and boundaries. A product of the information age we live in it travels like the cargo of a ship on the virtual ocean that is the information highway; when in fact the cargo, the ship and the information highway are all data, there is only ocean.

This ocean of data drives society, determines national budgets, aids decisions in industry and pigeon holes us into social and economic groups. From the global to the personal level data plays a significant role in all the decision processes of everyone’s life. Processes that if based on poor inaccurate, out of date or misleading data risk making decisions that are equally poor, misleading and out of date.

So, if we are to make good decisions, we need to know the outcomes, the benefits and consequences of our actions on ourselves, our neighbours and our environment. We need to understand the relationship between the macro and the micro, the local and the global and the only way to do that is through the data.

According to some reports we have generated more data in the last five years than in our entire history and each year we generate more. With this explosion in data comes opportunities for improving our decision processes and achieving global sustainability objectives. However with those opportunities come challenges in handling, differentiating and working out just what is and is not useful. For no data, is better than the wrong data. The right data however, despite what Mark Twain would aver, makes for good statistics and good statistics support good decision processes. But what is the ‘right data’ in an information age awash with the stuff.

What Is Data

The internet is data, everything on it and every piece of software on a computer is made up of Data. However in the context herein data has the more ‘narrow‘ scientific definition of

a set of values or measurements of qualitative or quantitative variables, records or information collected together for reference or analysis,” (Wikipedia)

it is the cargo on our ship…

The contents of a telephone book is an example of data collected for reference. Data that can and is put into databases for analysis. Once entered it can be re-organized and sorted so as to reveal how the names are distributed, measure their frequency and estimate ethnic or social economic distributions. The analysis might reveal odd correlations, trends and anomalies, such as the frequency at which three sixes appear in the telephone numbers of people with double barrel names, that would otherwise be missed. Such anomalies can fuel conspiracies and are examples of statistics being used like a drunk uses a lamp post, more for support than illumination. In truth there is though little one can get from a telephone book other than a telephone number and an address. That’s not to say that data isn’t useful.

Types Of Data

Data categorisation is very much dependent on purpose; there is no single category structure applicable to all. With that in mind I propose four Data spheres to initially distinguish data types.

Personal Data

A telephone book is just one source of personal data, as is a mailing list, a club membership, a bank account or a tax office receipt. Individually these data sources provide limited information about an individual but contain fields (name,address, etc) that make it easy to link the data so that collectively it documents extensive details about an individuals personal and financial life. Scary stuff and whilst it’s the most precious kind of data it similarly makes up an insignificant fraction of the total data currently held or being generated by the internet.

Economic Data

The state of the nation, the productivity of industry and the movement of goods and services within and between trading entities relies on the supply of good data. The budget, government policy and changes to or creation of new laws all rely on good relevant data. Without it there would be no means to balance the books, to calculate a nations GDP and value it’s currency. However data collection currently lags behind the policy that relies on it. At best the figures are for the previous quarter but more often than not are estimates aggregated together from different sources.

Sociopolitical Data

Domestic government policy on health and education as well as changes to and creation of new laws all rely on good data. At the regional level Data determines how policy will be implemented and budgets distributed between schools, policing, refuse collection, etc. National and local government therefore needs quantitative and qualitative data on the demographics, social trends, political, cultural and ethnic identities of the people it serves.

Environmental Data

Environmental data includes any lab, field and desktop data from any chemical, physical or biological discipline from the natural sciences. All data relating to Earth and biological disciplines from theoretical particle physics to the applied science of agriculture are forms of Environmental Data.

Non Exclusive Nature Of Data

Within these spheres data can be quantitative/qualitative, spatial/temporal, deterministic/stochastic or combinations there of. The data may similarly be relevant to a few, many or have a lasting or fleeting influence, and whilst most data conforms to the categories above some straddles more than one and all of it interacts with and influences the data in others. So whilst we can can compartmentalize data we can only understand it in the context of the whole.

What Is A Database

A database is an application (program) into which data can be input and organised to provide an indexing system or display statistical information on the data. A simple data set could be a membership list of a golf club. Each entry containing details on a members name, age, address, joining/subscription date and details of their achievements (i.e. handicap, or records held). The database would allow the club to sort the details by any field (name, age, address, joining date, subscription renewal, handicap, etc) and compile simple statistics (i.e. avg age, length of membership) or see who hadn’t paid their subs. A database might store values, charts, tables, files or just the location of the data as with bit torrent file sharing sites or search engines (i.e. google).

Types Of Database

All databases store information, ideally for easy retrieval. What differentiates one from another is the way the data is stored (within the database itself, or links to an external location), where the database is held (central or distributed), and how the data is subsequently accessed (public or private).

Traditional Database

Whilst limited and not generally regarded as a true database, a spreadsheet performs all the basic functions of one. MySQL the database in the LAMP (Linux Apache MySQL PHP) stack that drives the internet is an example of a more complex database. A MySQL database stores the content and links to a web sites media. This content is accessed though PHP scripts ( i.e. a Content Management System like WordPress) and then served to the internet by an Apache server built using Linux.

Distributed Hash Table (DHT)

A Distributed Hash Table (DHT) is a database that stores only the location(s) of a file along with a hash value (a unique reference that is the sum of the contents of the file). The hash value stored in the database can then be compared with that of the external file in order to qualify the integrity of the external file. A DHT may also hold data on when the file(s) was added, the last time it was accessed and the total number of calls made to the file. A DHT is a mechanism used for indexing and distributing files across a P2P network.


The bitcoin blockchain solves trust issues for cryptocurrency, but burns a lot of fossil fuel in the process. Although the bitcoin blockchain is referred to as a distributed database, it is more a duplicated ledger with every node maintaining an identical copy of the entire database. All nodes compete to balance the ledger by guessing a hash value; a value that can’t be calculated easily and can only by discovered by brute force. Guessed correctly it balances the entire system, and creates a block. That in a nut shell is the proof of work concept that makes the Bitcoin blockchain secure; A very energy hungry solution to solve an integrity issue with Homo sapiens.

A Framework For Sustainability

In the previous post I summarised a recent technical report by the Open Data Institute (ODI) which raised the need for a “blockchain ecosystem to emerge that mirrored the common LAMP 7 web stack” and was “compatible with the Web we have already.”

lamp stack02Reliable and secure the software that underpins the LAMP stack is, it is now nearly 20 years old and has arguably reached its peak. It has similarly evolved to be better at generating data than dealing with it. It’s good at serving files, not dealing with the information in them, so whilst the evolution of a data stack needs to evolve alongside the existing web structure it will likely be an evolution independent of it. One ‘promising’ data stack identified by the ODI team which met this criteria was “Ethereum as an application layer, BigchainDB as a database layer and the Interplanetary File System (IPFS) as a storage layer”.


the data stack04

Application Database Storage (ADS) Network

Unlike the LAMP stack the data ecosystem is more likely to evolve as a weave of intertwined data streams that converge on nodes that use the data. Similarly with the LAMP stack exchanges between nodes occurs at the server level, in an ADS network exchanges of data would occur in all layers, Application, Database and Storage.

The Application Layer

What makes databases powerful are the scripts, applications, programs and content management systems that use it. Scripts that are similarly responsible for entering data and with the rapid growth in smart appliances and the IoT this data inputting is increasingly becoming automated. How useful all that data turns out to ultimately be will depend as much on the applications that can use the data effectively as on the databases that store and organize it. Once data no longer has a processing value it would be archived, an action that would be performed by an application.

data spheres networks02

The Database and Storage Layers

Data with different economic, social and environmental relevance, much of it originating from the application layer, is indexed and organized through the database layer before finding its way into the storage layer. There is to a degree some blurring of the lines between these two layers with the database layer being dynamic whilst the storage layer is more for large files, legacy databases, redundant or archived data.

Blockchain As Metronomes In An ADS Network

The main function of a blockchain is to provide an immutable ledger that can be trusted. It’s a property an ADS network can exploit in order to synchronize databases. In particular supply chain auditing on a blockchain would provide a trusted data source for multiple users in a network. Blockchain being the ideal tool with which to build an authentication and tracking system that shadows produce as it moves from farm to fork (strengthening the food chain with a blockchain)

A Manifest Of Global Agricultural Produce

ads network 01Providing invaluable data to producers, importers, retailers and consumers alike, with an authentication and tracking system on the blockchain the the origin and route produce took to market could be qualified.

Once established a consumer would have access to an audit trail where they would be able to authenticate origin, standards in production or the carbon footprint of food.  Detailing the precise route that the produce took from the field to the shelf would give Importers and Retailers insight into double handling, stalling and wastage on route, whilst National and Supranational bodies would have precise data on the production, origin and consumption of agricultural produce. If data be the cargo in an ADS network, supply chain authentication and tracking system is the ship that carries that data.


Sowing The Seeds For Integrated Crop Production And Management Systems

With an authentication and tracking system in place a farmer would be able track in real time how much produce left the farm and reached the intended market. He would be able to see this relative to his neighbour, relative to acreage of a given crop in a region and relative to all the routes that crop took to market. Without having to communicate all farmers in a publicly accessible authentication and tracking system would be exchanging data that would help all of them plan and co-ordinate crop choices and market logistics.

It is a small step for that hub to widen, to encourage integrated crop production and management in farms across a region and improved logistics to tackle over and under production and transport wastage. One more step and farmers could begin to operate in their own regional network not only to produce and supply food but to create co-operatives to allocate resources more amicable or developing integrated fertility programs. My experiment with IRCC Cameroon was an attempt to remotely put such a structure in place.

Supporting The Development Of A Peer To Peer Economy

As well as farmers retailers and consumers could build co-operatives around a supply chain. Orders could be automatically coordinated through logistics operators to find the optimum route, and then tracked to the delivery address. On arrival the order could trigger payment or payments. It’s a future that relies on the establishment of an authentication and tracking system as well as the market places to promote and display the wares.

A good example of a blockchain authentication and tracking system is Deloitte’s ArtTracktive blockchain. Launched in May of this year to “prove the provenance and movements of artwork” the same technology, despite the huge difference in value of the goods, could be used to authenticate and track a hand of bananas from the Caribbean to the corner shop as easily as it can track a basket of fruit from Caravaggio to the Biblioteca Ambrosiana in Milan.

Widening the tracking remit are the London based startups  Blockverify and Provenance. A blockchain initiative on the Ethereum platform Provenance currently provides authentication and traceability of bespoke goods . They are similarly actively exploring retail supply chain tracking.  Blockverify similarly claim to be able to provide blockchain authentication to the pharmaceutical, luxury goods, diamonds and electronics industries.

Cropster, a company who create software solutions for the speciality coffee industry, similarly provides provenance to coffee producers so they can “instantly connect to a centralized market where thousands of roasters are actively looking.” Provenance which could be enhanced further by an authentication and tracking system that follows the beans entire journey from plantation to cup.

Undermining The Dark Web

Openbazaar, a peer to peer market place, now integrated with IPFS, is a decentralized Amazon/Ebay that charges no fees and uses an escrow system with Bitcoin for payments. Although Openbazaar discourages illicit trade, being a P2P network makes policing that policy difficult. Escrow brings in a new layer of authentication, a layer that would be enhanced and strengthened by an authentication and tracking system.

A decentralised market place using Bitcoin and supply chain tracking on a blockchain would represent the first completely decentralized market place to be created on the web. Whilst not completely ending the Dark Web an authentication and tracking system would address many of the anonymity issues P2P networks and cryptocurrency create by authenticating sender, delivery and recipient. Potentially a mechanism that is better suited to assisting the development of wholesale markets than a P2P reinvention of Yahoo Auctions.

Blockchains and global data infrastructure


Applying blockchain technology in global data infrastructure report by the ODI


Disclaimer: This 800 word summary of the 8000 word ODI document Applying blockchain technology in global data infrastructure was created to provide an overview and some commentary on what this author believes to be the most significant points in the report. It is the personal view of the author shared here for those too lazy to read the whole document and come to their own informed opinion.


Most Promising Applications

The report identifies that Bitcoin and cryptocurrency applications dominate the blockchain space and advise against “being swept up by ‘blockchain hype’ and to remember to focus on solid user needs……Whilst there are promising applications, a great many of the ideas out there are ‘vapourware’, with no viable implementation or model. There are also many instances of old ideas that failed for good reasons and the addition of a blockchain will not change those reasons.

Concentrating on “non-financial use cases” the authors identified four promising application areas for blockchain technology:

1. Document and intellectual property verification,
2. Monitoring supply chains (prev post: strengthening the food chain)
3. Building a peer-to-peer economy
4. Governance

Principal Draw Backs

They also note that in “an append-only system” data, once added to a blockchain, can never be removed. This as the authors highlight has consequences for privacy and scale. However the indelibility of the data, the fact that it is permanent and cannot be altered is equally one of if not the main selling point of the concept.

The authors argue that there are “drivers for having a few blockchains maintained by a large number of nodes, and drivers for having many blockchains maintained by a small number of nodes. It is likely it will end up somewhere in the middle.

btc minorHowever based on the examples of Bitcoin and Ethereum, there is currently only one driver. Nodes are maintained by mining rigs specifically employed to generate reward for creating blocks. A situation that has spawned voracious mining pools that gobble up huge amounts of energy in the process. If and when mining ceases or the energy costs exceed the value of the reward, the nodes will stop maintaining the blockchain. So there must be other benefits to encourage the nodes to continue.

More Paper Clips!

Similarly a Blockchain that stores a lot of data for multiple applications will also store a lot of data that is irrelevant to most nodes. Irrelevant data that will cause the blockchain to bloat in size and raise the difficulty. Nodes will just use up large amounts of computational power to maintain a blockchain that is, from their perspective, full of ‘irrelevant’ data. Both the mining reward and the one chain for everything model are thus flawed. One encouraging nodes composed of server banks fed by a pool of specialist mining rigs, the other populated with nodes hashing out blocks filled with data they (and possibly no one else) has any use for. Both behemoths churning out nonsense and relying on the energy output of a medium sized country in order to do so.

Reward systems as do blockchains that carry too much data for too many applications just encourage higher levels of difficulty in hashing blocks to be reached sooner rather than later. The immutability of blockchain data is in this respect both it’s purpose and it’s obstacle, it is forever doomed to trip over it’s own shoe laces. Thus a suite of smaller specialized blockchains that rely on providing cost efficient services to the nodes that maintain them can thrive as long as those services remain cost effective. If they are not the nodes will simply discard the blockchain in favour of and without impact on ones that are.

Waiting on Superman

Much of this promise however relies on, as the authors point out, “a technology stack that has not yet fully emerged”. As the field evolves the authors anticipate a common technology stack, one similar to the LAMP web stack will similarly evolve. The authors also posed the following questions with respect to data compatibility.

  1. How do we standardise storage in systems so that we get a single network of data, as opposed to having to use a different storage system every time we want a new type of information?
  2. What are the data protocols for distributed storage?
  3. How do we talk about, and perhaps enforce, ownership and licensing?

It’s Life Jim…


The authors conclude that distributed ledgers are “potentially important for enabling a shared data infrastructure” that could see “Blockchains used to build confidence in [private and] government services.” There was similarly “great potential for blockchains in collaborative maintenance of data for applications such as supply-chain information”. Smart contracts were also seen as having promise, however the authors “uncovered many cases that were little more than attempts to bolt failed ideas onto the technology or reinvent things that work perfectly well” without blockchain technology.

Perhaps when it’s all said and done, there is only so much one can do with a ledger, distributed or not…

Strengthening The Food Chain with Blockchain

Strengthening The Food Chain with a Blockchain
A publicly accessible authentication and tracking system

Produce Authenticity Log [PAL]

The blockchain in this scenario is used as a simple global tracking system to facilitate the logistics and authentication of global produce. It is not an alternative to existing logistics and supply chain mechanisms, nor is it a smart contract or payment system; but a ledger in which the produce is the unit of currency and the Blockchain the means to authenticate the origin and destination of the produce. In particular it would set out to achieve the following goals:

  • Authenticate and track the distribution of agricultural produce across the globe in real time.
  • Provide a secure, robust and publicly available record authenticating the origin, method of production and subsequent route from farm gate to shop shelf.
  • Provide a mechanism to prevent mislabelling of foods as organic, fair traded or originating from a country other than stated.
  • Facilitate the management of import licenses and the issuing of standards and certificates.

The Concept of PAL

A PAL is created by a node running the blockchain [and placed in a parent wallet]
An amount to reflect the value (qty) of the produce is allocated to a portion of the PAL.
This portion is moved into a consignment wallet.

The PAL is then ‘called’ by the wallets in the Supply and Retail chains.
Every movement of the PAL being called (initiated) by the recipient rather than the sender as the produce moves along the supply chain. The end customer will then be able to use the PAL to authenticate produce origin and transport history.

foodchain PALOnce created a portion of the PAL, equivalent to the produce volume, is sent to a ‘consignment wallet’ with any unused portion of the PAL remaining in the parent wallet. The portion of the PAL now in the consignment wallet can be transferred out by trusted wallets in the supply chain. This is repeated as the PAL follows the produce along the supply chain. If the produce is split and sent along different supply routes the PAL too can be split to follow the destination of everything that left the farm gate.

The PAL is ‘called’ by the recipient wallets in the Supply and Retail chains rather than sent by the Consignment wallet as both an anti-spam measure and a mechanism to aid the fluid ‘unhindered’ distribution of produce.

Benefits of PAL

Data linked to producer/regulatory organisations, supply and retailer chains to provide:

  • Full audit trail of produce to authenticate it’s origin and production standards.
  • Transnational, cross operator tracking independent of all the operators who use it.
  • Global statistics on food production and consumption.
  • Identify points of failure, such as unnecessary delay or excessive wastage/losses.
  • Log precise time goods transfer occurred.
  • Help source origin and routes of a pest or disease outbreak. (*including human pandemics, i.e ebola)

Malicious attack

A node could create fake logs with the intention of spamming the system, however it would need access to a supply chain of trusted wallets to call the log. Without such a route any PAL created would remain in the parent wallet of the node. A rogue node could still set about producing millions of PAL’s, potentially threatening scalability and operability. A limit in the rate at which a node could produce a PAL to one every 5 seconds would limit a node to 6.5 million PAL creations in a year: A year in which the node would need to be maintaining the blockchain; consume energy and securing the network in the process, in order to produce a six million innocuous entries.

No smart contracts

A smart contract is an executable command that is triggered by conditions in the blockchain being met… it may trigger a payment or some other action following an event or set of events occurring in the block chain. In more common parlance this would be referred to as ‘automatic’ rather than a smart payment or action. However smart contracts are inflexible they do not allow for changing plans and being hard coded run the risk of becoming recursive monsters, triggering actions and payments, long after the relevant entities have expired. Once written into the blockchain it is impossible to change the action of a smart contract without having to change the entire ledger. This does not preclude executable commands (smart contract) working with blockchains but the two can (and likely should) be distinct entities with the blockchain providing the authentication mechanism for an application to read and then execute a command.