I only have a few memories of my great-grandfather, Horace Barker. He was one of only three people I met whom I know to have been born in the 19th Century and he died a few weeks before my 5th birthday so we didn’t have a lot of time to get to know each other.
There are only a few facts about him I can recall: he was a kindly old man in his late seventies, married to my great-grandmother, Hilda. They lived in a bungalow with an immaculate garden and a greenhouse full of the sweetest tomatoes you’ve ever smelled. Unfortunately, my own insight ends there and I have to rely on other data sources to complete my picture of him.
If you know where to look, you can find out more about him. Various census sheets and official documents confirm that Horace was born in Pemberton, Wigan on 29th October 1897, he was a coal-miner, man and boy. He married Hilda in 1921 and together, they had a daughter, Marjorie, on 21st March 1924. He went to seek his fortune in Canada for a few months in 1929 but while he was there, Wall Street crashed – which may have influenced his decision to return home. At the outbreak of war in September 1939, Horace was recorded in the National Register as living at ‘Marus Bridge Shop’ and working as a “Colliery…Chargehand” (under-supervisor) and also a first-aider and an Air Raid Patrol warden. His wife Hilda was listed as a ‘Grocer and Confectioner’.
He was hardened by his experiences at the unforgiving coalface and later, as Colliery Manager, he bore the responsibility of the lives of the men who worked under him. The daily obligation to make life-or-death decisions undoubtedly shaped his outlook – and it’s no surprise to reflect that coal-mining was a formative part of some of the most revered working-class heroes of his generation; men like Matt Busby and Bill Shankly.
It’s not a fatuous comparison. Pop’ (as he was known in later life) once told his grandson – my Dad – during a callow attempt to make ambitious structural changes to a farm building “tha’ll ne’er do it” [You’ll never do it], knowing well that saying so would provide the extra determination to succeed. It worked. Like Shankly and Busby, he was what footballers would call a ‘psychologist’: adept at understanding and motivating others with a mixture of high standards and a gruff, uncompromising demeanour. By all accounts, he was a formidable character – and it’s easy to see why he needed to be.
Today, more than half a lifetime after his death, the world is a vastly different place. Fossil fuels – and their effects – are (literally) unsustainable and we’ve made great strides to power out future by harnessing the natural resources around us. That which we used to have to mine out of the ground to add value to our lives is necessarily diminishing in long-term value. And yet, over the same five decades, humanity has also created something in such a vast quantity that it now forms the most valuable mined resource than anything based in carbon.
Since 2017, it’s become widely accepted that data has become the world’s most valuable commodity, overtaking that long-standing former favourite, oil. The world’s most valuable companies now trade in quadrillions of bits, rather than billions of barrels. Carbon is just so finite, so boringly elusive, so…analogue. Data is different: it’s so dynamic, so ubiquitous, so…sustainable. And, just as with coal, the very juiciest bits of all this data, that inform decisions which can make or break fortunes, are there to be mined from the vastly more voluminous, less valuable stuff, all around it.
To do that, you need to be able to find relevant data, verify its accuracy and understand its meaning. For this you must also have a clear understanding of the problem that the data is being used to solve. You must also be aware of the statistical pitfalls of sticking different data together and making logical conclusions that clearly show that the correlations in the data unambiguously answer the questions being posed. To those who are not familiar with it, data mining may seem like a very indistinct process, maybe even a pseudoscience. But it’s simply a case of trying to create a ‘picture’ of knowledge about a group or an individual, based on available facts, cross-tabulated with other known information, to build a profile. If that still sounds unhelpfully abstract, then re-read the first five paragraphs above and you’ll see that’s exactly what I was doing there; turning documented fact into reasoned propensity.
Obviously, data-mining is not remotely dangerous; the work is not back-breaking work and there’s little chance of contracting long-term health conditions due to the working environment but it’s essentially the same principle – although I’m not sure that miners of old would see it that way. In ‘The Road To Wigan Pier’, George Orwell describes at length the awesome physicality demanded of coal miners, even comparing them to Olympic athletes. Pop once said of his own brother-in-law (whom he considered to be a less capable individual) “I’d durst let him’t strike at mi arse wi’ a pick”. If you cut through the old Lancashire dialect and the, er, slightly industrial language, it was a scathing put-down: ‘I’d dare to him to swing a pick-axe at my backside’ – believing him be too weak to do any harm.
We still have his miner’s lamp, although the reason for its presentation (long-service, retirement or just his actual working lamp, polished up) is now lost in the mists of time. There’s also a brilliantly evocative picture of him, arms folded, his coal-blackened face staring defiantly into the camera, taken at the pit-head – I believe at Chisnall Hall Colliery near Coppull. He died in 1978, before the final decline of the industry that sustained his whole life.
I often wonder what he would have made of the miners’ strike of the 1980s, of Arthur Scargill’s leadership of the National Union of Mineworkers, of Health & Safety law, of the demise of ‘Old King Coal’ and even of the shift to renewable energy.
More than anything, I’d love to explain to him the parallels between his industry and mine: the intricacies of data, profiling and algorithms. With the arrogance of (relative) youth, I might expect the ‘wonders’ of the digital age to blow his Victorian mind. I’d tell him how confidently I could pinpoint the addresses of all the greenhouse-owning pensioners in Standish, based on a few data sources and the internet. I’d like to think he’d tell me I’d “ne’er do it”.
But then I shouldn’t be surprised if it left him largely unimpressed – a lot of statistical inference could easily be termed ‘common sense’. If you’ve had any experience of retail, as he did, you soon develop a sense of what ‘type’ each customer is, based on their buying history and their responses to different stimuli. Grocers in 1939 didn’t need a suite of linked tables to understand which customers would be best suited to which products; their database was in their heads. Computers have merely added the capability to make the same predictions on a far greater scale and with ever-increasing complexity.
Nor would he necessarily be a stranger to the more contemporary concerns of wholesale data collation. As a coal miner in Wigan in the 1930s, he is likely to have been well aware of the famous Orwell book about his hometown. If he were to have discussed Orwell’s most famous novel, ‘Nineteen Eighty-Four’, just over a decade later, he would have become well-acquainted with that age’s most prescient description of data use and misuse – and a delicious historical irony would have followed. I remember the death of the aforementioned ‘pick axe’ brother-in-law in December 1983. At his memorial service, in the days after Christmas, the sermon made reference to the incoming new year (1984) and the parallels in the book of the same name that we should consider. Two or three weeks before Apple Computers famously did it, a vicar in Wigan was riffing on the warnings of the coming year.
There’ll always be a limit to what I can know about Horace Barker, and what I can reliably surmise, There are many closed-off avenues that, tantalisingly, could be re-opened with the provision of just a little more data. That’s the frustration of genealogy – the suspicion that one small discovery may set off a chain reaction of greater understanding. Exactly the same can be said of data mining – which makes the quest for the knowledge it can provide all the more enticing.