This is an album released last year, but which I didn’t write about on this blog. So here’s a belated bit about it.

Like much of my recent work, A FIDS MONITOR is based on sonification of data. This is economic and geophysical data that measure the state of the world: time-series datasets of global temperature, greenhouse gases, polar ice extent, bitcoin and the UK economy. Using Mathematica I transformed the data into MIDI files, applying various mappings between the numeric values and MIDI note pitch, volume and timing. These were often basic mappings, where greater values map to louder volume and/or higher pitch.

In generative music, the mapping or translation between data and sound is arbitrary in the sense that there’s not one particular setup that is ‘correct’ or ‘truthful’. But the choice of mapping determines which features of the data are audible and how they are heard, e.g. its structure, its range of values and its rate of change. This makes it an aesthetic relationship as well as generative (computational/procedural/productive/creative). These particular datasets don’t have a naturally musical structure, so it’s a challenge to make something musical with it, but I like to work this way, using constraints as a creative spur. It’s an approach I’ve grown into, mostly by not being able to afford much gear, partly through evolving taste/style, and it’s been developed by participating in the Disquiet Junto which sets a weekly task to make music under specific guidelines. In this case, the rules were:

  • use the whole of each dataset at least once
  • apply simple mappings to the data, and make simple MIDI files
  • use few instruments
  • make each track sound different
  • make sounds only from the data; no external sound sources

I arranged the MIDI files in Reaper. Most of the sounds are made with Razor – the VSTi synth designed by Errorsmith and Native Instruments, XILS3 – a VCS3 emulator, and Sforzando sample player with the Fluid R3 General MIDI sound font. Using Reaper’s parameter routing capability, I set up connections between the MIDI data and the synths so they interacted and created more variety within the constraints of the simple MIDI input. In this way, as processes become non-linear, the sounds become more complex.

Making the tracks just seemed to flow for once, and I didn’t tinker endlessly with each one. I’m quite pleased with how it turned out. Below are some details about the music and the data, with some charts to show the structure of the datasets. I hope it adds to the listening experience.

Global Surface Temperature

Met Office Hadley Centre. HadCRUT4 (anomaly w.r.t. 1961–1990 mean). 1850–2017. Monthly. °C. http://www.metoffice.gov.uk/hadobs/hadcrut4/data/current/download.html

NASA. GISS Surface Temperature Analysis (GISTEMP – deviation from 1951–1980 mean): Combined Land-Surface Air and Sea-Surface Water Temperature Anomalies (Land-Ocean Temperature Index, LOTI). 1880–2017. Monthly. °C. https://data.giss.nasa.gov/gistemp/

These two datasets represent global warming. Track 1 uses monthly readings and starts from 1880, when NASA started measuring, so both datasets are present throughout. The GISTEMP dataset is played with sample-based percussion and HAadCRUT4 with a synthesized pitched sound. The increase in temperature over time is only really audible in the synth that rises in pitch. Track 2 is similar but uses annual averages instead of monthly, so there’s fewer data points / musical events. Track 3 uses the whole of both datasets, so you first hear the HadCRUT dataset before GISTEMP joins in. Track 4 uses only the Met Office data.

UK Deficit

ONS. Public sector current budget deficit, excluding public sector banks. 1946–2016. Quarterly. £ million. https://www.ons.gov.uk/economy/governmentpublicsectorandtaxes/publicsectorfinance/timeseries/jw2t/pusf

The deficit is the difference between money raised and spent by the government. Track 5 is made with two copies of a MIDI file played in sync. One plays a synth bass and the other General MIDI percussion. The sonification works well here, highlighting the annual cycle in the quarterly data from the 1940s to the 1960s, where one quarter with a small surplus at the start of each new budget is followed by three quarters with a small deficit. Then it becomes more unstable and the government accounts go further into the red.

UK Balance of Payments

ONS. BoP Current Account Balance SA. 1955–2016. Quarterly. £ million.  https://www.ons.gov.uk/economy/nationalaccounts/balanceofpayments/timeseries/hbop/pnbp

ONS. BoP: Capital Account Balance CP SA. £m. 1955–2016. Quarterly. £ million.  https://www.ons.gov.uk/economy/nationalaccounts/balanceofpayments/timeseries/fnvq/pnbp

The balance of payments measures the inward and outward transactions of the residents of a country (in this case, the UK) and the rest of the world. The current account is the national net income – how much money the country has. The capital account balance consists of capital transfers and trading of land and natural resources. Added together, they show whether a country is a lender (in surplus) or borrower (in deficit) to the rest of the world. Track 6 interleaves the datasets, with the capital account data (bass sound) half a beat behind the current account data (drum sound, a modified version of Errorsmith’s excellent ‘Kick to Tom’ preset in Razor).

UK Employment & Unemployment

ONS. Employment rate (aged 16 to 64, seasonally adjusted). 1971–2016. %. https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/employmentandemployeetypes/timeseries/lf24/lms

ONS. Unemployment rate (aged 16 and over, seasonally adjusted). 1971–2016. %.  https://www.ons.gov.uk/employmentandlabourmarket/peoplenotinwork/unemployment/timeseries/mgsx/lms

These measures of employment and unemployment rates are inversely correlated but do not quite sum to 100% because they represent different definitions of employment and different age groups. Track 7 plays both datasets in parallel using bass and drum sounds.


Blockchain. Market Capitalization (The total USD value of bitcoin supply in circulation). 15/04/2016–14/04/2017. Daily. USD. https://blockchain.info/charts/market-cap

Blockchain. Average Block Size (The average block size in MB). 15/04/2016–14/04/2017. Daily. MB. https://blockchain.info/charts/avg-block-size

Blockchain. Transaction Rate (The number of Bitcoin transactions added to the memepool per second). 15/04/2016–14/04/2017. Daily. Transactions added per second. https://blockchain.info/charts/transactions-per-second

All three datasets are used in each of tracks 8, 9 and 10, but each uses different instruments and different parameter modulation setups.

Sea Ice

National Snow and Ice Data Center. Arctic sea ice extent and area. 1979-2016. Monthly.  ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/north/monthly/data/

National Snow and Ice Data Center. Antarctic sea ice extent and area. 1979–2016. Monthly.  ftp://sidads.colorado.edu/DATASETS/NOAA/G02135/south/monthly/data/

This polar ice extent data shows the annual cycle of increase and decrease, and how the polar cycles are 180° out of phase with each other. It also shows how much the northern ice caps are melting. Tracks 11, 12 and 13 all use both datasets. Each track uses different sounds, but within them both MIDI files use the same sound. In each track the north can be heard on the left and south on the right. The image at the top of this post is based on the difference in northern ice extent from the monthly average.

Greenhouse Gases

NOAA. CO2 air samples collected in glass flasks, Ascension Islands station. 1979–2015. Monthly. ppm. ftp://aftp.cmdl.noaa.gov/data/greenhouse_gases/co2/flask/surface/co2_asc_surface-flask_1_ccgg_month.txt

NOAA. CH4 air samples collected in glass flasks, Ascension Islands station. 1983–2015. Monthly. ppb. ftp://aftp.cmdl.noaa.gov/data/trace_gases/ch4/flask/surface/ch4_asc_surface-flask_1_ccgg_month.txt

These are measurements of the two main greenhouse gases, carbon dioxide (CO2) and methane (CH4). The datasets include the time of day at which the readings were taken. I used this in the music to set note duration. You can hear this in the irregular timings of the kick drum in track 14, which uses just a 3-year span of data. The data clearly includes anomalous readings – the visible outliers on the charts. I included these anomalies in the translation into MIDI files. You can hear them clearly in track 15, which only uses the CH4 data, and where the timing is also based on the same method as before. Track 16 uses both datasets in full, with the same anomalies and the same mapping/timing method. In this, the longest and final track, the rising CO2 levels are audible in the rising pitch of the synth sound.


I recommend Philip Sherburne’s recent article, ‘How Experimental Musicians Are Soundtracking the End of the World‘, featuring Matmos, Hildur Guðnadóttir, AGF and Tanya Tagaq.

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Yemen Data Project

I’ve got a new EP out today on the New York Haunted label. It’s based on sonification of data on air strikes in the Yemen war. The data is from Yemen Data Project, an organisation that collates, analyses and shares information about the long-running civil war between government and Houthi forces. In the absence of official records, the project team collects data on political violence and on the air raids conducted by the military coalition led by Saudi Arabia and the United Arab Emirates and backed by the US and the UK. I used the latter dataset, covering the period from 26/03/2015 to 15/12/2017. You can download the latest datasets here: https://yemendataproject.org/data.html Any money I make from this EP will be donated to the Yemen Data Project.

I used pivot tables in Excel to transform data on the variable Main Target Category in combination with date and time. The categories are: civilian, cultural/heritage, economic/infrastructure, educational facility, infrastructure, international community, media, medical facility, military security target, political/tribal and unknown. Using Mathematica, I re-scaled these lists, mapped the data to notes, and outputted as MIDI files. I arranged the MIDI in Reaper and played them through Razor synth. In each track, just over 2 years of data is represented in around 2 minutes of music. Different categories of target can be heard as different sounds. The simple mapping of data to music means that the louder it is, the more air strikes are represented.

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PARSA – uvuvu

The latest album by PARSA makes for some nice spectrograms. PARSA has previously made music with cellular automata (CODE147) and has recently collaborated with Ramtin Niazi (CLEANBOUNCE VARIATIONS) and with Beckton Alps2 as PARSALPS (Reductions). Here are some of spectrograms of uvuvu and a discussion we had about the music.

1 didone256hanning2

[Me:] First of all, how did you make this album? The track titles include references to sampling window functions, including the names and sizes of different types of window (‘hanning’, ‘blackman’; 64, 128, 256). Do the titles relate to the way that the tracks were made?
Window functions happen to be the basis of spectrograms. The window size determines whether the accuracy and resolution of the image is concentrated more towards time (with a short window) or frequency (with a long window). The different window types produce different kinds of analysis errors / visual artifacts. This is what makes the visible false frequency bands that run parallel to the actual frequency, like ripples or echoes. In the spectrograms of your uvuvu tracks, it makes some really nice patterns.

2 qqqq3_64hanning16

[PARSA:] The album is comprised of recordings I’d made while prototyping a sequencer in Unity. uvuvu was actually its working title. I would have it send MIDI off to Ableton Operator, or a Nord Drum 2 or a desktop Blofeld. The result of this endeavor was a sluggish sequencer, the realization that I was actually better off coding my ideas instead of dragging patch cables around with a mouse, and hours of recorded material which I abandoned for a year or two. I later on started using Cecilia5, and reached for this big pile of audio as the basic material. The source material is that, and all later processing was done in Cecilia, using the Vectral module. So each track title is: {source-file}{FFT-Size}{FFT-Envelope}{FFT-Overlaps}. Describing the settings of the module. Intentionally named so, so I could return and tweak things, because there were too many files. I did not know much about sampling window functions at the time, and I intentionally refrained from looking them up.

I do programming for a living and a big part of that to me is to know the ins and outs of what I’m working with. But when working on my own stuff, I need to NOT know something about what I’m working with, otherwise I’ll move on. Maybe that’s why everything I’ve released so far doesn’t sound polished, or complete or whatever. I record the process, not the product. So these settings were chosen just because I liked their effects on certain source material!

I recently dug up uvuvu in preparation for a talk I did at Tom Mudd’s class at the University of Edinburgh.

“4 chimes256hanning2 or my attempt at learning about Markov chains”

“8 mainline_rework. This was around the time that uvuvu worked offline and exported MIDI files”

Looking at these, I would do a lot of things differently if I wanted to start writing this thing now. This project failed pretty bad!

3 0015064hanning8

[Me:] Right, so the track titles relate directly to the parameters of a FFT vocoder. It’s definitely useful to use file names like that when experimenting, to keep track of things. It’s interesting that you’ve worked with Tom Mudd – I like his synthesis work. Do you often do that kind of talk, or get involved with teaching?

I think I know what you mean about not quite knowing what you’re working on. I’m also interested in the process as much, if not more than, the product. One idea that’s been useful for my own work is Philip Galanter’s definition of generative art (http://philipgalanter.com/downloads/ga2003_what_is_genart.pdf). Its defining element is that the artist gives away some amount of creative control over to a generative system. It is this element that often makes generative art unpredictable from the artist’s point of view when making it (usually only within certain carefully specified parameters) and that’s often part of the reason for using generative systems. The system could be a set of rules to follow, a physical mechanism, or code executed on a computer, but in all cases what makes it a generative system is that it does some of the creative work that would otherwise be done by the artist. In your work on this album, would it qualify as generative in terms of this particular definition?

Why do say it failed, and what would you do differently now?

4 chimes256hanning2

[PARSA:] I enjoy Tom’s music. He’s doing some crazy stuff with cool tech, can’t wait to hear more. We live in the same city and meet once in a while and talk about what we’re working on. He was kind enough to get me to talk about my approach in his class. I don’t have any real teaching experience, or formal education for that matter. Preparing for it however helped me realize a lot of things about my own work. Its title was “Zen an the Art of Making Mistakes”, actually (I know…). So I guess it’s a bridge to the next topic.

All the tracks are definitely generative. All produced by tiny systems with Markov chains + feedback as their prominent features, in this instance. I surely prefer listening to music over creating music, so generative systems that run with little interference from my end are perfect for me. Maybe what I’m trying to do is not so different from what a photographer or documentary maker does. I just show up and decide what to record. But I’m not sure about actual unpredictability in my work. Particularly when parameters can be/are (carefully) specified, in a digital environment. For instance: https://www.roulettephysics.com/russian-hackers-find-a-way-to-beat-rng-slots/ So, maybe it has to do with scope, or the magnitude of change? No idea! I’m not smart: I still have to look up simple sorting algorithms after 10 years of programming, or use a calculator for simple multiplications. But that’s why I’ve chosen to work this way. Because every mistake I make seems like a suggestion made not by “me”, and I could use a lot of that. If I were to rely on what I know, I’d do very little.

The software failed because it was providing a solution to a non-existent problem. I realized I didn’t need to create a generic tool at all. I was creating an environment in Unity that allowed me to build systems by putting together buildings blocks I’d have to write.
Which is to say, I was using the building blocks of a programming language (system) to create another system that would enable me to do so. So it was a sub-language defined on a sub-language that was built on top of another couple of languages. Much like how we go about making other things nowadays. :) That level of abstraction was completely unnecessary, so the current version is only a few hundred lines of C code that supports live-coding by hot-reloading libraries.

5 bev128blackman4_8

[Me:] Good stuff. Thanks for your responses – it’s been very interesting.

uvuvu is available via Bandcamp:

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Harmonic Series

Harmonic Series is a set of tracks I made in 2012 by generating pure sine waves at harmonic frequencies and arranging them in various sequential patterns. The sine waves were generated by writing some code in Mathematica, creating sets of tones with different harmonic ratios and amplitude envelopes, and the resulting files were sequenced in Reaper. At the time there was a web app that created polar coordinate spectrograms of music you uploaded to it (I forget what it’s called, and can’t find it now), with which I made some images of these tracks – these are on the album artwork. Below are some recent spectrograms of the same tracks made with Sonic Visualiser, using a setting that more accurately identifies frequencies, which are visualised as thin lines of colour instead of wide bands. Click images to enlarge – they look best at 100% or bigger.

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Sharpening M87

This is what happens when sharpening is applied repeatedly to the image of the black hole at the centre of M87 galaxy created by scientists with the Event Horizon Telescope. The first 3 images are sharpened 10×, 20×, and 100×.

These two images show the same detail at 10× and 100× sharpening, showing how the edges grow and layers accrete:

These shapes grow from tiny, faint shapes in the background (stars?), very much like 2D cellular automata do:

One of the brighter spots:


What was the dark centre of the black hole. It seems that over time the patterns stabilise after growing, while the colours continue to shift a bit longer.


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Viridis Spectrograms

Viridis is a colour scale designed to meaningfully represent quantitative data and to be perceived clearly by everybody including those with colour blindness. It provides a perceptually uniform scale in both colour and greyscale. Using a viridis colour palette generator, I applied the palette to the spectrogram visualiser in my music player, Foobar2000. It seems to work well. It makes a nice change from  rainbow colours but still has a wide range of hues, picking out features in the images. Each image shows 30–35 seconds.

Delia Derbyshire – Music of the Spheres

Bach (E. Powers Biggs) – Toccata and Fugue in D minor, BWV 565: a. Toccata

Meshuggah – Swarm

Mark Fell – Manitutshu… First Algorithm Test

Russell Haswell – PANTHER nO!se

NYZ – MirageA

NYZ – FM60Pcelltwonky


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This is the planet Earth, our planet. It is a small planet wrapped in clouds, but to us it is a very important place. It is home.

the extinction symbolGlobal warming is currently around 1°C. That’s on average; in some places it’s much higher. In the Arctic, for example, it’s more than 3 degrees. The 2016 Paris Agreement aim is to limit the increase in the global average temperature this century to well below 2°C above pre-industrial levels and to “pursue efforts” to limit it to 1.5°C. These targets represent the idea of a ‘tipping point’ to a ‘hothouse earth’ scenario. In fact there are many interlinked tipping points in complex ecological and Earth systems. This year’s IPCC special report describes the impacts of 1.5°C and 2.0°C warming, and identifies pathways to staying within those limits. It says that that to have a chance of staying within 1.5°C we must reverse the increase in carbon emissions within 12 years and reduce it to zero by 2050. All pathways involve behaviour change, innovation and investment in technology, and a transformation of economic and political systems. On current policies we will reach 1.5°C in 2040 and we are heading for 3.3° warming by 2100. Recent measurements of greenhouse gases are breaking records, global temperatures are exceeding expectations, and the rate of warming is rising. Groups like Extinction Rebellion are raising awareness about climate crisis. Their aims include a move towards a better democracy, based on the creation of a citizens’ assembly to oversee the required policy changes. The extinction symbol, above, represents the climate crisis in the form of an hourglass and the planet. As Greta Thunberg said in her speech at the UN COP24 climate talks, “We have run out of excuses and we are running out of time. We have come here to let you know that change is coming, whether you like it or not.”

All of this means that unless we change course dramatically and rapidly enough to limit the worst effects, our existing way of life will be destroyed anyway. On top of so much new evidence this year of the extent and impact of global warming, one paper – Deep Adaption by Jem Bendell – tipped me over to that conclusion. From the abstract: “The purpose of this conceptual paper is to provide readers with an opportunity to reassess their work and life in the face of an inevitable near term social collapse due to climate change.” It is bleak but realistic and important reading. Deep Adaptation is an “agenda of resilience, relinquishment and restoration” and an approach to engaging with social and environmental dilemmas:

Recent research suggests that human societies will experience disruptions to their basic functioning within less than ten years due to climate stress. Such disruptions include increased levels of malnutrition, starvation, disease, civil conflict and war – and will not avoid affluent nations. This situation makes redundant the reformist approach to sustainable development and related fields of corporate sustainability that has underpinned the approach of many professionals (Bendell et al, 2017). Instead, a new approach which explores how to reduce harm and not make matters worse is important to develop. In support of that challenging, and ultimately personal process, understanding a deep adaptation agenda may be useful.  http://www.lifeworth.com/deepadaptation.pdf

Joseph Poore & Thomas Nemeck – Reducing food’s environmental impacts through producers and consumers (Science, 360(6392): 987–992)
The single most effective way to reduce our impact on the environment is to eat less meat. This large-scale data study shows that if everybody switched to an animal-free diet, it could cut greenhouse gas emissions by half. It would also cut land use for farming – which currently takes up 43% of non-desert, ice-free land – by three quarters. In the context of rising sea levels, this would mitigate the loss of habitable land. The paper (PDF) is quite technical, but EnvironMath has a good summary of the research and its significance.

Christophe Bonneuil – Climate and Collapse: Only through the insurrection of civil societies will we avoid the worst
An interview with historian Bonneuil, for whom the idea of social collapse is real: it has started and is accelerating. He’s not talking about the extinction of humanity (we will survive, even though we’ll end up trying to kill each other, he says), but about the end of the “globalised industrial civilisation resulting from five centuries of capitalism.” Eating less meat may be an effective individual action, but collective action is needed too. Bonneuil argues that we need to work together to reform the political systems and economic structures that have failed us collectively from avoiding the current crisis:

Only a massive mobilisation of civil societies and victims of climate change already facing the damage of existing “globalisation”, only an ethical and political insurrection against all attacks against the living and human dignity itself, only an archipelago of revolutionary changes towards well-being and self-reliant societies can thwart this scenario of ecofascist capitalism. https://www.activisme.fr/climate-and-collapse/

[That’s the end of the stuff on the climate crisis in this post. It made sense to put it all together. The work cited above is genuinely amongst the things that meant the most to me this year. I admit that I’m struggling to deal with it: it affects my mental health and I worry about the future for my family and friends. At the same time, I have hope in the establishment of new economic and political systems to deal with both global warming and inequality.]

Absolver (Sloclap)
This game was given away free with PlayStation online subscription, and it’s become a favourite. Fighting games aren’t usually my thing but this is a bit different. It’s calm and quiet, and the characters don’t have grossly exaggerated gender features. It’s short and fairly simple to learn the basics, but it has a lot of depth and complexity, especially in PvP mode where the rock-paper-scissors aspect of the different fighting styles comes into play. It looks great too. New moves are acquired by successfully countering them. These can be built into a ‘deck’ of moves to suit your style of playing. To succeed against an opponent you need to learn their moves. One thing I noticed whilst playing is that what works well as background music with this game really doesn’t work for driving games like Gran Turismo, and vice versa. With Absolver, music with strong beats makes it difficult to perceive and judge the timing of punches and kicks, whereas soft drone music doesn’t interfere. On the other hand, dance or rock music with repetitive beats works well with driving games, possibly because it provides a metric tempo that helps judge braking and turning points. In contrast, drone music is distracting because it interferes with the sounds of the engine speed and tyre grip which provide necessary feedback. This is a masking effect – the aesthetic sound (background music) must not mask the semantic (information-carrying) sounds.

Ancient Methods – The Jericho Records
Probably one of my most-played albums this year, just because it’s a nice one to relax to (if you like relaxing to banging gothic techno). Autechre – NTS Sessions (Warp Records)
Whenever Autechre release new music, it always seems to illustrate something I wrote about in post a few years back, the ‘adjacent possible’. The original idea by Stuart Kauffman is an application of complex systems analysis to evolutionary biology. It refers to the way in which species evolve from what they are into the previously-unknown. It describes a limit in the space of possibilities and at the same time limitless potential, because some changes alter the space of possibilities itself, which enables increasing complexity. There are problems in drawing an analogy between biological evolution and musical evolution: individuals, species and families don’t map neatly to albums, artists and genres, and it’s difficult to find a cultural counterpart to the biological genotype/phenotype distinction (what is the ‘DNA’ of music?). But an evolutionary pathway in music might be imagined in terms of the way in which successive albums occupy or develop different styles. In both biology and music, an evolutionary history can be explained after the fact in terms of causes and contingencies, but its future direction is always unforeseeable.

Jacques Beloeil – Exit (Bandcamp)
Excellent musique concrète by the mastering engineer behind most of the albums on Entr’acte.

Kate Crawford & Vladan Joler – Anatomy of an AI System
An essay and diagram that maps the structure of the information economy by looking at one particular product. Crawford and Joler analyse Amazon Echo in terms of the processes and resources that go into its making and the network of systems involved in its operation. They show how information architecture plugs into the material world. https://anatomyof.ai/

This collaborative label is run by the people behind the labels Conditional, FLUF and Disformation. In just over one year CO-DEPENDENT has released around 40 albums, providing a showcase for new musicians. It uses a generic format for album titles and artwork. Artists only get to choose the 3-digit number associated with their release. CODE666 by Calum Gunn was the first release in November 2017. The latest was released yesterday, 30th December 2018 – CODE404 by Victor Moragues.

Consumed – A Decade of No (Umlaut Records)
My friends Steve Ford (vocals, guitar) and Chris Billam (drums), who I’ve known since the first incarnation of Consumed in the early 90s, got the band back on the road a few years ago and in 2018 released this new material. As always, it’s produced immaculately by Andy Sneap.

De Leon – De Leon (Mana Records)
Beautiful bell sounds and slinky rhythms.

Beatrice Dillon – FACT mix 657
Includes a few of my favourite music from this year, like 0009A by NYZ, and some great things I’d not heard before. https://www.factmag.com/2018/06/11/beatrice-dillon-fact-mix/

Films: Suspiria was a bit of a let-down, especially the ending, but a nice detail in Thom Yorke’s soundtrack was the music in the scene of the public performance, whose 5/4 time signature matched the pentagram hidden within the markings on the dance studio floor. Hereditary was much better: properly spooky and more coherent, and the music by Colin Stetson is particularly good. Best of all were You Were Never Really Here directed by Lynne Ramsay and The Phantom Thread by P.T. Anderson, both with soundtracks scored by Johnny Greenwood. My favourite is Mandy by Panos Cosmatos, which features Nic Cage on top form. It’s a bloody, twisted tale of revenge with retro psychedelic visuals and what turned out to be one of Johan Johansson’s final scores.

RIP Peter Firmin, artist, illustrator, model-maker. I grew up watching the TV programmes of Peter Firmin and Oliver Postgate: Bagpuss, Clangers, Noggin the Nog, Ivor the Engine. I still have a book by Firmin, the Winter Diary of a Country Rat, that I was given for Christmas back then. I’ve always loved his style of drawing. The lines about planet Earth quoted at the top of this post are from the introduction to Clangers.

GOHV – AA0008 (FLUF)
The first in the AA series of two-track releases on FLUF, AA0001 by tuuun, was in my end-of-year list for 2017. Since then the series has grown impressively. Here I’m picking out just one release, but the whole series has been one of my favourite things to listen to this year. GOHV is Casper Gottlieb and Jesper Bagger-Hvid. They specialise in making musical moiré patterns. I bloody love the track ‘0008A’, admittedly partly because it’s the kind of thing I’m trying to do with my own music. Although we have different aims and approaches, the ends results are similar: the music has a slightly disorienting effect based on slow changes in non-repeating patterns.

David Graeber – Bullshit Jobs: A Theory (Simon & Schuster)
Graeber’s book expands on his 2013 article, On the Phenomenon of Bullshit Jobs. The elaboration of the theory into a typology of bullshit jobs is based on a collection of testimonies and interviews with people who answered Graeber’s call for evidence on Twitter. It’s an engaging, informative book with lots of little insights alongside the main subject, such as: men tend to take the jobs they can tell stories about, while women tend to do the kind of work they can tell stories during. The book is good because it not only makes sense in itself but also connects with other things. For example: In the Deep Adaptation paper mentioned above, Jem Bendell recognises the bullshitization of academia that Graeber writes about (see also his article in the Chronicle of Higher Education), and pins it on neoliberal economics: “This ideology has now influenced the workloads and priorities of academics in most universities, which restricts how we can respond to the climate tragedy.” Graeber’s analysis of stories about a managerial culture based on futile tasks is complemented by research on what makes work meaningful which “showed that quality of leadership received virtually no mention when people described meaningful moments at work, but poor management was the top destroyer of meaningfulness”. His link between bullshit work and illness also relates to Mark Fisher’s ideas on the link between mental health and capitalist realism:

Neoliberalism reproduces itself through cynicism, through people doing things they “don’t really believe”. It’s a question of power. People go along with auditing culture and what I call “business ontology” not necessarily because they agree with it, but because that is the ruling order, “that’s just how things are now, and we can’t do anything about it”. That kind of sentiment is what I mean by capitalist realism. And it isn’t merely quietism; it’s true that almost no-one working in public services is likely to be sacked if they get a poor performance review (they will just be subject to endless retraining); but they might well be sacked if they start questioning the performance review system itself or refusing to co-operate with it. https://www.versobooks.com/blogs/3051-they-can-be-different-in-the-future-too-mark-fisher-interviewed

Alvin Lucier – Criss Cross / Hanover and So You … (Hermes, Orpheus, Eurydice) (Black Truffle)
The image above is a spectrogram of ‘So You … (Hermes, Orpheus, Eurydice)’. I looked at ‘Criss Cross’ and ‘Hanover’ in an earlier post. Spectrograms seem to work well with Lucier’s music because they can reveal ordinarily inaudible details and show the bigger picture in a way that’s difficult to perceive whilst listening. In this case, it shows a structure that represents the descent to Hades in the myth of Orpheus and Euridyce. In ‘So You…’, three sine waves start at around 2,000Hz and gradually descend in pitch to 64Hz and back again. This covers a range of around 5 octaves, approximately C2 to C7, over a duration of one hour. Against the sine tones there are three accompaniments: voice, cello and clarinet – which pitch in at around the same frequency. Because the sine waves are constantly changing pitch, the accompaniments are always slightly ‘off’. Lucier’s recent compositions are as vital as his early work.

rkss – DJ Tools (UIQ)
I recommend reading Xenogothic’s post on DJ Tools which describes it better than I can. The part that resonated with my experience of listening to this album is where he says that the album “is not saying: ‘Look what I can do with these out-of-the-box sounds.’ It’s saying, look what lurks just below the surface of EDM today… Here be dragons…“. Making something out of well-worn pieces of music has been a bit of a thing this year. In addition to rkss’s re-working of generic EDM sample packs, there’s been Rian Teanor’s RAVEDIT made with cheesy Euro-dance, EVOL’s Ideal Acid amassed from 1-second, 4-beat samples from hundreds of different acid tracks and Battle Tracks, instrumental MIDI-file versions of 57 dance pop tunes. rkss has also created a counterpart album of remixes of some well-known (copyrighted) tracks: DJ Tools: Illegal Material.

Laurie Spiegel & Don Christensen – Donnie and Laurie (Unseen Worlds)
A motorik drumbeat played by Christensen pans around and underpins Spiegel’s delicate oozing electronic synth chords. The two parts contrast highly – fast/slow, loud/quiet, hard/soft, simple/complex – and work together nicely. It’s a happy piece of music which is why I like it a lot.

Massimo Toniutti – Il Museo Selvatico (Black Truffle)
Like a soundtrack to a very dark comedy. In the first track, nerve-jangling sounds of scrapes, clanks and rattles reverberate in what might be a barn or a courtyard, whilst a low horn tone seems to alternate in perception between an ominous groan and a sad trombone. It’s arty, abstract music but humble, not pompous. Overall it has a very uncanny atmosphere. A metallic bell sound, occurring around 17 minutes into the 6th track, is so similar to the first note in the De Leon album (see above) that I had to check it wasn’t accidentally playing at the same time.

Rian Treanor – Contraposition (Arcola)
Possibly my favourite thing this year. Music to be jealous of, seemingly effortlessly combining cutting-edge razor-sharp sounds with taut rhythms to produce something that’s actually danceable. Really nice design on the vinyl too.

Buy Music Club
A simple web app to create and share lists of Bandcamp albums. Here’s a list of some of the good things I bought this year: https://buymusic.club/embed/guy-2018-long-list

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