DataHub Content Calendar — 2026

Overview

Goal: Drive traffic to DataHub datasets across social channels, 4×/week. Managed in: datapressr rig, bead prefix da Channels: Reddit (primary) · LinkedIn · X · Instagram (selective) · Newsletter (weekly) · YouTube (selective) Phases: Phase 1 (ready now) · Phase 2 (needs Observable viz added first)

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Posting Instructions

Reddit

• Time: 12:00 PM GMT every posting day
• Days: Mon–Thu only (skip Fri–Sun)
• Day guidance:
  • Mon → commodities, finance, macro (r/Gold, r/StockMarket, r/options)
  • Tue/Wed → environment, history, data science (peak engagement)
  • Thu → tech and AI (r/MachineLearning, r/Futurology)
• Post type: Link post. Paste the URL as the post link.
• Body text: Paste as a top comment immediately after posting.
• Cross-posting: Post to all base channels + topic-specific ones in the schedule.

Base channels — post every dataset here

Communities to avoid

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LinkedIn

• Time: 12:00 PM GMT, same day as Reddit
• Format: 150–250 word post. Lead with the key stat or hook. Frame for professional audience — "what this data reveals about X" not "here's a dataset."
• Image: Attach a screenshot of the datahub.io chart.
• Link: datahub.io URL with LinkedIn UTM at the end of the post.
• Post every dataset.

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X (Twitter)

• Time: 12:00 PM GMT, same day as Reddit
• Option A — short: Single tweet with punchy stat + chart screenshot + link. (The existing titles already work as tweets.)
• Option B — thread: 3–4 tweets for richer datasets. Hook → 2–3 key data points → link.
• Post every dataset.

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Instagram

• Selective — only visually dramatic datasets. Marked IG in schedule.
• Format: Chart screenshot as image. 100–150 word caption: hook → insight → "Full dataset at datahub.io — link in bio."
• Link: Update bio link to the dataset page on posting day.
• Skip: Finance/stock data and niche economic indicators — visual appeal too low for general IG audience.

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Newsletter

• Cadence: Weekly, sent every Friday
• Format: Digest of that week's 3–4 datasets:
  • Header: "This week in data — [date range]"
  • 3–4 items: dataset name → key insight (2–3 sentences) → datahub.io link
  • Featured pick: expand on the week's best-performing post
• Platform: TBD (Substack or Buttondown)
• All datasets feed into the newsletter as a digest — no additional curation needed.

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YouTube

• Shorts (60s): Screen recording of the chart + voiceover of the key insight. Script = body text condensed. One per week, paired with Tue/Wed posts.
• Long-form (8–15 min): "The story behind this chart." One per month. Walk through the history, show the data live on datahub.io.
• Long-form candidates marked 🎥 in the schedule.

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UTM Parameters

Reddit: no UTM. Use clean datahub.io URLs — tracking parameters look spammy and reduce click-through.

All other channels append:

?utm_source=[channel]&utm_medium=[medium]&utm_campaign=datahub-2026&utm_content=[BEAD-ID]

Replace [BEAD-ID] with the bead ID (e.g. da-b0w).

URL Note

All dataset URLs follow https://datahub.io/core/[slug]. Datasets marked ⚠️ may use a different org prefix — verify on datahub.io before posting.

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Schedule

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Phase 2 — Schedule (Add Viz First)

Each dataset needs an Observable Plot visualization committed before the post bead unlocks (see add-viz bead dependencies in datapressr).

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Newsletter — Weekly Digests

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YouTube — Long-form Queue

Datasets marked 🎥 in the schedule, ordered by narrative strength:

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Post Content

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da-b0w — Mar 30 (Mon) · r/Gold · r/StockMarket

Title:

Gold price since 1833 — 190 years of data showing every crash, bull run, and paradigm shift

Link:

https://datahub.io/core/gold-prices

Body (post as first comment):

From the gold standard era through Nixon's 1971 shock to today's safe-haven rallies — almost
two centuries of price history in one chart.

Key moments visible: the 1934 FDR devaluation, the 1971 end of Bretton Woods, the 1980
inflation peak, the 2008 financial crisis spike, and the COVID-era surge to all-time highs.

Data: monthly gold prices in USD from 1833 to present. Free to download.

Results (posted Mar 31):

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da-cjp — Mar 31 (Tue) · r/StockMarket · r/dataisbeautiful

Title:

S&P 500 since 1871 — nominal vs inflation-adjusted returns tell completely different stories [OC]

(Add [OC] only when posting to r/dataisbeautiful)

Link:

https://datahub.io/core/s-and-p-500

Body:

The nominal S&P 500 chart looks like unstoppable growth. Adjust for inflation and the
1966–1982 "lost decade" becomes visible — 16 years of zero real returns.

This dataset goes back to 1871 and includes price, dividend, earnings, and P/E ratio data
compiled by Nobel laureate Robert Shiller. One of the most important long-term finance
datasets available.

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da-kpf — Apr 2 (Thu) · r/energy · r/StockMarket

Reddit title:

Brent crude oil since 1987 — 5 major shocks that reshaped the global economy, all in one chart

LinkedIn post:

Five moments that broke the oil market — and sent shockwaves through the global economy:

▸ 1990: Gulf War — supply fear drove prices to $40
▸ 2008: Financial crisis — demand collapse cut prices in half in 6 months
▸ 2014: OPEC price war — flooded supply to kill US shale. Prices halved in 18 months.
▸ 2020: COVID — demand evaporated. WTI briefly went negative.
▸ 2022: Ukraine invasion — energy security became a national priority overnight.

Each shock had cascading effects on inflation, monetary policy, and geopolitics. The chart makes the volatility undeniable — and a reminder that energy markets remain deeply fragile despite decades of efficiency gains.

Weekly Brent spot prices from 1987 to present → datahub.io/core/oil-prices

X (tweet):

5 shocks that broke the oil market since 1987:

1990: Gulf War
2008: Financial crisis
2014: OPEC price war
2020: COVID
2022: Ukraine

Each one visible in one chart. Weekly Brent prices 1987–present 👇

datahub.io/core/oil-prices

Instagram caption:

Five moments that broke the oil market — all visible in one chart.

1990. 2008. 2014. 2020. 2022. Each spike or crash had real consequences: inflation, recession, energy crises, geopolitical realignments.

What looks like random noise is actually a timeline of global disruption.

Weekly Brent crude prices from 1987 to present. Free to explore at datahub.io — link in bio.

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da-xgo — Apr 1 (Wed) · r/StockMarket · r/financialindependence

Title:

Shiller CAPE ratio since 1881 — every major market crash followed a period of extreme overvaluation

Link:

https://datahub.io/core/s-and-p-500

Body:

The Cyclically Adjusted P/E ratio (CAPE) smooths earnings volatility by averaging 10 years of
real earnings. It's been one of the most reliable long-term valuation signals.

Black Tuesday (1929): CAPE was 32. Dot-com peak (2000): CAPE hit 44. Today's reading is
historically elevated — though elevated doesn't mean imminent crash.

Full data from 1881 to present, free to download.

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da-kpf — Apr 2 (Thu) · r/energy · r/StockMarket

Title:

Brent crude oil since 1987 — 5 major shocks that reshaped the global economy, all in one chart

Link:

https://datahub.io/core/oil-prices

Body:

1990 Gulf War. 2008 financial crisis. 2014 OPEC price war. 2020 COVID demand collapse.
2022 Ukraine invasion. Each spike or crash had cascading effects on inflation, growth,
and geopolitics.

Weekly Brent spot prices from 1987 to present. The data shows how volatile energy markets
remain despite decades of efficiency improvements.

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da-udt — Apr 6 (Mon) · r/StockMarket · r/options

Title:

VIX fear index since 1990 — 35 years of market panic in one chart. Every spike has a story

Link:

https://datahub.io/core/finance-vix

Body:

Black Monday aftermath. Dot-com crash. 9/11. The 2008 financial crisis (VIX hit 80!).
COVID crash in March 2020. Each spike marks a moment when markets seized with fear.

The CBOE Volatility Index measures 30-day expected S&P 500 volatility from options prices.
When VIX spikes, it's usually a buying opportunity in hindsight — but terrifying in real-time.

Daily data from 1990 to present.

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da-0p9 — Apr 7 (Tue) · r/economics · r/dataisbeautiful

Title:

GDP of the world's 10 largest economies (2000–2022) — China's rise is the story of our time [OC]

(Add [OC] only when posting to r/dataisbeautiful)

Link:

https://datahub.io/core/gdp

Body:

In 2000, China's GDP was roughly the size of Italy's. By 2022, it had surpassed the combined
GDP of Germany, Japan, and the UK.

World Bank data covering all countries plus regional aggregates from 1960 to present.
The top 10 economies chart makes the structural shift unmistakable.

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da-jvm — Apr 8 (Wed) · r/energy · r/economics

Title:

Henry Hub natural gas prices since 1997 — the shale revolution collapsed prices and changed everything

Link:

https://datahub.io/core/natural-gas

Body:

Natural gas was expensive and volatile before shale. The 2005 hurricane season sent Henry Hub
above $15/MMBtu. By 2012, shale had pushed prices below $2. The structural change is visible
in one chart.

Monthly Henry Hub spot prices from 1997 to present — the benchmark for North American gas markets.

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da-4t — Apr 9 (Thu) · r/MachineLearning · r/Futurology

Title:

AI training compute 1950–present: the exponential curve that explains the AI revolution

Link:

https://datahub.io/core/epoch-data-on-ai-models

⚠️ Verify this URL on datahub.io before posting

Body:

From ENIAC to GPT-4, training compute has grown by roughly 10 orders of magnitude. That's
more growth than from a bicycle to a rocket ship — in computing power applied to training
a single model.

The Epoch AI dataset tracks compute (FLOPs), parameters, and training data for major ML
models. The recent acceleration post-2010 is unlike anything in computing history.

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da-d15 — Apr 13 (Mon) · r/climate · r/energy

Title:

Global CO₂ emissions by fuel type since 1751 — coal, oil, gas, and cement each tell a different story

Link:

https://datahub.io/core/co2-fossil-global

Body:

Coal dominated for 200 years. Oil exploded after WWII. Natural gas has risen as a "bridge fuel."
Together they've pushed atmospheric CO₂ from 280ppm to over 420ppm.

Data from CDIAC/Global Carbon Project covering global CO₂ emissions from fossil fuels and
cement from 1751 to 2020. Free to download.

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da-enz — Apr 14 (Tue) · r/climate · r/dataisbeautiful

Title:

The Keeling Curve: CO₂ at Mauna Loa since 1958 — the most important climate measurement in history [OC]

(Add [OC] only when posting to r/dataisbeautiful)

Link:

https://datahub.io/core/co2-ppm

Body:

Charles Keeling began measuring atmospheric CO₂ at Mauna Loa in 1958, when it stood at 315ppm.
Today it's above 420ppm — a 34% increase in 65 years, and rising faster each decade.

The annual sawtooth shows the planet "breathing": CO₂ falls as northern hemisphere vegetation
grows in summer, rises in winter. The upward trend is relentless.

Monthly readings since 1958.

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da-d8a — Apr 15 (Wed) · r/climatechange · r/environment

Title:

CO₂ emissions by country since 1950 — how the top 10 emitters diverged over 70 years

Link:

https://datahub.io/core/co2-fossil-by-nation

Body:

The US dominated for decades, then China overtook it in 2006 and never looked back.
Europe has been declining since 1990. India is rising fast.

CDIAC national emissions data from 1950 to 2020, covering all countries. The divergence
between developed and developing economies is the central tension in climate negotiations.

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da-njj — Apr 16 (Thu) · r/europe · r/environment

Title:

EU Emissions Trading System (2005–2024): how carbon pricing has shaped European industry sector by sector

Link:

https://datahub.io/core/eu-emissions-trading-system

⚠️ Verify this URL on datahub.io before posting

Body:

The EU ETS covers 10,000+ installations across energy, aviation, and heavy industry.
Phase 1 was a learning exercise. Phase 3 tightened caps significantly.

The data from the EU Transaction Log shows which sectors have actually decarbonized —
and which haven't. Power generation leads; aviation and cement lag.

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da-0br — Apr 20 (Mon) · r/StockMarket · r/stocks

Title:

S&P 500 by sector: which industries have the most companies — and how that differs from where the money is

Link:

https://datahub.io/core/s-and-p-500-companies

Body:

Industrials and financials have the most companies in the S&P 500. But that's not where
the market cap lives. A handful of tech companies dominate by valuation while representing
a smaller slice of company count.

Dataset includes sector, market cap, P/E, and earnings per share for all ~505 companies.
Free to download.

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da-j9z — Apr 21 (Tue) · r/dataisbeautiful · r/aviation

Title:

World airports by type: 72,000 facilities from balloonports to major hubs — the full global infrastructure [OC]

(Add [OC] only when posting to r/dataisbeautiful)

Link:

https://datahub.io/core/airport-codes

Body:

There are only 1,194 large commercial airports in the world. But 22,000+ heliports and
42,000+ small airports. Commercial aviation's infrastructure is far more concentrated
than most people imagine.

Data from OurAirports.com covering all 72,000+ registered airport facilities worldwide
with type, location, IATA/ICAO codes, and coordinates.

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da-31s — Apr 22 (Wed) · r/StockMarket · r/ValueInvesting

Title:

S&P 500 market cap vs P/E ratio by sector — where the market is cheap and where it's expensive right now

Link:

https://datahub.io/core/s-and-p-500-companies-financials

Body:

Financials and utilities often trade at lower P/Es. Tech carries premium multiples.
Energy swings wildly with commodity cycles.

Includes market cap, P/E ratio, earnings per share, and 52-week high/low for S&P 500
companies with full financial details. Good for sector rotation analysis.

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da-etv — Apr 27 (Mon) · r/economics · r/dataisbeautiful

Title:

Eight centuries of global real interest rates — rates were falling for 700 years before QE reversed the trend [OC]

(Add [OC] only when posting to r/dataisbeautiful)

Link:

https://datahub.io/economic-history/eight-centuries-interest-rates

⚠️ Verify this URL on datahub.io before posting

Body:

From medieval Venetian bonds to today's central bank rates — the long arc of interest
rates shows a 700-year downtrend that arguably reversed around 2020–2022.

The dataset by Paul Schmelzing (Bank of England working paper) covers global real
interest rates from 1311 to 2018, constructed from sovereign bond yields across 17 countries.
One of the most ambitious economic history datasets ever compiled.

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da-97a — Apr 28 (Tue) · r/economics · r/dataisbeautiful

Title:

Global wealth distribution: the top 1% own more than the bottom 50% combined [OC]

(Add [OC] only when posting to r/dataisbeautiful)

Link:

https://datahub.io/economic-history/global-wealth-distribution

⚠️ Verify this URL on datahub.io before posting

Body:

The world's 56 million dollar millionaires (1% of adults) hold 45% of global wealth.
The bottom half of adults — 2.8 billion people — hold just 1.3%.

Data from the Credit Suisse Global Wealth Report covering wealth distribution by
percentile and country. Free to explore and download.

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da-lm2 — Apr 29 (Wed) · r/history · r/economics

Title:

1,000 years of UK economic data: GDP, inflation, wages, and interest rates from 1086 to today

Link:

https://datahub.io/economic-history/millennium-macroeconomic-data-uk

⚠️ Verify this URL on datahub.io before posting

Body:

Starting from Domesday Book estimates in 1086, the Bank of England's "Millennium of
Macroeconomic Data" dataset is one of the most ambitious economic history projects ever assembled.

The Black Death is visible as a productivity spike (fewer workers, higher wages).
The Industrial Revolution as a growth inflection. WWII as a debt explosion.

Free to download. One of the best history + economics datasets anywhere.

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da-e71 — Apr 30 (Thu) · r/dataisbeautiful · r/history

Title:

We work far less than our ancestors: annual hours worked fell from 3,000 to 1,700 over 150 years [OC]

(Add [OC] only when posting to r/dataisbeautiful)

Link:

https://datahub.io/economic-history/working-hours-historical

⚠️ Verify this URL on datahub.io before posting

Body:

A British worker in 1870 worked around 3,000 hours per year. Today the average is under 1,700.
The reduction came from labor movement victories, rising productivity, and higher living standards.

Historical annual hours worked per worker across multiple countries from the mid-19th century
to present. The cross-country comparison is striking.

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da-2mb — May 4 (Mon) · r/Gold · r/Silver · r/StockMarket

Title:

Gold vs silver vs platinum: 40 years of precious metal prices — three very different stories

Link:

https://datahub.io/energy-and-commodities/precious-metals-prices

⚠️ Verify this URL on datahub.io before posting

Body:

Gold is the safe haven. Silver has significant industrial demand. Platinum depends on
auto catalysts and is increasingly tied to hydrogen fuel cells. Their price relationships
shift with macro conditions, industrial cycles, and market sentiment.

Daily closing prices for gold, silver, and platinum from 1987 to present.

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da-aw2 — May 5 (Tue) · r/energy · r/environment

Title:

BP Statistical Review: the global energy mix is shifting — but slower than most people think

Link:

https://datahub.io/energy-and-commodities/bp-statistical-review-world-energy

⚠️ Verify this URL on datahub.io before posting

Body:

Renewables are growing fast but fossil fuels still supply ~80% of primary energy globally.
The BP Statistical Review has tracked global energy consumption, production, and trade since 1965.

Covers oil, gas, coal, nuclear, hydro, and renewables by region. Widely considered the
most comprehensive public energy dataset available.

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da-3d0 — May 6 (Wed) · r/energy · r/history

Title:

400 years of US energy: from wood to coal to oil to nuclear — the full transition history in one chart

Link:

https://datahub.io/energy-and-commodities/us-primary-energy-consumption-historical

⚠️ Verify this URL on datahub.io before posting

Body:

In 1635, American colonists burned wood. By 1900, coal had taken over. By 1950, oil dominated.
Each transition took decades — and the current renewable transition looks similar in pace so far.

US primary energy consumption by source from 1635 to 2000, compiled from EIA historical archives.

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da-urg — May 7 (Thu) · r/environment · r/economics

Title:

Carbon pricing around the world: Sweden charges $130/tonne CO₂ — most countries charge nothing

Link:

https://datahub.io/climate-and-environment/carbon-pricing

⚠️ Verify this URL on datahub.io before posting

Body:

Sweden charges $130+ per tonne. Most US states have no carbon price at all. The EU ETS
has ranged from €5 to €100. The range reflects wildly different political commitments to
climate action across jurisdictions.

Covers carbon taxes and emissions trading schemes across all countries and subnational
jurisdictions, with price history and coverage scope.

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da-d1z — May 11 (Mon) · r/energy · r/climate

Title:

Lazard LCOE: utility-scale solar fell from $359/MWh in 2010 to $24/MWh in 2023 — a 93% cost collapse

Link:

https://datahub.io/climate-and-environment/lazard-levelized-cost-of-energy

⚠️ Verify this URL on datahub.io before posting

Body:

Onshore wind has followed a similar trajectory — down ~70% in 13 years. Both are now
cheaper than new coal or gas plants in most markets, on an unsubsidized basis.

Lazard's annual Levelized Cost of Energy analysis is the gold standard for comparing
generation technologies. The dataset covers every annual edition.

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da-90v — May 12 (Tue) · r/collapse · r/dataisbeautiful

Title:

The Great Acceleration: 12 global indicators all started bending upward around 1950. GDP, CO₂, plastic, more [OC]

(Add [OC] only when posting to r/dataisbeautiful)

Link:

https://datahub.io/climate-and-environment/great-acceleration

⚠️ Verify this URL on datahub.io before posting

Body:

GDP, population, energy use, water use, CO₂, nitrous oxide, methane, species loss,
ocean acidification, stratospheric ozone — they all inflect around 1950.

The "Great Acceleration" refers to the unprecedented surge in human activity and Earth
system changes after WWII. Dataset compiles all 24 indicators from the original
Steffen et al. (2015) paper. The charts are striking.

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da-tfr — May 13 (Wed) · r/environment · r/climatechange

Title:

Planetary boundaries: of the 9 systems that keep Earth stable, we've already breached 6

Link:

https://datahub.io/climate-and-environment/planetary-boundaries

⚠️ Verify this URL on datahub.io before posting

Body:

The Stockholm Resilience Centre's planetary boundaries framework defines the "safe
operating space" for humanity across 9 Earth systems.

Climate change, biodiversity loss, land system change, biogeochemical flows, freshwater
change, and novel entities (including plastics and chemicals) — all breached.
Ozone depletion and ocean acidification are within bounds for now.

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da-owb — May 14 (Thu) · r/climate · r/environment

Title:

Project Drawdown: 80+ climate solutions ranked by CO₂ reduction potential. The ranking will surprise you

Link:

https://datahub.io/climate-and-environment/project-drawdown

⚠️ Verify this URL on datahub.io before posting

Body:

Reducing food waste ranks higher than electric vehicles. Educating girls and family
planning are near the top. Rooftop solar is good, but utility-scale solar is much better.
The rankings consistently challenge popular intuitions.

Project Drawdown is the most comprehensive analysis of climate solutions ever assembled,
with cost and emissions impact estimates across 80+ solutions.

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da-aj7 — May 18 (Mon) · r/history · r/environment

Title:

10,000 years of human land use: from hunter-gatherers to industrial agriculture, visualized

Link:

https://datahub.io/climate-and-environment/hyde-history-database-of-the-global-environment

⚠️ Verify this URL on datahub.io before posting

Body:

In 8000 BCE, almost no land was farmed. By 1800, roughly 6% was cultivated.
Today it's over 50% — pasture, cropland, and urban areas dominating landscapes that were once wild.

The HYDE database reconstructs historical land use every 10 years from 10,000 BCE to 2017,
using population estimates and historical records. One of the most ambitious historical
datasets in environmental science.

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da-1k0 — May 19 (Tue) · r/dataisbeautiful · r/Optimism

Title:

200 years of human progress: life expectancy doubled, extreme poverty fell from 90% to 10%, literacy hit 86% [OC]

(Add [OC] only when posting to r/dataisbeautiful)

Link:

https://datahub.io/society-and-living-standards/history-global-living-conditions

⚠️ Verify this URL on datahub.io before posting

Body:

In 1820, average global life expectancy was 29 years. Extreme poverty was the norm —
over 90% of the world lived on the equivalent of $2/day. Child mortality was above 40%.

Today: life expectancy 73 years, extreme poverty ~10%, child mortality under 4%.
Based on Max Roser's Our World in Data research, covering health, education, income,
and poverty from 1820 to present.

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da-0ww — May 20 (Wed) · r/education · r/dataisbeautiful

Title:

PISA scores 2022: how 79 education systems compare on reading, math, and science [OC]

(Add [OC] only when posting to r/dataisbeautiful)

Link:

https://datahub.io/society-and-living-standards/pisa-education-performance

⚠️ Verify this URL on datahub.io before posting

Body:

Singapore, Macao, Hong Kong, Estonia, and Japan consistently top the rankings.
The US and UK sit in the middle. The gaps between top and bottom countries are enormous —
and they've been remarkably persistent across decades.

OECD's PISA tests 15-year-olds every 3 years in reading, math, and science.
Dataset covers every PISA wave since 2000.

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da-nos — May 21 (Thu) · r/sociology · r/urbanplanning

Title:

Residential segregation in US cities: how racial and income separation has changed since 1970

Link:

https://datahub.io/society-and-living-standards/segregation-tracking

⚠️ Verify this URL on datahub.io before posting

Body:

Some cities have become significantly more integrated since the 1970s. Others remain as
segregated as they were 50 years ago. Income segregation has actually risen even as
racial segregation has modestly declined.

Tracks dissimilarity and exposure indices across US metropolitan areas using Census
data from 1970 to 2020.

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da-y82 — May 25 (Mon) · r/environment · r/geography

Title:

Bioregions 2023: a new map of Earth's 185 living zones — defined by ecology, not politics

Link:

https://datahub.io/climate-and-environment/bioregions-2023

⚠️ Verify this URL on datahub.io before posting

Body:

National borders are human constructs. Bioregions map the actual living world — areas
defined by shared ecology, species assemblages, and climate rather than political history.

The One Earth 2023 update covers 185 bioregions across 14 biomes and 8 biogeographical
realms, with spatial data and biodiversity indicators. Useful for conservation planning
and ecological research.

---

Last updated: 2026-05-26 (da-e71 posted to r/datahub, r/opendata, r/datasets, r/history, r/economics — URL corrected to https://datahub.io/economic-history/working-hours-historical) | 2026-05-13 | Instagram | da-0br | — | — | https://www.instagram.com/p/DYSHRajDQz7/ |