The Three Headed Monster
The framework behind the series: three heads, twelve problems.
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Why your data infrastructure undermines your expertise, and how to fix it. Three heads, twelve problems.
The stories in this series are composites of real projects, anonymized.
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The framework behind the series: three heads, twelve problems.
Read on LinkedInData In: how errors enter early and compound at every step.
Read on LinkedInData Work: the effort that starts from zero every cycle.
Read on LinkedInData Out: why your impact stays locked away.
Read on LinkedInThe governance and architecture framework behind the series.
Read on LinkedInData In
Without systematic intake and validation, errors slip through early and compound at every step.
Data In
One team entered a sea urchin, Paracentrotus lividus, as "spiky thing (purple)". An infrastructure problem, not a people problem.
Read on LinkedInData In
Six months of physically impossible dissolved oxygen readings, because nobody checked at entry.
Read on LinkedInData In
Five years of monitoring data that could not be analyzed as a time series, because every phase used different units, schemas and column names.
Read on LinkedInData In
Twelve years of spatial science reduced to one static screenshot and two weeks of coordinate system emails.
Read on LinkedInData Work
Every cycle starts from zero: scripts rebuilt, spreadsheets merged by hand, one person holding all the answers.
Data Work
Forty three files, the most useful one named AAAAA.R, and eight weeks to work out which script did what.
Read on LinkedInData Work
One stakeholder asked for the same data three times in a month because they kept losing the email attachment.
Read on LinkedInData Work
The same report rebuilt from scratch every quarter, same charts, same indicators.
Read on LinkedInData Work
Same river basin, same questions, five years on. The difference in citations was a public data portal.
Read on LinkedInData Out
Reports take weeks, stakeholders get attachments instead of portals, and when staff leave, institutional knowledge goes with them.
Data Out
An EU grant application rejected on procedural grounds before anyone read the science.
Read on LinkedInData Out
Ten years of data architecture in one person's head, and four months to reverse engineer it after she left.
Read on LinkedInData Out
Six weeks and thousands of euros to partially recover five years of biodiversity data from a 2008 Access database.
Read on LinkedInData Out
A research group with stronger science lost to a competitor whose data infrastructure was better.
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