Faculty Publications & Rankings Data System

The Problem#

A business school's research output feeds directly into rankings, accreditation, and reputation — yet publication data typically arrives fragmented, inconsistently formatted, and unverified. Before it can inform strategy, it has to be made trustworthy.

This page describes structure and method only; no sensitive institutional records are shown.

What the System Does#

• Data normalization — reconciles publication records across sources into a single consistent schema: one author, one venue, one work, represented once.
• Source verification — every record is checked against its origin, so that what enters the system is fact, not transcription.
• Ranking classification — publications are classified against the journal lists and frameworks that rankings bodies actually use, converting raw output into strategically legible categories.
• Reporting workflow — a repeatable pipeline from raw records to leadership-ready views, replacing ad hoc spreadsheet assembly with a governed process.

Why It Matters#

Rankings are one of the mechanisms through which institutional reputation is priced. A system that makes research output accurate, classified, and reportable turns a compliance chore into decision-support infrastructure — leadership can see where the institution stands and where investment moves the needle.

What I Learned#

Classification is a form of judgment. Deciding what counts, under which framework, with what evidence, is where data work stops being clerical and becomes strategic.