Match hospital affiliations to ROR without guessing the institution

1. Preserve the author’s original statement

Keep the original affiliation exactly as submitted alongside any normalized version. Separate department, organization, city and country into working fields without silently discarding a campus name. Ask what time the affiliation describes: where the research was performed, the author’s current address, or another relationship defined by the journal’s instructions. These can differ, and an identifier cannot resolve that editorial question on its own.

In the fictional case, an author submits “Respiratory Research Unit, Al-Sahil Teaching Hospital, East Campus, Gulf City”. The research took place in 2023, while the author now works elsewhere. Al-Sahil, Gulf City and every candidate below are invented. No country, university partnership or corporate owner has been supplied. Those details must not be manufactured merely to create a complete-looking registry query.

2. Inspect more than the displayed name

ROR’s current record structure includes name variants and language tags, locations, organization types, status and relationships. A hospital can have a healthcare type, while a medical school is treated differently. Parent, child and related relationships describe different organizational connections. Read the record rather than selecting a result solely because its English display name resembles the submitted text.

For a small editorial workflow, assemble a candidate sheet using the registry record and the institution’s own public information. Compare exact names, place, domain and organization level. Treat an Arabic name and an English transliteration as evidence to examine, not proof that two entries are identical. If the institutional page does not explain the campus, keep the campus question open instead of deleting it from the affiliation.

Reference: ROR: organization record structure

3. Work through an ambiguous match

Assume the editor receives three invented candidate descriptions. Candidate A has a similar hospital name but is in a different city. Candidate B matches the supplied campus and a dated institutional page, but the author has not confirmed that this was the research affiliation. Candidate C is the parent university rather than the hospital. None of these descriptions contains a real ROR ID, and the table is not the output of a live search.

The key decision is not which row looks most complete. It is whether the evidence supports the specific institution and relationship being recorded. A confirmed organization candidate can coexist with an unconfirmed author affiliation. Record those states separately, because an internal form that offers only “matched” or “unmatched” can conceal what still needs the author’s answer.

On small screens, scroll the table horizontally, or focus it and use the arrow keys.

4. Choose a matching method with an accountable reviewer

ROR documents different query and affiliation-matching approaches. Its query approach supports a person selecting a candidate; its affiliation service can return a chosen indicator, and ROR advises against selecting solely by the confidence score. A returned suggestion is still not proof of the author’s employment or permission to claim an affiliation. Do not present an automated match as an institutional endorsement.

For this proposed small-journal process, one staff member records the candidate and evidence and another checks ambiguous cases. The author confirms the affiliation text and relevant time period. If the answers disagree, pause that mapping while the manuscript proceeds only through steps that do not depend on the disputed information. Avoid sending a broad list of authors or private correspondence to an external matching service merely because an API is convenient.

Reference: ROR: matching organization names

5. Keep historical affiliation accurate

Suppose the fictional hospital joined a new health group in 2025. That event does not automatically rewrite the affiliation of work completed in 2023. Establish the relevant name and organization at the time described. ROR’s documentation distinguishes name changes from predecessor/successor relationships and discusses retaining historically correct names and identifiers in DOI metadata. Check the specific record history before applying a current label to an older article.

A current-address note can help readers understand where an author now works, but it should not erase the institution associated with the research. Conversely, do not freeze an obvious transcription error under the excuse of historical accuracy. Separate a genuine organizational change from a mistaken original entry, and route any published correction through the journal’s actual editorial procedure.

Reference: ROR: organization record structure

6. Verify the published representation

Once the match and author statement are confirmed, record the exact identifier, source record, review date, reviewer and affiliation text used. Read back the public page, PDF and relevant metadata export. Check that the department remains text associated with the correct institution, that the hospital was not replaced by a parent, and that Arabic and English names do not point to different organizations.

An unresolved identifier can remain absent while the approved affiliation is shown as text. Track the missing evidence instead of creating a fake ROR-like string. If a later correction is made, retain why it changed and recheck the affected outputs. A successful organizational match improves the precision of this record; it does not prove indexing, institutional prestige, authorship eligibility or the scientific quality of the article.

Questions for a practical final check

• Original affiliation and relevant time preserved
• Name, location and organization level examined together
• Hospital, campus and parent relationship distinguished
• Candidate match separated from author confirmation
• No invented ROR identifier or affiliation evidence
• Approved values read back in both languages and exported metadata