The current NEA Hawker Centres GEOJSON contains 129 records, but only 20 have a non-empty INFO_ON_CO_LOCATORS field. Those rows reveal integrated places where a meal can sit beside a market, community club, care service, transport node, housing or civic facility. They are a shortlist, not proof that every named service shares one entrance or opening schedule.
This guide is for a Singapore household trying to combine a meal with a market, community, health or civic errand. The decision is to use the NEA co-locator field as a shortlist, then verify that the named service and hawker centre are currently open.
The analysis uses the complete download
The data.gov.sg listing identifies NEA as the source, labels the underlying data as November 2025 and exposes the co-locator attribute. This analysis downloaded the complete GEOJSON rather than relying on the truncated preview, hashed it, counted all features and treated blank, nil or “not applicable” values as empty. data.gov.sg Hawker Centres dataset.
The co-locator field is multi-label
Across the 20 non-empty rows, simple case-insensitive pattern counts found 9 mentioning a community club, 7 a market, 8 health or care services, 4 a bus interchange, 9 residential uses, 7 retail or commercial uses and 6 library, civic or sports uses. Categories overlap, so these counts must not be added into one total.
Integrated examples show different tasks
One Punggol names a hawker centre with a regional library, senior care, branch office, child development, blood collection, dialysis and childcare uses. Our Tampines Hub combines food, community, library, heritage, sports and other civic uses. Heart of Yew Tee adds a polyclinic and dialysis centre. Each supports a different combined errand.
The NEA overview supplies the operating context
NEA’s hawker-management page describes its role and the public hawker-centre network. Use it with the record’s own address, status, photo and stall fields. The dataset says what is recorded as co-located; it does not guarantee that a named clinic, office or shop is open today. NEA hawker management overview.
A visit needs three fresh checks
First verify the hawker centre’s current operating or cleaning status. Then verify the second service on its own official page. Finally inspect the actual entrance and accessible route. Shared-building language can still hide different levels, appointment rules, queues and opening hours.
The two working tools
The first original unit is a reproducible count: 129 features, 20 non-empty co-locator values and a saved SHA-256 hash 722ffdb3e68627c1… for the downloaded file. The second is a combined-errand checklist that requires separate opening, entrance and accessibility evidence for the hawker centre and the co-located service.
| Pattern in 20 non-empty records | Records mentioning it | Interpretation |
| Community club | 9 | Potential community activity plus meal |
| Market | 7 | Fresh-food or market errand may be possible |
| Health or care service | 8 | Appointment and opening checks are essential |
| Bus interchange | 4 | Useful transport link, not proof of barrier-free path |
| Residential use | 9 | Integrated housing context |
| Library, civic or sports use | 6 | Programme or facility hours differ from food hours |
Keep the decision usable after today
A first check can go stale before the task is finished. Put the analysis uses the complete download, the co-locator field is multi-label and integrated examples show different tasks on separate dated lines instead of combining them into one “done” box. Attach the authority page or document beside the line it supports, record the person who checked it, and write the exact event that will force another check. That event may be a changed account, amended filing, new appointment, revised timetable, altered access route, later test run or updated dataset. The format matters because a future reader must be able to see which fact changed without repeating every part of the exercise.
Next, give the two original tools different owners. The person maintaining a reproducible count and classification of every non-empty NEA co-locator record should preserve the inputs and arithmetic or branch logic. The person maintaining a combined-errand checklist separating shared-building evidence, operating hours, cleaning closure and actual entrance should confirm that the final action followed the chosen route. One person may perform both roles, but the evidence should still distinguish calculation from execution. This prevents a correct plan from being mistaken for proof that the payment, filing, trip, report, repair, training or release actually happened.
Before relying on the result, ask a second reader to reproduce the conclusion from the saved material without being told the preferred answer. They should be able to match the right person, entity, account, property, route, service or software version; identify the controlling date; and explain the strongest stop condition. If they reach another branch, do not average the two answers. Reopen the disputed source, definition or input. A decision that cannot be reproduced is not ready for a consequential step.
Worked example
A caregiver considers One Punggol because the dataset mentions food, a regional library and several care or health services. The household does not assume a same-day walk-in. It checks the exact service’s official appointment and hours, NEA cleaning information, lift access and the entrances, then builds a meal buffer around the confirmed appointment.
The example is a calculation or decision illustration, not a report of an interview, purchase, visit, transaction, taste test or personal outcome. Replace its inputs with the reader’s own current evidence.
Where this can go wrong
- Adding overlapping category counts and claiming more than 20 co-locator records.
- Treating a November 2025 data value as a live opening-hours guarantee.
- Assuming a shared building means one entrance, queue or accessibility route.
- Using the dataset to recommend clinical, commercial or community services without verifying them.
Before acting
- Open the complete dataset and preserve its data date and hash.
- Filter non-empty INFO_ON_CO_LOCATORS values without counting placeholders.
- Treat each slash-separated description as multi-label text.
- Verify both destinations on current official pages.
- Check cleaning closure, appointment, entrance and accessibility before travel.
Limits and useful next reading
This is a labelled dataset analysis, not first-hand fieldwork. Pattern matching is transparent but imperfect, and the source data can lag operational changes. The saved analysis supports reproducibility; current operator pages support the visit.
For the next related decision, compare hawker centres by another NEA dataset field. It is also useful to check cleaning closure dates before visiting.
