Construction & Engineering Data Provider · Head-to-head
OECD Data Explorer (Building Permits & Construction Indicators) vs Web Soil Survey (WSS)
Which construction & engineering data provider data fits your job: OECD Data Explorer, or Web Soil Survey. API, files, or your warehouse. Daily, weekly, or hourly.
OECD Data Explorer (Building Permits & Construction Indicators)
Web Soil Survey (WSS)
Coverage, side by side
| OECD Data Explorer | Web Soil Survey | |
|---|---|---|
| Geographic | `REF_AREA`: ISO country codes for all OECD members plus partner economies; regional flows add subnational detail | AOI selectors: `AOICOORDS`, `MUKEYLIST`, `SSA`, `WSSAOIID` bounding any US area |
What each contains
Pick by fit, not by loyalty.
| OECD Data Explorer | Web Soil Survey | |
|---|---|---|
| Observation identity | `REF_AREA` + `MEASURE` + `ACTIVITY` composed key (e.g. USA.M.PRVM.IX.F.N) | `mukey` + `muname` + `musym` (e.g. 49456, Sarkar-McGilvery complex, 10F) |
| Observed value | `OBS_VALUE` under `UNIT_MEASURE` (IX index, base period in `BASE_PER`) | Polygon geometry plus component/horizon attribute columns and interpretation ratings |
| Time stamp | `TIME_PERIOD` (YYYY-MM, e.g. 2026-05) | Retrieval snapshot - SSURGO is continuously revised, not versioned |
| Geographic key | `REF_AREA`: ISO country codes for all OECD members plus partner economies; regional flows add subnational detail | AOI selectors: `AOICOORDS`, `MUKEYLIST`, `SSA`, `WSSAOIID` bounding any US area |
| Classification system | `ACTIVITY` on ISIC Rev.4: F Construction, F41 buildings, F42 civil engineering, F43 specialised (F4329/F4330/F4390) | Soil taxonomy: map unit names, components and horizons per the National Soil Survey Handbook |
| Derived analytics | Five measures in one flow: PRVM production volume, PR production, OD orders/demand, OI orders inflow, EM employment | Engineering interpretations: dwellings with basements, septic absorption, roads ratings via SERVICE=interpretation REQUEST=getrating |
| Adjustment flag | `ADJUSTMENT` (N not seasonally adjusted, S seasonally adjusted) | None - raw surveyed attributes throughout |
What each does better
OECD Data Explorer
Cross-country breadth on one grid. The core STES flow (DSD_STES@DF_INDSERV) carries five construction measures - PRVM production volume, PR production, OD order intentions or demand, OI orders inflow and EM employment - sliced by ISIC Rev.4 activity down to sub-classes like F4329 and F4390. Every OECD member and partner economy reports into the same dimensional structure, so a five-country comparison of construction output needs no schema stitching.
A monthly macro clock with real history. Short-term indicators run monthly from the 1990s to the current month; the captured US sample shows consecutive index readings for February through May 2026 - 168.16, 185.23, 195.52, 206.20 (index, 2015=100) - a live series you can trend straight into a model.
The only OECD-published record in the slice. Inside Datadory's 19-dataset construction set it is the organisation's sole entry, which makes it the default when a client deck needs harmonised international construction numbers rather than one jurisdiction's ledger.
Web Soil Survey
Parcel-level answers no national series can give. WSS speaks in map units: mukey 49456, Sarkar-McGilvery complex, 75 to 120 percent slopes, symbol 10F; mukey 49457, Kupreanof-Tolstoi association, 5 to 35 percent slopes, symbol 11B - real rows pulled from a live query during the August 2026 research pass. Suitability ratings arrive per area of interest through the interpretation service, feeding foundation screening, earthworks, drainage and site selection directly.
National ground coverage. SSURGO spans the United States and territories with soil maps over more than 95% of US counties, and the record carries spatial feature types (MapunitPoly, SurveyAreaPoly) alongside hundreds of tabular properties at component and horizon level - depth of attribute structure a monthly indicator row cannot approach.
Snapshot discipline as a feature. There is no release calendar to chase: the database is continuously maintained, so a captured extract stays internally consistent forever once you record its retrieval date. For engineering workflows that version their inputs, that beats a series that moves under you every month.
The verdict
Verdict: sample both, pick by fit. Let the unit of analysis decide. If your question names an economy - US construction production volume running at 206.20 against a base of 100 in May 2026 after starting the year at 168.16, or employment in civil engineering across every member economy - OECD Data Explorer (Building Permits & Construction Indicators) is shaped for it. If your question names a place - whether a slope over 75 percent sits under the parcel, what the septic absorption rating says, which map units bound the corridor - Web Soil Survey (WSS) answers it and nothing else can.
Because both records carry the same 8/10 score, neither wins on quality; they win on different questions. Cut each sample to the countries, measures and areas of interest you actually model, and let the returned rows make the call rather than the brand names.
Sample both, pick by fit. See OECD Data Explorer · See Web Soil Survey
Fair questions
Is OECD Data Explorer (Building Permits & Construction Indicators) better than Web Soil Survey (WSS)?
Different instruments, tied on craft - both score 8/10. The OECD wins whenever the question crosses a border: production volume, orders and employment harmonised across every member and partner economy on one monthly grid. WSS wins whenever the question touches ground: map unit polygons, slope ranges and septic or foundation ratings for any US area of interest. Sample both, pick by fit.
Which dataset covers more geography?
Depends how you count. The OECD record spans every member and partner economy - dozens of countries in one dimensional grid - while WSS covers exactly one country but goes deeper than any international series can: more than 95% of US counties mapped at individual soil map unit level. Breadth belongs to the OECD; vertical resolution inside the United States belongs to WSS.
Do the two datasets overlap anywhere?
Only structurally, not substantively. Both anchor observations in time, both carry verified field definitions, and both publish through official statistical agencies. But their subject matter never intersects - the OECD measures economic activity in the construction sector, WSS describes physical ground conditions beneath it. They complement rather than compete.
Which dataset should a construction analyst sample first?
Sample both, pick by fit - the deliverable decides. Market sizing, cycle timing or cross-country benchmarking starts with [OECD Data Explorer (Building Permits & Construction Indicators)](/datasets/construction-engineering/oecd-data-explorer-building-permits-construction-indicators); site selection, foundation screening or land-feasibility work starts with [Web Soil Survey (WSS)](/datasets/construction-engineering/web-soil-survey-wss). Name the countries, measures or areas of interest when you request the sample and it lands pre-cut, with field definitions and coverage profiles attached.
Can Datadory deliver both datasets together?
Yes. Either record arrives alone or merged onto one delivery calendar, aligned on period and unit so the join is done before it reaches you - delivered daily, weekly, or hourly, your call. Because the two layers answer different halves of the same build decision, most teams take both in one feed.