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A Singapore Government Agency Website 

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COVID-19 Weekly Stats

Data on COVID-19 cases

CSV

Ministry of Health (MOH)

Dengue Clusters

Location of dengue cluster

KML

National Environment Agency (NEA)

Zika Cluster

Active Zika Cluster In Singapore

KML

National Environment Agency (NEA)

CEA Salesperson Information

Listing of 'Active' salesperson that is currently registered under CEA. Data is
updated thrice daily.

CSV

Council For Estate Agencies (CEA)

ACRA Information on Corporate Entities

This is a more detailed version of the UEN dataset here
(https://data.gov.sg/dataset/entities-with-unique-entity-number). It is updated
monthly, and there is additional information such as paid up capital and
auditor.

CSV

Accounting and Corporate Regulatory Authority (ACRA)

Registered Entities with Unique Entity Number

The Unique Entity Number (UEN) is a standard identification number for entities,
ranging from businesses and partnerships to charities and societies, to interact
with government agencies. This dataset comprises data on entities that are
registered in Singapore with any of the UEN Issuance Agencies listed below: *
Accounting and Corporate Regulatory Authority (ACRA) * Attorney-General's
Chambers (AGC) * IE Singapore * Islamic Religious Council of Singapore (MUIS) *
Ministry of Culture, Community and Youth (MCCY) * Ministry of Education (MOE) *
Ministry of Finance (MOF) * Ministry of Foreign Affairs (MFA) * Ministry of
Health (MOH) * Ministry of Communications and Information (MCI) * Ministry of
Manpower (MOM) * Ministry of National Development (MND) * Monetary Authority of
Singapore (MAS) * People's Association (PA) * Registry of Societies (ROS) *
Singapore Land Authority (SLA) For more information, please visit the UEN
Website at https://www.uen.gov.sg/ueninternet/faces/pages/admin/aboutUEN.jspx

CSV

Accounting and Corporate Regulatory Authority (ACRA)

HDB Property Information

HDB property information contains the location of existing HDB blocks, highest
floor level, year of completion, type of building and number of HDB flats
(breakdown by flat type) per block etc.

CSV

Housing and Development Board (HDB)

PM2.5

Regional hourly PM2.5 value measured in μg/m3

API

National Environment Agency (NEA)

Ultra-violet Index (UVI)

UV Index value averaged over the past hour. Updated every hour between 7 AM and
7 PM everyday.

API

National Environment Agency (NEA)

Realtime Weather Readings across Singapore

NEA provides APIs for readings of temperature, humidity, precipitation and wind
conditions at up to one-minute intervals. The data is provided at
weather-station level.

API

National Environment Agency (NEA)

Weather Forecast

Weather forecast for next 2 hours, next 24 hours and next 4 days.

API

National Environment Agency (NEA)

Tourist Attractions

Tourist Attractions in Singapore

KML

Singapore Tourism Board (STB)

Graduate Employment Survey - NTU, NUS, SIT, SMU, SUSS & SUTD

The Graduate Employment Survey (GES) is jointly conducted by NTU, NUS, SMU, SIT
(from 2014), SUTD (from 2015) and SUSS (from 2018) annually to survey the
employment conditions of graduates about six months after their final
examinations. The Ministry of Education (MOE) publishes the results of key
employment indicators of the survey to provide prospective students with timely
and comparable data to assist them in making informed course decisions.
Graduates from NTU, NUS, SMU and SUSS are surveyed in Nov. Due to their
different academic calendars, graduates from SUTD and SIT are surveyed in Feb
and Mar. 2021 GES: * 5,599 fresh graduates and 114 follow-up graduates from NTU
were surveyed and the overall response rates obtained were 75.1% and 78.1%
respectively. * 6,897 fresh graduates and 830 follow-up graduates from NUS were
surveyed and the overall response rates obtained were 74.6% and 69.4%
respectively. * 1,914 fresh graduates and 156 follow-up graduates from SMU were
surveyed and the overall response rates obtained were 76.3% and 78.8%
respectively. * 511 fresh graduates from SUSS were surveyed and the overall
response rate obtained was 81.0%. * 416 full-time and 82 follow-up graduates
from SUTD were surveyed and the overall response rates obtained were 82.0% and
78.0% respectively. * 2,006 full-time graduates from SIT were surveyed and the
overall response rate obtained was 84.5%. 2020 GES: * 5,755 fresh graduates and
99 follow-up graduates from NTU were surveyed and the overall response rates
obtained were 79.1% and 83.8% respectively. * 6,894 fresh graduates and 853
follow-up graduates from NUS were surveyed and the overall response rates
obtained were 78.5% and 74.1% respectively. * 1,883 fresh graduates and 145
follow-up graduates from SMU were surveyed and the overall response rates
obtained were 78.4% and 77.2% respectively. * 370 fresh graduates from SUSS were
surveyed and the overall response rate obtained was 88.6%. * 372 full-time and
62 follow-up graduates from SUTD were surveyed and the overall response rates
obtained were 81.2% and 74.2% respectively. * 2,172 full-time graduates from SIT
were surveyed and the overall response rate obtained was 86.6%. 2019 GES: *
5,909 fresh graduates and 75 follow-up graduates from NTU were surveyed and the
overall response rates obtained were 78.4% and 80.0% respectively. * 6,609 fresh
graduates and 870 follow-up graduates from NUS were surveyed and the overall
response rates obtained were 77.9% and 74.7% respectively. * 1,842 fresh
graduates and 161 follow-up graduates from SMU were surveyed and the overall
response rates obtained were 77.0% and 72.7% respectively. * 252 fresh graduates
from SUSS were surveyed and the overall response rate obtained was 87.3%. * 431
full-time and 62 follow-up graduates from SUTD were surveyed and the overall
response rates obtained were 85.8% and 80.6% respectively. * 1,809 full-time
graduates from SIT were surveyed and the overall response rate obtained was
83.3%. 2018 GES: * 5,900 full-time graduates and 28 follow-up graduates from NTU
were surveyed and the overall response rates obtained were 75.9% and 96.4%
respectively. * 6,699 full-time graduates and 877 follow-up from NUS were
surveyed and the overall response rates obtained were 76.3% and 68.4%
respectively. * 1,886 full-time graduates and 145 follow-up graduates from SMU
were surveyed and the overall response rates obtained were 79.7% and 77.2%
respectively. * 168 full-time graduates from SUSS were surveyed and the overall
response rate obtained was 91.7%. * 334 full-time graduates and 76 follow-up
graduates from SUTD were surveyed and the overall response rate obtained were
85.3% and 84.2% respectively. * 1,707 graduates from SIT were surveyed and the
overall response rate obtained was 85.2%. 2017 GES: * 6,042 full-time graduates
and 30 follow-up graduates from NTU were surveyed and the overall response rates
obtained were 84.3% and 100% respectively. * 6,466 full-time graduates and 825
follow-up from NUS were surveyed and the overall response rate obtained were
80.6% and 72.1% respectively. * 1,779 full-time graduates and 114 follow-up
graduates from SMU were surveyed and the overall response rate obtained were
77.6% and 75.4% respectively. * 228 graduates from SUTD were surveyed and the
overall response rate obtained was 85.4%. * 1,530 graduates from SIT were
surveyed and the overall response rate obtained was 85.6%. 2016 GES: * 5,836
graduates from NTU were surveyed and the overall response rate obtained was
77.0%. * 6,314 graduates from NUS were surveyed and the overall response rate
obtained was 80.4%. * 1,803 graduates from SMU were surveyed and the overall
response rate obtained was 74.1%. * 246 graduates from SUTD were surveyed and
the overall response rate obtained was 83.7%. * 1,230 graduates from SIT were
surveyed and the overall response rate obtained was 84.6%. 2015 GES: * 5,774
graduates from NTU were surveyed and the overall response rate obtained was
71.9%. * 6,188 graduates from NUS were surveyed and the overall response rate
obtained was 74.8%. * 1,638 graduates from SMU were surveyed and the overall
response rate obtained was 76.2%. * 298 graduates from SUTD were surveyed and
the overall response rate was 86.2%. * 1,363 graduates from SIT were surveyed
and the overall response rate obtained was 78.9%. 2014 GES: 14,868 graduates
from NTU, NUS, SIT and SMU were surveyed and the overall response rate obtained
was 75%. 2013 GES: 15,365 graduates from NTU, NUS and SMU were surveyed and the
overall response rate obtained was 72%. Notes: \* SMU's courses are direct
four-yr programmes and graduates could be awarded Cum Laude and above, Merit,
High Merit or no awards. The data for SMU's courses is displayed in two
categories: (i) overall results for all graduates within the course regardless
of the award they attained, and (ii) results for the graduates awarded Cum Laude
and above. Should the graduates undertake more than one Degree (e.g. Dual Degree
programme), they have been classified based on their first Degree. ^ Data is
based on a sample size of fewer than 30 respondents. \** No data is shown due to
the small number of graduates and/or low response rates. \# Data on Law,
Medical, Pharmacy and Biomedical Sciences & Chinese Medicine graduates are
obtained from a follow-up survey on those who graduated one year ago (e.g. for
2018 GES survey, data is obtained from 2017 graduates) after they have completed
their one-year practical law course/pupillage/housemanship/first-year
residency/practical training. Data on Architecture graduates are obtained from a
follow-up survey on those who graduated 3 years ago (e.g. for 2018 GES survey,
data is obtained from 2015 graduates) after they have completed their practical
training. ^^ Data includes the employment figures of graduates from Bachelor of
Engineering (Bioengineering), which was merged into Bachelor of Engineering
(Biomedical Engineering) in 2014. \## Data on NTU’s Medicine graduates will be
obtained from a follow-up survey on the graduates after they have completed
their housemanship/first-year residency. \### Data on SUTD's Bachelor of Science
(Architecture and Sustainable Design) graduates will be obtained from a
follow-up survey on the graduates after they have completed their practical
training. **Disclaimer:** The data published is provided on an “as is” basis
without any warranties of any kind.  To the fullest extent permitted by law, MOE
does not warrant and hereby disclaims any warranty as to the accuracy,
correctness, completeness, reliability or fitness for any particular purpose of
such data.  The reader assumes all responsibility and risk for the use of such
data.  MOE shall not be liable for any damage or loss of any kind caused as a
result (directly or indirectly) of the use of such data, including but not
limited to any damage or loss suffered as a result of reliance on the data
published.

CSV

Ministry of Education (MOE)

Singapore Police Force Digital Traffic Red Light Cameras

Digital Traffic Red Light System (DTRLS) consists of SPF wholly owned traffic
enforcement cameras deployed at road junctions to deter and detect vehicles from
committing the traffic offence of red-running. Implementation approach is in
phases.

KML

Singapore Police Force (SPF)

Master Plan 2019 Subzone Boundary (No Sea)

Indicative polygon of subzone boundary. To facilitate urban planning, the Urban
Redevelopment Authority (URA) divides Singapore into regions, planning areas and
subzones. The Planning Regions are divided into smaller Planning Areas. Each
Planning Area is further divided into smaller subzones which are usually centred
around a focal point such as neighbourhood centre or activity node. The Master
Plan is a forward looking guiding plan for Singapore's development in the medium
term over the next 10 to 15 years and the planning boundaries may not coincide
with existing developments for some areas.

KML

Urban Redevelopment Authority (URA)

HDB Resale Price Index

Tracks the overall price movement of the public residential market. The index is
based on quarterly average resale price by date of registration. The index till
3Q2014 was computed using stratification method, while that from 4Q2014 onwards
is computed using the stratified hedonic regression method. 1Q2009 is adopted as
the new base period with index at 100. The index from 1Q1990 to 3Q2014 are
rebased to the new base period at 1Q2009. Indices from 1Q1990 to 3Q2014 are
re-scaled using a factor of 100 (new index in 1Q2009) / 138.3 (original index in
1Q2009) multiplied on the original index level to derive the re-based index
level for the respective quarters. Due to rounding, there could be some
differences in the quarterly price change compared to the RPI series before
re-scaling.

CSV

Housing and Development Board (HDB)

Renting Out of Flats 2023

Market rental rates by approval date. The rental should be taken as indicative
only as the rental agreed between the flat owners and tenants are dependent on
many factors. The rental is based on the declaration by the flat owner. HDB does
not verify the accuracy of the data.

CSV

Housing and Development Board (HDB)

Annual Motor Vehicle Population by Vehicle Type

Annual motor vehicle population by vehicle type

CSV

Land Transport Authority (LTA)

Public Transport Utilisation - Average Daily Public Transport Ridership

Average daily number of trips made islandwide on MRT, LRT, bus & taxi. * Only
data from 2001 onwards had been updated when the methodology of estimating taxi
ridership was revised in 2003.

CSV

Land Transport Authority (LTA)

Median Rent by Town and Flat Type

Median Rent by Town, Flat Type Per Quarter. The data is based on rent
self-declared in the renting out of flat application. The median rent indicates
that half the total number of units were rented above that price while half were
below. NOTES: * The figures are based on rent declared in the renting out of
flat applications and rounded off to the nearest $10 * "-" Indicates that the
median rent is not shown because there are less than 20 renting out of flat
transactions in the quarter for that particular town and flat type. The median
rent of these cases are not shown as they may not be representative.

CSV

Housing and Development Board (HDB)

Traffic Images

Returns links to images of live traffic conditions along expressways and
Woodlands & Tuas Checkpoints.

API

Land Transport Authority (LTA)

Real-time APIs

View all

PM2.5

Regional hourly PM2.5 value measured in μg/m3

API

National Environment Agency (NEA)

Pollutant Standards Index (PSI)

Overall and regional PSI data (24-hr PSI, Pollutant Concentration and Sub-Index)

API

National Environment Agency (NEA)

Ultra-violet Index (UVI)

UV Index value averaged over the past hour. Updated every hour between 7 AM and
7 PM everyday.

API

National Environment Agency (NEA)

Weather Forecast

Weather forecast for next 2 hours, next 24 hours and next 4 days.

API

National Environment Agency (NEA)

Carpark Availability

Get the latest carpark availability in Singapore: - Retrieved every minute - Use
the date_time parameter to retrieve the latest carpark availability at that
moment in time - Detailed carpark information can be found at
https://data.gov.sg/dataset/hdb-carpark-information - Limited to 60 requests per
minute per API key

API

Housing and Development Board (HDB)

Taxi Availability

For access to real-time taxi availability data. Returns location coordinates of
all Taxis that are currently available for hire. Does not include "Hired" or
"Busy" Taxis.

API

Land Transport Authority (LTA)

IPOS applications API

This dataset contains APIs for the retrieval for the following type of
applications: - Patents - Designs - Trademarks

API

Intellectual Property Office of Singapore (IPOS)

Realtime Weather Readings across Singapore

NEA provides APIs for readings of temperature, humidity, precipitation and wind
conditions at up to one-minute intervals. The data is provided at
weather-station level.

API

National Environment Agency (NEA)

Traffic Images

Returns links to images of live traffic conditions along expressways and
Woodlands & Tuas Checkpoints.

API

Land Transport Authority (LTA)

Geospatial data

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Water Ventures

to locate Water-Ventures in Singapore

GEOJSON

People's Association (PA)

Amendment to Master Plan 2019 Symbol Line layer

Gross Plot Ratio, Nature Reserve, National Park and Conservation Area
demarcation line layer. This layer is extracted from the latest Master Plan 2019
which may be updated from time to time. For the latest Master Plan, please visit
URA�s web site at https://www.ura.gov.sg/.

GEOJSON

Urban Redevelopment Authority (URA)

Amendment to Master Plan 2019 Monument Site layer

Indicative Monument site boundary layer. This layer is extracted from the latest
Master Plan 2019 which may be updated from time to time. For the latest Master
Plan, please visit URA�s web site at https://www.ura.gov.sg/.

GEOJSON

Urban Redevelopment Authority (URA)

Amendment to MP2014 Rail Station

Indicative outline of the MRT, LRT stations.

GEOJSON

Urban Redevelopment Authority (URA)

Amendment to MP2014 Other Text

Annotation of other texts displayed in the master plan.

KML

Urban Redevelopment Authority (URA)

Amendment to MP2014 Conservation Area Text

Annotation of Conservation Area Text

GEOJSON

Urban Redevelopment Authority (URA)

URA No of Dwelling Units (current year)

This layer shows the number of Dwelling Units for private residential properties
for both occupied and vacant properties.

KML

Urban Redevelopment Authority (URA)

Amendment to Master Plan 2019 Rail Station layer

Indicative MRT and LRT station outline layer. This layer is extracted from the
latest Master Plan 2019 which may be updated from time to time. For the latest
Master Plan, please visit URA�s web site at https://www.ura.gov.sg/.

KML

Urban Redevelopment Authority (URA)

Amendment to Master Plan 2019 Road Graphic layer

Indicative line of road kerb or road divider layer. This layer is extracted from
the latest Master Plan 2019 which may be updated from time to time. For the
latest Master Plan, please visit URA�s web site at https://www.ura.gov.sg/.

KML

Urban Redevelopment Authority (URA)

Social Service Agencies

Directory of Voluntary Welfare Organisations

KML



Strengthening Families Programme

Strengthening Families Programme@Family Service Centre (FAM@FSC) and Related
Programmes

KML



Amendment to Master Plan 2019 Rail Line layer

Indicative line of MRT, LRT and Railway network layer. This layer is extracted
from the latest Master Plan 2019 which may be updated from time to time. For the
latest Master Plan, please visit URA�s web site at https://www.ura.gov.sg/.

GEOJSON

Urban Redevelopment Authority (URA)

Master Plan 2019 Planning Area Boundary (No Sea)

Indicative polygon of planning area boundary. To facilitate urban planning, the
Urban Redevelopment Authority (URA) divides Singapore into regions, planning
areas and subzones. The Planning Regions are divided into smaller Planning
Areas. Each Planning Area have a population of about 150,000 and served by a
town centre and several neighbourhood commercial/shopping centres. The Master
Plan is a forward looking guiding plan for Singapore's development in the medium
term over the next 10 to 15 years and the planning boundaries may not coincide
with existing developments for some areas.

KML

Urban Redevelopment Authority (URA)

Amendment to Master Plan 2019 Underground Structure layer

Indicative outline showing selective underground structure and infrastructure
layer. This layer is extracted from the latest Master Plan 2019 which may be
updated from time to time. For the latest Master Plan, please visit URA�s web
site at https://www.ura.gov.sg/.

KML

Urban Redevelopment Authority (URA)

Amendment to Master Plan 2019 Road Name layer

Annotation of road names layer. This layer is extracted from the latest Master
Plan 2019 which may be updated from time to time. For the latest Master Plan,
please visit URA’s web site at https://www.ura.gov.sg/.

KML

Urban Redevelopment Authority (URA)

Amendment to Master Plan 2019 Rail Station Name layer

Annotation of MRT and LRT Station name layer. This layer is extracted from the
latest Master Plan 2019 which may be updated from time to time. For the latest
Master Plan, please visit URA�s web site at https://www.ura.gov.sg/.

KML

Urban Redevelopment Authority (URA)

Amendment to Master Plan 2019 Other Line layer

Other line works layer. This layer is extracted from the latest Master Plan 2019
which may be updated from time to time. For the latest Master Plan, please visit
URA�s web site at https://www.ura.gov.sg/.

KML

Urban Redevelopment Authority (URA)

Amendment to MP2014 Rail Station Text

Annotation of MRT and LRT station name.

GEOJSON

Urban Redevelopment Authority (URA)

Amendment to Master Plan 2019 Monument Building layer

Indicative monument building layer. This layer is extracted from the latest
Master Plan 2019 which may be updated from time to time. For the latest Master
Plan, please visit URA�s web site at https://www.ura.gov.sg/.

GEOJSON

Urban Redevelopment Authority (URA)

Amendment to Master Plan 2019 Monument Number layer

Annotation of Monument Number layer. This layer is extracted from the latest
Master Plan 2019 which may be updated from time to time. For the latest Master
Plan, please visit URA’s web site at https://www.ura.gov.sg/.

GEOJSON

Urban Redevelopment Authority (URA)

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