Dataset Open Access
González, Óscar;
Barberán, Víctor;
Camprodon, Guillem;
Gharbia, Salem;
Pilla, Francesco;
Ottosen, Thor-Bjørn;
Kumar, Prashant;
Kalaiarasan, Gopinath;
Barwise, Yendle;
Di Nicola, Francesca;
Di Sabatino, Francesca;
Brattich, Erika
Dataset Description
This dataset contains all the deployment data using low cost sensors during the iSCAPE project. The dataset is divided in a series of deployments, each of them described on a yaml file with the test name. Each csv file contains time series data of each experiment, and the yaml files contain the lists of devices used in each test. The tests are described in the comment of the yaml file, and are meant to be self explanatory. Two different types of tests are herein presented:
A complete description of these datasets and the result of their analysis is shown in D7.8 of iSCAPE which can be found in this url: https://www.iscapeproject.eu/results/.
Sensors
The sensors used are herein referred as Citizen Kits or Smart Citizen Kits, and the Living Lab Station or Smart Citizen Station. These are a set of modular hardware components that feature a selection of low cost sensors for environmental monitoring listed below. The Smart Citizen Station is meant to expand the capabilities of the Smart Citizen Kit, aiming to measure pollutants with more advanced sensors. The hardware is licensed under CERN Open Hardware License V1.2 and is fully described in the HardwareX Open Access publication: https://doi.org/10.1016/j.ohx.2019.e00070. The sensor documentation can be found at https://docs.smartcitizen.me and with this DOI at Zenodo: https://doi.org/10.5281/zenodo.2555029.
In the list below, the different sensors for the Citizen Kits are detailed, and their [CHANNELS] in the csv files above linked.
In the list below, the different sensors for the Citizen Kits are detailed, and their [CHANNELS] in the csv files above linked.
The files with the _processed suffix, are processed files which:
1. Resample the data using pandas resampling with mean() - reference here
2. Clean NaN and wrong readings.
3. Add calculations for electrochemical sensors based on this methodology
How to find the data
Each yaml file contains the description of a test. Each test is comprised of recordings of several devices in the same location and during the same period. Each yaml file is comprised of the following fields:
Description of devices entry
For each device that was used in the test, two generic types are used:
For low cost Smart Citizen sensors, the fields are:
For high end sensors, the fields are:
iSCAPE Dataset Reference Numbers:
The datasets here presented are related to the following iSCAPE dataset reference numbers:
Name | Size | |
---|---|---|
2018-03_EXT_DUBLIN_TESTS_KIT0000.csv
md5:aeb2fc574692b785eb905758c86376a5 |
465.1 kB | Download |
2018-03_EXT_DUBLIN_TESTS_KIT0001.csv
md5:37ac0244239470109cb962d24bb53676 |
479.3 kB | Download |
2018-03_EXT_DUBLIN_TESTS_STATION0002.csv
md5:c9ac74d5798e0d076dae5df66d725cd0 |
1.7 MB | Download |
2018-09_EXT_BOLOGNA_TEST_WALL_MO_STATION_ARPAE.csv
md5:e6c966fd69b0908d040ed542c8dfef6a |
1.7 MB | Download |
2018-09_EXT_BOLOGNA_TEST_WALL_MO_STATION_SCK2.csv
md5:7ba423524a7e5f7e8aeebf3f066532b5 |
12.1 MB | Download |
2018-09_EXT_BOLOGNA_TEST_WALL_RE_STATION_ARPAE.csv
md5:0654acd8a8b610bbc1ed21d0f8af05be |
2.0 MB | Download |
2018-09_EXT_BOLOGNA_TEST_WALL_STATIONSCK3.csv
md5:579890921176524578aaf1125083c8fb |
12.6 MB | Download |
2019-03_EXT_UCD_URBAN_BACKGROUND_API_CITY_COUNCIL_DAY_REF.csv
md5:23736ec9c9c7b6ffdf424e2d24cf7be4 |
1.7 kB | Download |
2019-03_EXT_UCD_URBAN_BACKGROUND_API_CITY_COUNCIL_REF.csv
md5:4ad73dbf609cf520bcbd12d96d8f1750 |
540.8 kB | Download |
5262.csv
md5:06fb0752a7f65beb0f6b4a7a9b6ab2db |
16.8 MB | Download |
5262_PROCESSED.csv
md5:8186510966fc8b2f5e28c76db6fb588c |
47.2 MB | Download |
5527.csv
md5:fc670114566b6b8020d46a2e10cb8417 |
37.0 MB | Download |
5527_PROCESSED.csv
md5:966017469c295788164517894e92edf5 |
53.6 MB | Download |
5528.csv
md5:9204c1a4afcc8bf71390e28a8a1c1367 |
33.8 MB | Download |
5528_PROCESSED.csv
md5:2527a1313b4e7ea0c92a011a57ee9a69 |
52.6 MB | Download |
5565.csv
md5:6bb9ffb9f1259258820facb00514162d |
21.8 MB | Download |
5565_PROCESSED.csv
md5:7cb27a52b4798ba1ff10cbf28fe57a5e |
53.1 MB | Download |
8739.csv
md5:1aca68ff651f428ea6ca78087fc9c0aa |
46.2 MB | Download |
8739_PROCESSED.csv
md5:53859a2aae47232f311f3ac5addc5e8b |
34.3 MB | Download |
9397.csv
md5:d784ee84bd17379da46ea3a9bc85097e |
46.9 MB | Download |
9397_PROCESSED.csv
md5:92e318a09a6f9e8e040443ebe2dc6304 |
34.2 MB | Download |
9530.csv
md5:e2ba6fd2719d3bb66fdb894a4062e071 |
7.2 MB | Download |
9530_PROCESSED.csv
md5:784a8e7ac173be848d727cb294771568 |
10.0 MB | Download |
9694.csv
md5:19c16e35b03a82a8c94517749d7dda57 |
32.1 MB | Download |
9694_PROCESSED.csv
md5:345010a25351d447c374cbd22d6f36ff |
30.2 MB | Download |
test_description_2018-03_EXT_DUBLIN_TESTS.yaml
md5:f6ed89d11f935cb580b600c0ad88a17d |
5.0 kB | Download |
test_description_2018-09_EXT_BOLOGNA_TEST_WALL_MO.yaml
md5:1bd37f9379a54456cc970ae06b86565b |
2.9 kB | Download |
test_description_2018-09_EXT_BOLOGNA_TEST_WALL_RE.yaml
md5:a925a37e5187e27d8afbadcf5c3dbdc2 |
2.8 kB | Download |
test_description_2019-03_EXT_UCD_URBAN_BACKGROUND_API.yaml
md5:e8612e4436cca9a48c6944c9beae713b |
2.0 kB | Download |
test_description_2019-03_EXT_UOS_URBAN_BACKGROUND_API.yaml
md5:7ba0cf4094ce7affb67cf4a96510dc6f |
1.0 kB | Download |
test_description_2019-06_EXT_HASSELT_SCHOOL.yaml
md5:2114d087813db0ead864b645d49de213 |
1.2 kB | Download |
test_description_2019-06_EXT_UOS_HEDGES_API_SECOND_BATCH.yaml
md5:82bc49d0ff467bfd4de57f0dd885df12 |
1.0 kB | Download |
All versions | This version | |
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Views | 224 | 224 |
Downloads | 290 | 290 |
Data volume | 2.6 GB | 2.6 GB |
Unique views | 195 | 195 |
Unique downloads | 164 | 164 |