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  "author": "SMDH Data Science Team",
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  "author": "SMDH Data Science Team",
            
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  "author_email": "info@smdh.uk",
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  "author_email": "info@smdh.uk",
            
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"anonymised-indoor-air-quality-benchmarking-dataset",
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"anonymised-indoor-air-quality-benchmarking-dataset",
            
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  "creator_user_id": "06d04fb0-fe0e-4a6a-b958-061fb38a9f9c",
            
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  "license_id": "cc-nc",
            
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  "license_title": "Creative Commons Non-Commercial (Any)",
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  "license_title": "Creative Commons Non-Commercial (Any)",
            
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  "license_url": "http://creativecommons.org/licenses/by-nc/2.0/",
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  "license_url": "http://creativecommons.org/licenses/by-nc/2.0/",
            
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  "maintainer": "Dermot Kerr",
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  "maintainer": "Dermot Kerr",
            
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  "maintainer_email": "d.kerr@ulster.ac.uk",
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  "maintainer_email": "d.kerr@ulster.ac.uk",
            
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  "metadata_modified": "2026-03-18T17:21:13.279066",
            
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  "name": 
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  "name": 
            
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lster-university--anonymised-indoor-air-quality-benchmarking-dataset",
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lster-university--anonymised-indoor-air-quality-benchmarking-dataset",
            
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  "notes": "# Anonymised Indoor Air Quality Benchmarking Dataset -- 
19
  "notes": "# Anonymised Indoor Air Quality Benchmarking Dataset -- 
            
20
Manufacturing Facilities\r\n\r\n## Description\r\n\r\nThis dataset 
20
Manufacturing Facilities\r\n\r\n## Description\r\n\r\nThis dataset 
            
21
contains anonymised benchmarking indicators derived from\r\nindoor 
21
contains anonymised benchmarking indicators derived from\r\nindoor 
            
22
air\u2011quality sensor measurements collected from 
22
air\u2011quality sensor measurements collected from 
            
23
manufacturing\r\nfacilities participating in the **Smart Manufacturing 
23
manufacturing\r\nfacilities participating in the **Smart Manufacturing 
            
24
Data Hub (SMDH)**\r\nprogramme.\r\n\r\nThe dataset summarises 
24
Data Hub (SMDH)**\r\nprogramme.\r\n\r\nThe dataset summarises 
            
25
air\u2011quality performance across multiple companies\r\nand sectors 
25
air\u2011quality performance across multiple companies\r\nand sectors 
            
26
using aggregated environmental indicators and 
26
using aggregated environmental indicators and 
            
27
statistical\r\nbenchmarking metrics. The purpose of the dataset is to 
27
statistical\r\nbenchmarking metrics. The purpose of the dataset is to 
            
28
enable\r\n**cross\u2011company environmental performance comparison 
28
enable\r\n**cross\u2011company environmental performance comparison 
            
29
while preserving\r\ncompany anonymity**.\r\n\r\nThe dataset focuses on 
29
while preserving\r\ncompany anonymity**.\r\n\r\nThe dataset focuses on 
            
30
indoor air\u2011quality conditions derived from **CO\u2082\r\nand 
30
indoor air\u2011quality conditions derived from **CO\u2082\r\nand 
            
31
Total Volatile Organic Compounds (TVOC)** sensor measurements. 
31
Total Volatile Organic Compounds (TVOC)** sensor measurements. 
            
32
These\r\nmeasurements are converted into air\u2011quality indices and 
32
These\r\nmeasurements are converted into air\u2011quality indices and 
            
33
benchmarking\r\nindicators that allow comparison across facilities 
33
benchmarking\r\nindicators that allow comparison across facilities 
            
34
with different\r\noperational 
34
with different\r\noperational 
            
35
-------------------------------------------------------------\r\n\r\n# 
35
-------------------------------------------------------------\r\n\r\n# 
            
36
Data Source\r\n\r\nThe data originates from **IFM environmental 
36
Data Source\r\n\r\nThe data originates from **IFM environmental 
            
37
sensors installed in\r\nparticipating manufacturing facilities**. Raw 
37
sensors installed in\r\nparticipating manufacturing facilities**. Raw 
            
38
sensor measurements were\r\nprocessed and aggregated before inclusion 
38
sensor measurements were\r\nprocessed and aggregated before inclusion 
            
39
in this anonymised 
39
in this anonymised 
            
40
-------------------------------------------------------------\r\n\r\n# 
40
-------------------------------------------------------------\r\n\r\n# 
            
41
Anonymisation\r\n\r\nTo protect company confidentiality:\r\n\r\n-   
41
Anonymisation\r\n\r\nTo protect company confidentiality:\r\n\r\n-   
            
42
Company names are replaced with anonymised identifiers 
42
Company names are replaced with anonymised identifiers 
            
43
(`company1`,\r\n    `company2`, etc.).\r\n-   Sector labels are 
43
(`company1`,\r\n    `company2`, etc.).\r\n-   Sector labels are 
            
44
represented as coded identifiers (`sector_code`).\r\n-   No 
44
represented as coded identifiers (`sector_code`).\r\n-   No 
            
45
facility\u2011level identifiers or timestamps that could reveal\r\n    
45
facility\u2011level identifiers or timestamps that could reveal\r\n    
            
46
operational patterns are included.\r\n-   The dataset contains 
46
operational patterns are included.\r\n-   The dataset contains 
            
47
**aggregated benchmarking metrics rather than\r\n    raw sensor 
47
**aggregated benchmarking metrics rather than\r\n    raw sensor 
            
48
-------------------------------------------------------------\r\n\r\n# 
48
-------------------------------------------------------------\r\n\r\n# 
            
49
Dataset Structure\r\n\r\nEach row represents a **company\u2011level 
49
Dataset Structure\r\n\r\nEach row represents a **company\u2011level 
            
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observation for a specific time\r\nperiod**, including environmental 
50
observation for a specific time\r\nperiod**, including environmental 
            
51
indicators and benchmarking metrics\r\nused to compare 
51
indicators and benchmarking metrics\r\nused to compare 
            
52
air\u2011quality performance across companies.\r\n\r\nThe dataset 
52
air\u2011quality performance across companies.\r\n\r\nThe dataset 
            
53
includes:\r\n\r\n-   Environmental performance indicators\r\n-   
53
includes:\r\n\r\n-   Environmental performance indicators\r\n-   
            
54
Normalised benchmarking metrics\r\n-   Data coverage indicators\r\n-   
54
Normalised benchmarking metrics\r\n-   Data coverage indicators\r\n-   
            
55
Statistical benchmarking metrics (z\u2011scores)\r\n-   Relative 
55
Statistical benchmarking metrics (z\u2011scores)\r\n-   Relative 
            
56
performance 
56
performance 
            
57
-------------------------------------------------------------\r\n\r\n# 
57
-------------------------------------------------------------\r\n\r\n# 
            
58
Analytical Methodology\r\n\r\n1.  **Sensor Data Preparation**\r\n    -   
58
Analytical Methodology\r\n\r\n1.  **Sensor Data Preparation**\r\n    -   
            
59
Cleaning and validation of IFM sensor measurements\r\n    -   Removal 
59
Cleaning and validation of IFM sensor measurements\r\n    -   Removal 
            
60
of missing or inconsistent observations\r\n2.  **Indicator 
60
of missing or inconsistent observations\r\n2.  **Indicator 
            
61
Construction**\r\n    -   Conversion of CO\u2082 and TVOC measurements 
61
Construction**\r\n    -   Conversion of CO\u2082 and TVOC measurements 
            
62
into air\u2011quality index\r\n        (AQI) metrics\r\n3.  
62
into air\u2011quality index\r\n        (AQI) metrics\r\n3.  
            
63
**Benchmarking Normalisation**\r\n    -   Normalisation of AQI metrics 
63
**Benchmarking Normalisation**\r\n    -   Normalisation of AQI metrics 
            
64
to enable cross\u2011company comparison\r\n4.  **Coverage 
64
to enable cross\u2011company comparison\r\n4.  **Coverage 
            
65
Assessment**\r\n    -   Calculation of data availability metrics to 
65
Assessment**\r\n    -   Calculation of data availability metrics to 
            
66
ensure fair\r\n        benchmarking\r\n5.  **Statistical 
66
ensure fair\r\n        benchmarking\r\n5.  **Statistical 
            
67
Benchmarking**\r\n    -   Calculation of **z\u2011scores** to quantify 
67
Benchmarking**\r\n    -   Calculation of **z\u2011scores** to quantify 
            
68
relative performance\r\n        compared with peer companies\r\n6.  
68
relative performance\r\n        compared with peer companies\r\n6.  
            
69
**Performance Classification**\r\n    -   Classification of company 
69
**Performance Classification**\r\n    -   Classification of company 
            
70
performance as **Better**,\r\n        **Average**, or **Worse** 
70
performance as **Better**,\r\n        **Average**, or **Worse** 
            
71
relative to 
71
relative to 
            
72
-------------------------------------------------------------\r\n\r\n# 
72
-------------------------------------------------------------\r\n\r\n# 
            
73
Intended Use\r\n\r\nThis dataset supports:\r\n\r\n-   
73
Intended Use\r\n\r\nThis dataset supports:\r\n\r\n-   
            
74
Cross\u2011company environmental benchmarking\r\n-   Manufacturing 
74
Cross\u2011company environmental benchmarking\r\n-   Manufacturing 
            
75
environmental performance analysis\r\n-   Indoor air\u2011quality 
75
environmental performance analysis\r\n-   Indoor air\u2011quality 
            
76
research\r\n-   Development of environmental performance 
76
research\r\n-   Development of environmental performance 
            
77
dashboards\r\n-   Academic or industrial research into workplace 
77
dashboards\r\n-   Academic or industrial research into workplace 
            
78
environmental\r\n    
78
environmental\r\n    
            
79
-------------------------------------------------------------\r\n\r\n# 
79
-------------------------------------------------------------\r\n\r\n# 
            
80
Limitations\r\n\r\n-   The dataset contains **derived benchmarking 
80
Limitations\r\n\r\n-   The dataset contains **derived benchmarking 
            
81
indicators rather than\r\n    raw sensor readings**.\r\n-   Results 
81
indicators rather than\r\n    raw sensor readings**.\r\n-   Results 
            
82
should be interpreted as **relative benchmarking indicators\r\n    
82
should be interpreted as **relative benchmarking indicators\r\n    
            
83
rather than regulatory compliance assessments**.\r\n-   Sector codes 
83
rather than regulatory compliance assessments**.\r\n-   Sector codes 
            
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are anonymised and do not represent specific\r\n    industries.",
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are anonymised and do not represent specific\r\n    industries.",
            
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robotics, computer vision, and computational intelligence. Translating 
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robotics, computer vision, and computational intelligence. Translating 
            
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research into technologies that catalyse innovation in small and large 
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research into technologies that catalyse innovation in small and large 
            
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enterprises, we have been instrumental in attracting inward investment 
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enterprises, we have been instrumental in attracting inward investment 
            
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and developing the knowledge economy. Ulster lead SMDH, lead the 
94
and developing the knowledge economy. Ulster lead SMDH, lead the 
            
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virtual manufacturing platform and contribute to data science, 
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virtual manufacturing platform and contribute to data science, 
            
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roll-out and marketing.",
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      "display_name": "Sensor-Air_Quality",
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      "name": "Sensor-Air_Quality",
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    {
            
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      "name": "Sensor-Air_Quality",
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      "name": "Sensor-Air_Quality",
            
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  "title": "Anonymised Indoor Air Quality Benchmarking Dataset",
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  "title": "Anonymised Indoor Air Quality Benchmarking Dataset",
            
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