Class DQSystem

A data quality system (DQS) in openLCA describes a pedigree matrix of $m$ data quality indicators (DQIs) and $n$ data quality scores (DQ scores). Such a system can then be used to assess the data quality of processes and exchanges by tagging them with an instance of the system $D$ where $D$ is a $m * n$ matrix with an entry $d_{ij}$ containing the value of the data quality score $j$ for indicator $i$. As each indicator in $D$ can only have a single score value, $D$ can be stored in a vector $d$ where $d_i$ contains the data quality score for indicator $i$. The possible values of the data quality scores are defined as a linear order $1 \dots n$. In openLCA, the data quality entry $d$ of a process or exchange is stored as a string like (3;2;4;n.a.;2) which means the data quality score for the first indicator is 3, for the second 2 etc. A specific value is n.a. which stands for _not applicable_. In calculations, these data quality entries can be aggregated in different ways. For example, the data quality entry of a flow $f$ with a contribution of 0.5 kg and a data quality entry of (3;2;4;n.a.;2) in a process $p$ and a contribution of 1.5 kg and a data quality entry of (2;3;1;n.a.;5) in a process $q$ could be aggregated to (2;3;2;n.a.;4) by applying an weighted average and rounding. Finally, custom labels like A, B, C, ... or Very good, Good, Fair, ... for the DQ scores can be assigned by the user. These labels are then displayed instead of 1, 2, 3 ... in the user interface or result exports. However, internally the numeric values are used in the data model and calculations.

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Properties:

hasUncertainties boolean
source Ref[Source]
indicators List[DQIndicator]

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Properties from CategorizedEntity:

category Ref[Category] The category of the entity.
tags List[string] A list of optional tags. A tag is just a string which should not contain commas (and other special characters).
library string If this entity is part of a library, this field contains the identifier of that library. The identifier is typically just the combination of the library name and version.

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Properties from RootEntity:

name string The name of the entity.
description string The description of the entity.
version string A version number in MAJOR.MINOR.PATCH format where the MINOR and PATCH fields are optional and the fields may have leading zeros (so 01.00.00 is the same as 1.0.0 or 1).
lastChange dateTime The timestamp when the entity was changed the last time.

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JSON-LD Example

{
    "@context": "http://greendelta.github.io/olca-schema/context.jsonld",
    "@type": "DQSystem",
    "@id": "e7ac7cf6-5457-453e-99f9-d889826fffe8",
    "name": "ecoinvent data quality system",
    "version": "00.00.000",
    "hasUncertainties": true,
    "indicators": [
        {
            "@type": "DQIndicator",
            "name": "Temporal correlation",
            "position": 3,
            "scores": [
                {
                    "@type": "DQScore",
                    "position": 4,
                    "description": "Less than 15 years of difference to the time period of the data set",
                    "uncertainty": 1.2
                },
                {
                    "@type": "DQScore",
                    "position": 3,
                    "description": "Less than 10 years of difference to the time period of the data set",
                    "uncertainty": 1.1
                },
                {
                    "@type": "DQScore",
                    "position": 5,
                    "description": "Age of data unknown or more than 15 years of difference to the time period of the data set",
                    "uncertainty": 1.5
                },
                {
                    "@type": "DQScore",
                    "position": 1,
                    "description": "Less than 3 years of difference to the time period of the data set",
                    "uncertainty": 1.0
                },
                {
                    "@type": "DQScore",
                    "position": 2,
                    "description": "Less than 6 years of difference to the time period of the data set",
                    "uncertainty": 1.03
                }
            ]
        },
        {
            "@type": "DQIndicator",
            "name": "Completeness",
            "position": 2,
            "scores": [
                {
                    "@type": "DQScore",
                    "position": 1,
                    "description": "Representative data from all sites relevant for the market considered, over and adequate period to even out normal fluctuations",
                    "uncertainty": 1.0
                },
                {
                    "@type": "DQScore",
                    "position": 3,
                    "description": "Representative data from only some sites (\u003c\u003c 50%) relevant for the market considered or \u003e 50% of sites but from shorter periods",
                    "uncertainty": 1.05
                },
                {
                    "@type": "DQScore",
                    "position": 4,
                    "description": "Representative data from only one site relevant for the market considered or some sites but from shorter periods",
                    "uncertainty": 1.1
                },
                {
                    "@type": "DQScore",
                    "position": 5,
                    "description": "Representativeness unknown or data from a small number of sites and from shorter periods",
                    "uncertainty": 1.2
                },
                {
                    "@type": "DQScore",
                    "position": 2,
                    "description": "Representative data from \u003e 50% of the sites relevant for the market considered, over an adequate period to even out normal fluctuations",
                    "uncertainty": 1.02
                }
            ]
        },
        {
            "@type": "DQIndicator",
            "name": "Geographical correlation",
            "position": 4,
            "scores": [
                {
                    "@type": "DQScore",
                    "position": 2,
                    "description": "Average data from larger area in which the area under study is included",
                    "uncertainty": 1.01
                },
                {
                    "@type": "DQScore",
                    "position": 3,
                    "description": "Data from area with similar production conditions",
                    "uncertainty": 1.02
                },
                {
                    "@type": "DQScore",
                    "position": 1,
                    "description": "Data from area under study",
                    "uncertainty": 1.0
                },
                {
                    "@type": "DQScore",
                    "position": 5,
                    "description": "Data from unknown or distinctly different area (North America instead of Middle East, OECD-Europe instead of Russia)",
                    "uncertainty": 1.1
                },
                {
                    "@type": "DQScore",
                    "position": 4,
                    "description": "Data from area with slightly similar production conditions",
                    "uncertainty": 1.05
                }
            ]
        },
        {
            "@type": "DQIndicator",
            "name": "Further technological correlation",
            "position": 5,
            "scores": [
                {
                    "@type": "DQScore",
                    "position": 1,
                    "description": "Data from enterprises, processes and materials under study",
                    "uncertainty": 1.0
                },
                {
                    "@type": "DQScore",
                    "position": 4,
                    "description": "Data on related processes or materials",
                    "uncertainty": 1.5
                },
                {
                    "@type": "DQScore",
                    "position": 2,
                    "description": "Data from processes and materials under study (i.e. identical technology) but from different enterprises",
                    "uncertainty": 1.05
                },
                {
                    "@type": "DQScore",
                    "position": 3,
                    "description": "Data from processes and materials under study but from different technology",
                    "uncertainty": 1.2
                },
                {
                    "@type": "DQScore",
                    "position": 5,
                    "description": "Data on related processes on laboratory scale or from different technology",
                    "uncertainty": 2.0
                }
            ]
        },
        {
            "@type": "DQIndicator",
            "name": "Reliability",
            "position": 1,
            "scores": [
                {
                    "@type": "DQScore",
                    "position": 3,
                    "description": "Non-verified data partly based on qualified estimates",
                    "uncertainty": 1.1
                },
                {
                    "@type": "DQScore",
                    "position": 4,
                    "description": "Qualified estimate (e.g. by industrial expert)",
                    "uncertainty": 1.2
                },
                {
                    "@type": "DQScore",
                    "position": 5,
                    "description": "Non-qualified estimates",
                    "uncertainty": 1.5
                },
                {
                    "@type": "DQScore",
                    "position": 1,
                    "description": "Verified data based on measurements",
                    "uncertainty": 1.0
                },
                {
                    "@type": "DQScore",
                    "position": 2,
                    "description": "Verified data partly based on assumptions or non-verified data based on measurements",
                    "uncertainty": 1.05
                }
            ]
        }
    ]
}