Development of a quality evaluation framework for consumer generated domestic food preparation data: D6.3
Development of a quality evaluation framework for consumer generated domestic food preparation data: D6.3
This deliverable formulates a set of quality criteria for the evaluation of this consumergenerated food preparation data in terms of its scientific relevance and technical and legal governance. These three area were selected as indicators of quality as they allow for the assessment of data in relation to key questions relating to domestic food preparation behaviour (i.e., What/Who/Why/How and Where). This is, in addition to assessing the legal limitations, organizational restrictions, confidentiality and privacy concerns related to collection, integration and dissemination of consumer-generated data and the technical protocols and standards for data access and data processing. Information about these topics is crucial for developing the blueprint of a data platform, such as RICHFIELDS, as well as for its data governance structure.In addition to providing a framework for the evaluation of data quality, the result of this deliverable also provides structure and guidance for the data collection process of deliverable 6.1, which is an inventory of consumer-generated food preparation data tools. Morespecifically, this quality framework provides an operationalised definition for each quality criteria in the form of a set of relevant questions that should be answered for each tool included in the RICHFIELDS Inventory Management System (RIMS). RIMS is an online management system for the storage and assessment of tools that produce consumergenerated data on the purchase, preparation, consumption of food and/or beverages and their associated lifestyle data that could potentially be of use to social science researchers.RIMS comprises two component parts; [1] a typology of the tools stored within the inventory, and [2] a list of quality criteria against which each tool can be evaluated. The typology is a scheduled framework categorizing the food preparation tools according to defined groupings. The current typology for food preparation is a four-level model. The firstlevel is the overall domain - in this instance, domestic food preparation. The second level reflects the goal of underlying motivation of the behaviour captured by the tool. The third level reflects the specific behaviours captured by the tool and the final level is indicative of the recorded behaviour. The identified quality criteria are based on aspects of health and lifestyle specific to food consumption. Preparation behaviours are in some respect quite distinct and different from food intake, as they frequently require a degree of pre-behaviour decision making such as looking up a recipe. In this regard the current quality criteria don’t sufficiently capture ‘intended’ behaviours, only enacted behaviours. The next step for these criteria is to test them with the tools currently in RIMS. However, for these tools it will be challenging to validate them according to current criteria at the level required for the inventory presented in deliverable 6.1. As for many tools, it is not possible to respond to these the criteria, particularly with the feasibility parameters worked to in this exercise. That is to say, it is not possible to easily identify certain aspects of a tool’s quality without either expert knowledge of the fields of ICT and Law, and without the downloading and the downloading and testing of a tool, the examination of a tool’s data structure and/or the examination of a hosting data infrastructure. This is therefore a potentially time consuming and costly process to validate the quality of consumer-generated data produced via a tool.
Klepacz, Naomi
31061121-a4ac-4a6b-a110-bcc6afd554fd
Maringer, Marcus
14c80c9e-a943-4d91-848d-d647cc833ce7
Ekman, Susanne
039751fa-e5cf-466c-89ff-a4fa99556946
Normann, A.
dd0250cf-d8fd-4689-a597-4a0bdd672347
Verain, Muriel
d67e3115-bccf-4199-ad21-b7c9f9f106c7
Geelen, Anouk
a1ccaee8-a603-462e-bbbf-57e16b9af3d5
Raats, Monique M.
50c792ae-b24d-4e84-b9e6-5e7d475c7126
2016
Klepacz, Naomi
31061121-a4ac-4a6b-a110-bcc6afd554fd
Maringer, Marcus
14c80c9e-a943-4d91-848d-d647cc833ce7
Ekman, Susanne
039751fa-e5cf-466c-89ff-a4fa99556946
Normann, A.
dd0250cf-d8fd-4689-a597-4a0bdd672347
Verain, Muriel
d67e3115-bccf-4199-ad21-b7c9f9f106c7
Geelen, Anouk
a1ccaee8-a603-462e-bbbf-57e16b9af3d5
Raats, Monique M.
50c792ae-b24d-4e84-b9e6-5e7d475c7126
Klepacz, Naomi, Maringer, Marcus, Ekman, Susanne, Normann, A., Verain, Muriel, Geelen, Anouk and Raats, Monique M.
(2016)
Development of a quality evaluation framework for consumer generated domestic food preparation data: D6.3
European Commission
31pp.
Record type:
Monograph
(Project Report)
Abstract
This deliverable formulates a set of quality criteria for the evaluation of this consumergenerated food preparation data in terms of its scientific relevance and technical and legal governance. These three area were selected as indicators of quality as they allow for the assessment of data in relation to key questions relating to domestic food preparation behaviour (i.e., What/Who/Why/How and Where). This is, in addition to assessing the legal limitations, organizational restrictions, confidentiality and privacy concerns related to collection, integration and dissemination of consumer-generated data and the technical protocols and standards for data access and data processing. Information about these topics is crucial for developing the blueprint of a data platform, such as RICHFIELDS, as well as for its data governance structure.In addition to providing a framework for the evaluation of data quality, the result of this deliverable also provides structure and guidance for the data collection process of deliverable 6.1, which is an inventory of consumer-generated food preparation data tools. Morespecifically, this quality framework provides an operationalised definition for each quality criteria in the form of a set of relevant questions that should be answered for each tool included in the RICHFIELDS Inventory Management System (RIMS). RIMS is an online management system for the storage and assessment of tools that produce consumergenerated data on the purchase, preparation, consumption of food and/or beverages and their associated lifestyle data that could potentially be of use to social science researchers.RIMS comprises two component parts; [1] a typology of the tools stored within the inventory, and [2] a list of quality criteria against which each tool can be evaluated. The typology is a scheduled framework categorizing the food preparation tools according to defined groupings. The current typology for food preparation is a four-level model. The firstlevel is the overall domain - in this instance, domestic food preparation. The second level reflects the goal of underlying motivation of the behaviour captured by the tool. The third level reflects the specific behaviours captured by the tool and the final level is indicative of the recorded behaviour. The identified quality criteria are based on aspects of health and lifestyle specific to food consumption. Preparation behaviours are in some respect quite distinct and different from food intake, as they frequently require a degree of pre-behaviour decision making such as looking up a recipe. In this regard the current quality criteria don’t sufficiently capture ‘intended’ behaviours, only enacted behaviours. The next step for these criteria is to test them with the tools currently in RIMS. However, for these tools it will be challenging to validate them according to current criteria at the level required for the inventory presented in deliverable 6.1. As for many tools, it is not possible to respond to these the criteria, particularly with the feasibility parameters worked to in this exercise. That is to say, it is not possible to easily identify certain aspects of a tool’s quality without either expert knowledge of the fields of ICT and Law, and without the downloading and the downloading and testing of a tool, the examination of a tool’s data structure and/or the examination of a hosting data infrastructure. This is therefore a potentially time consuming and costly process to validate the quality of consumer-generated data produced via a tool.
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Published date: 2016
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Local EPrints ID: 483712
URI: http://eprints.soton.ac.uk/id/eprint/483712
PURE UUID: 2a30a007-89a5-4f57-bbd7-a825493279de
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Date deposited: 03 Nov 2023 17:57
Last modified: 18 Mar 2024 04:07
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Contributors
Author:
Naomi Klepacz
Author:
Marcus Maringer
Author:
Susanne Ekman
Author:
A. Normann
Author:
Muriel Verain
Author:
Anouk Geelen
Author:
Monique M. Raats
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