Data Openness Badges

1.   Objective and Overview

The aim of the data openness badges is to reward authors whose articles exhibit higher levels of data openness, accessibility, and interoperability between data formats beyond the strict minimum for publication. The Journal of Industrial Ecology and the International Society for Industrial Ecology thus strive to promote the contribution of reusable and interoperable data in a wide range of research contexts (Hertwich et al. 2018).

The badge is optional. It aims to be flexible, with two dimensions rewarding (1) the extent of data contribution and (2) the level of data accessibility, that is, the interoperability and reusability of the data supplied. It also aims to be progressive, with two levels, gold and silver, for each dimension. As illustrated below, these two dimensions and two levels lead to four distinct badges.

The following table summarizes the evaluation criteria, which are then explained in greater detail in the following sections.

	DATA CONTRIBUTION	DATA ACCESSIBILITY
Gold	Entire system description is contributed	Human & machine readable, and directly importable into free analysis software
Silver	Option 1: Detailed, useful, and self‐contained descriptions of significant parts of the system; Option 2: Total exchanges of the technological system with the environment published in an uncharacterized form	Human & machine readable, or directly importable into free analysis software

2.   General Requirements

If you seek a data badge, please complete the data badge questionnaire and upload it with other files related to your manuscript when you submit a revised manuscript in response to an initial decision, i.e., after the first round of peer review.

Own data: To qualify for either badge, you must provide a URL, DOI, or other permanent path for accessing the specified information in a public, open-access, long-term repository. Exceptions may be made for exceptionally small data sets, which could be published as supporting information with the published JIE article.

Other qualifying data/materials repositories are listed at http://re3data.org/. Personal websites, most departmental websites, and GitHub do not qualify as repositories. Zenodo is recommended for industrial ecology research. Please also consider using the industrial ecology tag in Zenodo.

Proprietary data and data requiring paid licensure: For proprietary data and data such as that from ecoinvent accessible only under paid license, all information needed to identify the data used in the paper must be provided. That includes naming the exact database version (e.g., ecoinvent v3.5, cut-off allocation) and all referenced processes (e.g., ‘sheet rolling copper, RoW’, UUID: ‘4721d5addda822f0cbc0978543bbaad3’).

Licensing of data: An open license for the deposited data is required that allows others to copy, distribute, and make use of the data while allowing the licensor to retain credit and copyright as applicable. Creative Commons has defined several licenses for this purpose, which are described at www.creativecommons.org/licenses. CC0 or CC-BY 4.0 are recommended.

Third party or confidential data: Authors who wish to publicly post third-party content in their data must have the proper authority or permission agreement in order to do so. There are circumstances in which it is not possible or advisable to share any or all data publicly. For example, sharing participants’ data could violate confidentiality or commercial database licensing agreements that restrict their sharing.

3.   Data Contribution

The badge rewards contribution of quantitative and qualitative data on industrial ecology that can potentially be reused in other studies.

Data Contribution: Gold

The gold level indicates that the entire system description is published at the same level of resolution and completeness as was used by the authors to calculate their results.

• These system descriptions notably include, as applicable, the descriptions of all processes, activities, agents, objects, flows, stocks, exchanges with the biophysical environment, system boundaries, and behaviors and actions, along with links to external or secondary data sets (including licensed databases).
• All the primary data and the necessary data citations are made available such that the results could be reproduced, although the authors are not required to share all detailed calculation and analysis steps that were performed using the system description.
  • Example 1: A global input-output footprint analysis links to an open and accessible system description including the matrix of technical requirements, exchanges with the environment, final consumption, and value added, as used in the footprint calculations.
  • Example 2: An LCA study makes available its foreground (all process descriptions based on own research and primary data) and also publishes all the links to a published data set (e.g., ecoinvent) for all secondary data used.

Data Contribution: Silver

The criterion for achieving the silver data contribution level is that a significant data contribution be made by the work. Two options for how this can be achieved and examples are provided below.

Option 1: In situations where authors cannot share their entire system description, for example when facing confidentiality issues, they can nonetheless share the detailed description of the non-sensitive parts of the system.

• Published datasets would include, for example, complete process descriptions, extensive quantifications of stocks and flows, and tabulated product compositions.
• The intent is that a significant portion of the system analyzed is described in a self-contained manner with useful metadata allowing for the unambiguous interpretation of each data point within the published part of the system description.
  • Example 1: An LCA study of Li-ion battery use may be unable to fully describe the assembly of battery cells because the data on energy requirements to do this are commercially sensitive. This analysis may nonetheless usefully characterize unit processes describing in full detail the production of the anodes, cathodes, and electrolytes, thereby contributing useful primary data to the community.
  • Example 2: Similarly, it may not be possible to publish an MFA model in full because it includes data describing material stocks that are commercially sensitive. Nonetheless, the authors may share an extensive table of the mass and elemental composition for many of the stocks and flows in the model, which will likely prove useful in other research.

Option 2: The second approach to fulfilling the objective of the silver level applies to studies that link a technological system to a damage or an impact (e.g., global warming) through multiple types of interactions with the environment (emissions and resource use, e.g., releases of carbon dioxide [CO₂], methane [CH₄], and nitrous oxide [N₂O]). Because of the diversity of characterization methods to translate interactions into impacts, the badge recognizes the benefits for the community of publishing the total interactions of the technological system with the environment in a readily reusable and uncharacterized format.

• Example 1: An Input-Output analysis calculating the carbon footprint of nations would provide the results not only in terms of characterized CO₂-equivalents, but also in terms of the total emissions of the different greenhouse gases (CO₂,CH₄,N₂O, etc.)
• Example 2: In the case of an LCA study, a complete LCI of elementary flows would be published at the systems process level. That means the study would contain the cumulative total for the whole life cycle of each type of emission flow and each type of resource use.

3.   Data accessibility

This badge promotes the formatting and structuring of data such that it facilitates reuse, efficient data integration, and interoperability with free analysis software.

Data Accessibility: Gold

For the gold level, the system description must be formatted and archived such that it is (1) both human and machine readable, and (2) directly importable into free software capable of completing the relevant IE analysis.

• Human and machine readability: The system is described such that it can be read and understood by humans in plain text files. Examples of such file formats include plain text, comma separated values (csv), json, and xml files, but compressed versions of these formats are also accepted, such as xlsx and ods spreadsheet formats, but not the proprietary xlsb or xls formats. The data should also be machine readable in the sense that a relevant software can readily distinguish words from numbers, recognize table structures, etc. For example, a system description in a spreadsheet is machine readable, whereas a system description in PDF or word processing formats (.docx, odt, etc.) is not.

https://is4ie.org/

	Machine readable	Not machine readable
Human readable	txt, csv, json, xml, xlsx, ods	.docx, .odt
Not human readable	.xls, xlsb	PDF, .doc

• Direct imports in relevant free software: The relevant analyses can be directly performed on the system description without requiring payment for software. Many situations fulfill this objective, for example:
  • Example 1. A system description is exported in a nonproprietary structured format (e.g., ecospold XML files) that can be imported directly into free software (e.g., openLCA and brightway2), which can directly perform the relevant analysis (e.g., LCA calculations).
  • Example 2. Both the data and the calculations of the study are fully embedded in a spreadsheet (e.g., ods, xlsx file), requiring no external software to complete the analysis. If this spreadsheet can be opened in a free office suite (e.g., LibreOffice) without loss of functionality, it fulfills the requirement.
  • Example 3. A study publishes not only the data, but also the (free) software to parse and analyze it (e.g., a Python script).

Data Accessibility: Silver

For this badge, the system description must be formatted such that it can fulfill at least one of the two criteria of the Accessibility Gold badge: It must either be directly readable by humans and machines, or be directly importable in a relevant free analysis software.

Examples:

• .zmfa files produces by the free MFA software STAN (Accessible with free software, but not human readable).
• A Microsoft Excel xlsx spreadsheet with advanced computations/macros that cause compatibility issues (human and machine readable, but not importable without loss of functionality in free software, such as LibreOffice).