A data extraction template for the behaviour change intervention ontology

Background The Behaviour Change Intervention Ontology (BCIO) aims to improve the clarity, completeness and consistency of reporting within intervention descriptions and evidence synthesis. However, a recommended method for transparently annotating intervention evaluation reports using the BCIO does not currently exist. This study aimed to develop a data extraction template for annotating using the BCIO. Methods The BCIO data extraction template was developed in four stages: i) scoping review of papers citing component ontologies within the BCIO, ii) development of a draft template, iii) piloting and revising the template, and iv) dissemination and maintenance of the template. Results A prototype data extraction template using Microsoft Excel was developed based on BCIO annotations from 14 papers. The ‘BCIO data extraction template v1’ was produced following piloting and revision, incorporating a facility for user feedback. Discussion This data extraction template provides a single, accessible resource to extract all necessary characteristics of behaviour change intervention scenarios. It can be used to annotate the presence of BCIO entities for evidence synthesis, including systematic reviews. In the future, we will update this template based on feedback from the community, additions of newly published ontologies within the BCIO, and revisions to existing ontologies.


Results
A prototype data extraction template using Microsoft Excel was developed based on BCIO annotations from 14 papers.The 'BCIO data extraction template v1' was produced following piloting and revision, incorporating a facility for user feedback.

Any reports and responses or comments on the
This data extraction template provides a single, accessible resource to extract all necessary characteristics of behaviour change intervention scenarios.It can be used to annotate the presence of BCIO entities for evidence synthesis, including systematic reviews.In the future, we will update this template based on feedback from the community, additions of newly published ontologies within the BCIO, and revisions to existing ontologies.

Plain language summary
Behaviour change interventions are often reported in an inconsistent and incomplete manner in study reports.This makes it difficult to build knowledge and predict outcomes.There is a need for a shared language to describe behaviour change interventions.This need was met using 'ontologies', which are classification systems that represent knowledge in a standardised way.The Behaviour Change Intervention Ontology (BCIO) has been developed to describe the different aspects of interventions in a way that is precise enough for computers as well as humans to 'read' study findings.The BCIO can be used to extract information from study reports for evidence synthesis, such as systematic literature reviews.To meet the need for a resource for annotating (coding) study reports according to the BCIO, we developed a data extraction template.The template was developed in four stages: i) reviewing existing papers using the BCIO, ii) development of a draft template, iii) piloting and revising the template, and iv) dissemination and maintenance of the template.The resulting resource is an accessible, easy-to-use template to assist with specifying the content of published papers reporting interventions and their evaluation.The template will be updated based on user feedback and future revisions to the BCIO.

Introduction
Behaviour change interventions vary considerably in their characteristics including their content and delivery, context (setting and population), target behaviours, and mechanisms of action (Michie & Johnston, 2017).However, interventions are often poorly reported, with inconsistent or ambiguous use of scientific terminology (Ioannidis et al., 2014;Michie et al., 2009).This makes it difficult to replicate and scale up interventions, and to synthesise evidence to build knowledge (Wright et al., 2020).Although reporting guidelines (e.g., Hoffmann et al., 2014;Montgomery et al., 2018) have improved the clarity and completeness of reporting, there is a need for a common, shared vocabulary to standardise the classification of key aspects of behaviour change interventions.
Ontologies can meet this need by integrating knowledge across different disciplines, domains and data types (see Appendix 1 for glossary of terms that are bolded and italicised).Ontologies are formal classification systems for representing the world in terms of classes of entities (anything that exists in the universe) and relations between entities (Arp et al., 2015).
Every entity consists of a label and a formal, unambiguous definition which are specified using logic-based language and unique identifiers, allowing it to be computer-readable (Hastings, 2017).In several scientific fields, ontologies have helped create a common language and a 'controlled vocabulary' (standardised sets of terms) to organise and represent knowledge (Hastings, 2017;Sharp et al., 2023;Smith et al., 2007).The Open Biological and Biomedical Ontology (OBO) Foundry hosts a collection of coordinated, interoperable ontologies (Smith et al., 2007).They follow principles, such as being openly available (see https://obofoundry.org/principles/fp-000-summary.html).The precision of ontologies means that ontologies can support the application of artificial intelligence and machine learning approaches in data extraction, evidence synthesis, and outcome prediction (Hastings et al., 2023;West et al., 2023a).This can reduce research waste and maximise the speed and scale of evidence accumulation.
The Human Behaviour-Change Project (Michie et al., 2017) has developed a Behaviour Change Intervention Ontology (BCIO) as part of constructing an automated 'knowledge system' for gathering information from reports of behaviour change intervention evaluations, and using this information to predict intervention outcomes in novel scenarios (Michie et al., 2021).The BCIO contains more than 1000 entities relating to intervention content (BCTs; Marques et al., 2023), delivery (including mode (Marques et al., 2020), source (Norris et al., 2021), style (Wright et al., 2023) and schedule), engagement, target population, setting (Norris et al., 2020), target behaviour, and mechanisms of action (Schenk et al., 2023).It follows the OBO foundry principles for good practice in ontology development.The upper level BCIO is described in Michie et al. (2021), and the method for developing the lower level (component) ontologies is described in Wright et al. (2020).
The BCIO can be used to enable writing clear and comprehensive study protocols and study reports by using its entity labels and definitions.

Aim
This study aimed to develop a data extraction template for annotating intervention evaluation reports according to the BCIO.

Ethical statement
Ethical approval was granted by the University College London's ethics committee (CEHP/2020/579).
i) Scoping review of papers citing the BCIO Forward citation searching was performed in November 2023 on published papers reporting the development of lower-level ontologies within the BCIO, namely Mode of delivery (Marques et al., 2020), Intervention Setting (Norris et al., 2020), Intervention Source (Norris et al., 2021), Mechanisms of Action (Schenk et al., 2023), Behaviour Change Technique (Marques et al., 2023) and Style of delivery (Wright et al., 2023) ontologies (Papaioannou et al., 2010).Google Scholar was used for forward citation searching, as it is widely viewed as the most comprehensive citation tool (Martín-Martín et al., 2021), including citations from grey literature and preprints (e.g on PsyArXiV, MetaArXiv).Information on papers citing and using each ontology was extracted onto a Microsoft Excel template (Table 1).It included rows for each lower-level ontology and columns for: a) number of papers citing the ontology, b) in-text reporting of annotation using the ontology: number of papers, references and quotes, c) supporting documents featuring annotation using the ontology: number of papers, references, nature of reporting within the supporting documents and links to these documents.Data extraction from all papers citing the ontologies was split between two authors (EN & LZ). ii
ii The template structure was revised to more clearly reflect the structure of ontologies, with levels widthwise, reflecting the structure used by Wuerstl et al. (2023), and papers were presented in columns rather than rows.For each paper, separate columns were added to represent 'entity present': i.e the entity being present in the given paper, and 'evidence' for quotes reflecting entity presence to be pasted directly into the document.Initially, the presence of an entity was indicated by highlighting the cell (as in Wuerstl et al., 2023).However, after external feedback and discussions with the team, it was decided that the presence of an entity should be indicated by a '1' in the relevant cell.This is to enable it to be computer readable.Columns for intervention and comparator conditions were added, to enable both to be annotated.The template allows users to add subsequent columns for each study included in their evidence synthesis.

Strengths and limitations
This template provides an easy-to-use method of annotating according to the BCIO using widely available software (Microsoft Excel).It also allows users to view the ontologies within the BCIO in-full and in a hierarchical structure without using ontology-specific Web Ontology Language (OWL) format (http://humanbehaviourchange.org/ontology/bcio.owl).The template has an ongoing route to improvement based on user suggestions, via the feedback portal.However, a limitation of using Microsoft Excel for this BCIO coding template is that updates to the ontologies within it require manual adjustments and maintenance, as opposed to being automatically integrated into the document.
Manual data extraction can be time-consuming, and a degree of training may be needed to understand and become familiar with the BCIO and its entities before undertaking the data extraction stage.A training programme has been developed and is available at https://www.bciontology.org/training.The training aims to help people use the BCIO effectively and encourage them to build the BCIO into their routine workflows.Developments such as natural language processing, machine learning and artificial intelligence provide new opportunities for automated data extraction, reducing the time necessary to complete or update an evidence synthesis (Jonnalagadda et al., 2015).

Future research using this BCIO data extraction template
The BCIO data extraction template can be used to annotate the BCIO within evidence synthesis studies, as well as to describe new intervention studies.In the future, we will update this template based on feedback from users, additions of newly completed ontologies within the BCIO, and revisions to existing ontologies.When future versions of the template are released, we will change to v2, v3 etc. Users should specify exactly which version they have used in their work.The template URL (https://osf.io/x6afp)will always link to the most current version, with previous version accessible by clicking on the Revisions tab on Open Science Framework.

Consent
Any respondents to the Google Forms feedback portal are asked for their informed consent.Respondent indicate their consent by ticking a box.

Extended data
This project contains the following extended data:

Annotation guidance manual
Written guidance on how to identify and tag pieces of text from intervention evaluation reports with specific codes relating to entities in the ontology, using for example EPPI-Reviewer software.

Class
A category of entities as represented in an ontology.

Entity
Anything that exists or can be imagined, including objects, processes, and their attributes.It Includes mental process, i.e., the process and content of cognitive representations, and emotions.Entities can be represented hierarchically by parent and child classes (see definition of parent class).

Interoperability
Two systems are interoperable to the extent that the data in each system can be used by the other system.Note: An ontology is interoperable with another ontology if it can be used together with the other ontology. http://www.obofoundry.org/principles/fp-010-collaboration.html

Open Biological and Biomedical Ontology (OBO) Foundry
A collective of ontology developers that are committed to collaboration and adherence to shared principles.The mission of the OBO Foundry is to develop a family of interoperable ontologies that are both logically well-formed and scientifically accurate.

Ontology
A standardised representational framework providing a set of entities for the consistent description (or "annotation" or "tagging") of data and information across disciplinary and research community boundaries.

Parent class
A class within an ontology that is hierarchically related to one or more child classes (subclasses) such that all members of the child class are also members of the parent class, and all properties of the parent class are also properties of the child class.

Relation
The manner in which two entities are connected or linked.

Uniform Resource Identifiers (URI)
A string of characters that unambiguously identifies an ontology or an individual entity within an ontology.Having URI identifiers is one of the OBO Foundry principles. http://www.obofoundry.org/principles/fp-003-uris.html

Web Ontology Language (OWL)
A formal language for describing ontologies.It provides methods to model entities of "things", how they relate to each other and the properties they have.OWL is designed to be interpreted by computer programs and is extensively used in the Semantic Web where rich knowledge about web documents and the relations between them are represented using OWL syntax.
https://www.w3.org/TR/owl2-quickreference/The manuscript provides a concise overview of the development process which included a scoping review and pilot test for version 1, with further developments planned for version 2 based on user feedback.

References
I have provided a few comments below on how this manuscript could be further improved.
Methods i) Please describe the inclusion/exclusion criteria and screening process for these papers to enhance transparency and replicability.For example, Table 1 suggests that papers were included if they reported BCIO coding in-text? 1.
iii) "The prototype BCIO data extraction template was piloted to annotate papers using the BCIO in a systematic review of digital interventions" -please reword as this could be mistaken as only papers using the BCIO were eligible for inclusion in the review cited.

2.
Results i) No papers were identified using the Mechanisms of Action, BCT and Style of Delivery ontologies.Please can you describe the process of developing these sections of the prototype template in the absence of this information? 1.
iv) Please can you state the month and year in which the template was made available on OSF.

2.
iv) Great to see the inclusion of a feedback portal here.It is important to note that the 3.
template authors are all familiar with the BCIO.Therefore, piloting of the template by study groups outside of this team is important to improve its usability across disciplines.Has any feedback been received yet?It would be useful to include this, although I appreciate not much time has lapsed since the OSF publication.Discussion 1. Strengths and limitations: In relation to my previous comment, I think it is important to acknowledge that the study authors are familiar with the BCIO and likely this would have influenced the perceived usability of the template.The template will be applicable to interventions across a range of behaviours and disciplines.There is often limited behavioural science expertise within research, policy, and intervention development teams, therefore the feedback will be vital for optimising the accessibility of the tool so that it can achieve its desired impact.

If applicable, is the statistical analysis and its interpretation appropriate? Not applicable
Are all the source data underlying the results available to ensure full reproducibility?Yes

Are the conclusions drawn adequately supported by the results? Partly
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Health Psychology and Behavioural Science I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.I have a few comments for consideration: When exactly was the BCIO published?I expect few published papers are citing the ontologies (yet), rather than the BCTTv1 for example.But my question is why the scoping review of citing papers step was needed to develop the template?Could you elaborate a little on why this was necessary and how it helped?

○
Only one database (Google Scholar) has been used to search citing articles.While Google Scholar may have the largest coverage of the most common databases, it is possible that relevant articles may have not been included so you may wish to mention that.

○
From my understanding, the data extraction template is primarily (at least for now) to be used when conducting systematic reviews of the literature.I have two thoughts about this: (1) I wonder why you choose to publish this template now rather than wait until all ontologies are included?Would this not lead to mixed/incomplete reporting?(2) How will this link to existing reporting guidelines which don't necessarily ask data extraction templates to be published?Are there plans to update existing reporting checklist to ensure this step is completed?

○
To answer questions related to "what works" wouldn't the template need to also include data extraction of primary/secondary outcomes or some measure of effect?I didn't see this mentioned so I am interested to know how you will do this, particularly with respect to predicting behavioural outcomes.

○
Somewhat linked to the previous comment, I understand one of the motivations for the approach was to enable AI and ML to read and synthesis the data and make predictions on outcomes.Are excel documents the best way to do this?You hint towards this in the paper but it's not entirely clear how this will be realised and I think it would be good to expand on this.If this is the first step in the process, what is the roadmap going forward?
○ Is it expected that authors will also use and publish the excel template when describing the development of interventions and how will that impact on the publication process in terms of reporting standards etc? ○ I'm wondering whether you can provide some brief advice on the 'how to use' highlights?I appreciate there are detailed manuals, but this paper could highlight the key points for readers.For example, with mode of delivery, things can get complicated with digital interventions -how do you distinguish between mobile device BCIO:011012 and mobile app BCIO:011028 and even messaging BCIO:011024?In the case of a whatsapp intervention, should all three be coded?Some key considerations would be helpful in this manuscript.The labeling of the template as "v1" could also be reflected in the title.1.
One thought I had reading this paper is that with the development of new ontologies, each of which will have its own guide for coding, using this template in an Excel format will become increasingly cumbersome.Surely, the way forward would be to develop a free software where all the ontologies and the user guide for each would be integrated in a userfriendly way?Something to perhaps consider mentioning in the Discussion.

2.
In the abstract, it would be useful for the reader to know what ontologies are included in the template.Also, consider changing "facility" to "option".

3.
Introduction: In the second paragraph it is mentioned that ontologies follow principles but only one is mentioned (being openly available).Maybe the phrasing should be changed to "one principle the ontologies should follow is…" or something similar.

4.
Method/Results: Can the authors report the inter-rater agreement in the double-coding they did in the piloting phases?I was also surprised to read the statement that "Definitions and unique IDs for ontology entities were added".Which ontologies were altered and how exactly?Have the authors who developed these ontologies being involved in such changes?More information here would be useful, as this reads like a substantial change.Having used some of these ontologies when conducting systematic reviews, I believe the development of this data extraction template will be very useful for assisting with annotation in evidence syntheses and for the reporting of intervention studies.

Is the work clearly and accurately presented and does it cite the current literature? Yes
Overall, the article is well-structured, clearly written, and makes a valuable contribution to the field of behaviour change.The suggested corrections below are minor and aim to improve its clarity and readability.

Abstract:
The phrase in the results section "The 'BCIO data extraction template v1' was produced following piloting and revision, incorporating a facility for user feedback.",could be clearer.It would be helpful to specify what is meant by "incorporating a facility for user feedback".

Methods:
In the section 'iii) Piloting and revising the data extraction template', I suggest adding the word 'were' in the sentence: "Papers in this systematic review were double-coded using the ontologies by two authors (HF & EN), and appropriate revisions made".The revised sentence should read: "… and appropriate revisions were made".

Results:
There is a typo in section 'iv) Dissemination and maintenance of data extraction template', "c) Have you developed and alternative template that you wish to share?".The word "and" should be replaced by "an".Discussion: I suggest clarifying earlier in the article that users should specify which version they have used in their work.

Consent:
There is a typo in the sentence 'Any respondents to the Google Forms feedback portal are asked for their informed consent.Respondent indicate their consent by ticking a box.'The word "respondent" should be pluralised to "respondents".

Is the work clearly and accurately presented and does it cite the current literature? Yes
Is the study design appropriate and is the work technically sound?Yes

Are sufficient details of methods and analysis provided to allow replication by others? Yes
If applicable, is the statistical analysis and its interpretation appropriate?Not applicable Are all the source data underlying the results available to ensure full reproducibility?Yes

Are the conclusions drawn adequately supported by the results? Yes
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: behaviour change, health psychology I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.
Arp R, Smith B, Spear AD: Building ontologies with basic formal ontology.MIT Press, 2015.Publisher Full Text Encantado J, Palmeira AL, Silva C, et al.: What goes on in digital behaviour change interventions for weight loss maintenance targeting physical activity: A scoping review.Digit Health.2022; 8: 20552076221129089.PubMed Abstract | Publisher Full Text | Free Full Text Froome HM, Cheung KL, Martin W, et al.: Identifying and characterising digital behaviour change interventions to improve fruit and vegetable intake in low-socioeconomic status primary school children: A Systematic Review.Research Square.2023.Publisher Full Text Giroux EE, Casemore S, Clarke TY, et al.: Enhancing participation while aging with spinal cord injury: applying behaviour change frameworks to develop Tamla Evans Obesity Institute, Leeds Beckett University School of Health (Ringgold ID: 151650), Leeds, England, UK Thank you for the opportunity to review this important study which addresses the gap in tools available to support use of the recently developed BCIO for the purposes of data extraction.Development of this tool will increase the accessibility and usability of the BCIO and facilitate the consistent reporting of behaviour change interventions needed for successful systematic reviews and meta-analyses.
ETH Centre, Campus for Research Excellence And Technological Enterprise (CREATE), Singapore, Singapore 2 Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore This paper provides a very nice overview of the process undertaken to develop a data extraction tool that can be used to systematically and consistently describe behaviour change interventions via ontologies.With widespread uptake amongst the behavioural science community (and beyond) this will facilitate better reporting and better evidence synthesis to enhance our understanding of the effectiveness of behaviour change interventions.
Is the study design appropriate and is the work technically sound?YesAre sufficient details of methods and analysis provided to allow replication by others?PartlyIf applicable, is the statistical analysis and its interpretation appropriate?Not applicable Are all the source data underlying the results available to ensure full reproducibility?YesAre the conclusions drawn adequately supported by the results?YesCompeting Interests: No competing interests were disclosed.Reviewer Expertise: Motivation, health behaviour change, physical activity promotion I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.Reviewer Report 24 May 2024 https://doi.org/10.21956/wellcomeopenres.23094.r80985© 2024 Silva C.This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Carolina C Silva Trinity College Dublin, Dublin, Ireland The article describes the development of a data extraction template for annotating using existing ontologies within the Behaviour Change Intervention Ontology.The various steps involved in the development of this template are outlined, as well as a process to continuously update it.
It can also be used to synthesise evidence as it clarifies what is the same, and what is different, across studies.Because entities each have a unique identifier, information represented by ontologies can be used in artificial intelligence and machine learning to predict behavioural outcomes.
"materials in how to code according to this revised framework", highlighting that an accessible resource is necessary to support researchers and practitioners to apply the BCIO in evidence synthesis.For example, in annotating BCIO entities for a systematic review of digital interventions to address children's fruit and vegetable consumption(Froome et al.,  2023), it was apparent that there was a need for a single data extraction template covering all component ontologies within the BCIO.It can also serve as a key entry point for using the BCIO more broadly for other purposes, such as intervention development.Specialist software such as EPPI-Reviewer, Covidence, and RevMan are excellent tools to support data extraction.However, researchers would need to create data extraction sheets by manually inputting entities from the BCIO into the software system.Given the large number of entities, this is inefficient and creates an unnecessary burden on researchers.Here we report the development of an accessible and standardised data extraction template, containing every BCIO entity label, definition and Uniform Resource Identifier (URI) within its hierarchical structure.

text reported BCIO coding Reference for papers with in-text reported BCIO coding
(Norris et al., 2020)presents development of a data extraction template to support annotations using the BCIO.This tool currently features entities from the six component ontologies within the BCIO that are published: mode of delivery(Marques et al.,  2020), setting(Norris et al., 2020), source(Norris et al., 2021), mechanisms of action(Schenk et al., 2023), behaviour change techniques(Marques et al., 2023), and style of delivery(Wright  et al., 2023).More ontologies within the BCIO are underway and will be added into this template once developed: human behaviour, fidelity, schedule, dose, engagement, and population.

Table A1 . Glossary of terms.
This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Not applicable Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests:
(I also noted on the Mode of Delivery manual that you suggest having a separate extraction sheet for each arm-why is that?Your template has the intervention and comparator together.)Minorpoint, but it's not immediately clear what is meant by upper and lower levels until you ○ look into the template itself.I wonder whether there is another way to describe this sort of hierarchical structure?Please provide dates of when all documents were made available.No competing interests were disclosed.

confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.
This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.studiesusing the BCIO.The authors clearly justify the purpose of this template and provide a detailed explanation of its development in the method section.Additionally, they offer easily accessible links to the template and supplementary material, allowing newcomers to the template and ontologies in general to engage with these tools.While I haven't utilized BCIO in my previous systematic reviews or intervention development work, I can appreciate the benefits these tools will offer researchers like myself in the future.I agree with the suggestions made by the previous reviewers.I also have one minor suggestion to enhance the reader's understanding of the role played by Froome et al. (2023) in the development of this template:In the introduction, the authors state: "For example, in annotating BCIO entities for a systematic review of digital interventions to address children's fruit and vegetable consumption(Froome et  al., 2023), it was apparent that there was a need for a single data extraction template covering all component ontologies within the BCIO."It would be helpful to be given a specific reason why it was apparent this data extraction template was needed -especially since this paper was used to pilot the template during the development.Additionally, it would be helpful for the authors to briefly clarify the role the paper will play in the development of the template when it is introduced in the introduction.
https://doi.org/10.21956/wellcomeopenres.23094.r86251© 2024 Rodger A. Amy Rodger Edinburgh University, Edinburgh, UK This paper describes the creation of the Behaviour Change Intervention Ontology (BCIO) data extraction template.The template aims to help researchers annotate evidence synthesis and intervention development

the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Yes If applicable, is the statistical analysis and its interpretation appropriate? Not applicable Are all the source data underlying the results available to ensure full reproducibility? No source data required Are the conclusions drawn adequately supported by the results? Yes Competing Interests:
No competing interests were disclosed.

have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.
This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Ntoumanis Danish Centre of Motivation and Behaviour Science (DRIVEN), University of Southern Denmark, Odense, Denmark With the development of the new ontologies, a data extraction template that integrates all available ontologies is a welcome addition to the literature.The manuscript describes in a clear and concise way the steps used in the development of this template.Below I offer some minor thoughts and suggestions for the authors' consideration.