Comic books and graphic novels represent a narrative format that is both easily understandable and accessible, making the medium a great form of “graphic medicine” for communicating healthcare information. However, metadata describing comics publications have not been well-connected with subject headings or descriptors for the narrative content itself by using the health-related knowledge organization systems (including taxonomies, classification systems, thesauri, subject headings, and ontologies) which often define and explain specific symptoms, treatment side-effects, etc. Enriching existing comics metadata with Linked Open Data (LOD) vocabularies offers an opportunity to enhance the discoverability of relevant comics material and content for patients, care givers, and providers. This pilot study presents an example of creating LOD for States of Mind, a graphic novel about bipolar disorder. Virtual poster presentation. 2022, July 18-19. Comics Studies and Practices Symposium. https://digital.sandiego.edu/csp-symposium/2022/2022/11/

1. Enriching comic book and graphic novel
metadata using Linked Open Data (LOD);
a pilot study for comics about mental health
Sean Petiya
Kent State University
spetiya1@kent.edu
https://github.com/comicmeta/LOD-MentalHealth

3.  Comic books and graphic novels are a visual and engaging medium, a great form of graphic
medicine, defined as “the intersection of comics and healthcare” (Czerwiec et al., 2015)
 Comics can be helpful both for educating patients and providing insight into the patient
experience for healthcare providers (Green & Myers, 2010)
 Metadata describing comics publications may lack medical subject headings, or
descriptions of narrative content
 Stories, pages, and panels may illustrate specific symptoms, treatments, side-effects, etc.
 Semantic enrichment using LOD offers an opportunity to enhance discoverability by linking
comics content to common healthcare vocabularies and ontologies

4.  Comics about health and illness can help explain
complex medical topics, and share personal healthcare
stories between patients, caregivers, and providers
(Jaggers et al., 2020)
 Comics may also help improve empathy and
communication between healthcare providers and patients
(Jaggers et al., 2020)
 Works of fiction (Death of Captain Marvel)
 Or non-fiction (Everything is an Emergency, The Fire
Never Goes Out, and Marbles)
Graphic novels about bipolar disorder

5.  Personal memoir of bipolar disorder starting with onset,
triggered by stressful events
 Begins with symptoms of panic and anxiety, followed by
severe depression mixed with episodes of euphoria
 Experiences several hospitalizations while struggling to
find effective treatment
 Struggles with acceptance and adherence to treatment
after receiving official diagnosis of bipolar disorder
A page from States of Mind by
Patrice and Emilie Guillon

6.  Common mental health condition; typically
characterized by mood swings
 Low periods of depression, emotionally high periods
called hypomania or mania
 Uncharacteristic behavior; loss of appetite, lack of
sleep, etc.
 May have limited insight or awareness of disorder
(Látalová, 2012)
 Insight can affect adherence with treatment and
medication (Látalová, 2012)
https://health.clevelandclinic.org/4-myths-you-shouldnt-
believe-about-bipolar-disorder/

7.  Data that is made freely available on the Web,
published with an open license (Berners-Lee,
2006)
 Uses common protocols (HTTP)
 Uses common data formats (XML, JSON, etc.)
 Uses common identifiers (URIs) instead of strings
for the names of subjects (#Bob not “Bob”)
 Machine readable and linked to other data

8.  LOD is supported by a graph data model, containing nodes and edges
 Graphs are expressed as RDF triple statements; subject > predicate > object
Bob Alice
knows
 Linked Open Vocabularies (LOV) can be used to describe relationships between
data, including comics content
#StatesOfMind mesh:D001714
schema:about
 Specific healthcare vocabulary can be found in LOD repositories like BioPortal
“Bipolar Disorder”
“Manic Depression”
name
altLabel

9.  Semantic enrichment is “the process of adding a layer of topical metadata to content so
that machines can make sense of it and build connections to it” (Clarke & Harley, 2014)
 The strategy of semantic enrichment has been successfully implemented by libraries,
archives, and museums (LAMs) to improve discoverability and reuse of their data
(Zeng, 2019)
 Adding semantic annotations to digital comics content has been explored using
automated tools like ComSem (Herwegen et al., 2017)
 This pilot study builds on these approaches in three phases; (1) a review of existing
metadata, (2) indexing and analyzing content, (3) creating enriched metadata

10. https://encore.cuyahoga.lib.oh.us/iii/encore/record/C__Rb11444844__Sstates%20of%20mind__?lang=eng&marcData=Y
520. Summary
650. Subjects (LCSH)
655. Genre/Form (LCGFT)
MARC

11. http://experiment.worldcat.org/oclc/1057775520.ttl
RDF

12. https://www.comics.org/issue/1963646/
HTML

13. Comic Book Ontology (CBO) – Sequence Model

14. BioPortal – https://bioportal.bioontology.org/
schema:name schema:about

15. https://github.com/comicmeta/LOD-MentalHealth

16. story
comic
pag
e
pane
l
abou
t
label
Graph of mental health topics for States of Mind

17. story
comic
abou
t
label
Graph of mental health topics for States of Mind by chapter

18.  76 pages or panels illustrating topics related to mental health indexed
 37 total healthcare terms from 11 LOD healthcare ontologies
 Opportunity exists to better link metadata descriptions for comics and comics content to
healthcare vocabularies and ontologies
 Potential to enhance the discovery of comics content for specific medical terms and
healthcare topics
 Discovery of distinct comics content better enables potential for reuse
 Limitations; (1) indexing/analysis can be subjective, and (2) accuracy of term
selection requires review by domain experts

19. PREFIX NAME
ICD10CM International Classification of Diseases, Version 10 Clinical Modification
MESH Medical Subject Headings
MEDDRA Medical Dictionary for Regulatory Activities Terminology
OGMS The Ontology for General Medical Science
NDDF National Drug Data File Plus Source Vocabulary
SYMP Symptom Ontology
MEDLINEPLUS MedlinePlus Health Topics
MFOMD MFO Mental Disease Ontology
ICNP International Classification for Nursing Practice
NDFRT National Drug File - Reference Terminology
ICPC2P International Classification of Primary Care - 2 PLUS
See BioPortal (https://bioportal.bioontology.org) for more information

20. Sean Petiya
spetiya1@kent.edu
Comic Book Ontology (CBO)
https://comicmeta.org/cbo
LOD Mental Health Pilot Study
https://github.com/comicmeta/LOD-MentalHealth

21. REFERENCES
Berners-Lee, T. (2006). Linked data-design issues. http://www.w3.org/DesignIssues/LinkedData.html
Clarke, M., & Harley, P. (2014). How smart is your content? Using semantic enrichment to improve your user experience and your
bottom line. Science, 37(2), 40-44
Green, M. J., & Myers, K. R. (2010). Graphic medicine: use of comics in medical education and patient care. Bmj, 340
Herwegen, J. V., Verborgh, R., & Mannens, E. (2017, May). ComSem: Digitization and Semantic Annotation of Comic Books. In
European Semantic Web Conference (pp. 65-70). Springer, Cham
Jaggers, A., Noe, M., & Pomputius, A. (2020). Graphic medicine in your library: Ideas and strategies for collecting comics about health
care. In Ballestro, J. (Ed.), The library's guide to graphic novels (pp. 165-184). ALA Editions, 2020.
Látalová, K. (2012). Insight in bipolar disorder. Psychiatric Quarterly, 83(3), 293-310
Czerwiec, MK., Williams, I., Squier, S. M., Green, M. J., Myers, K. R., & Smith, S. T. (2015). Graphic medicine manifesto. Penn State
Press.
Zeng, M. L. (2019). Semantic enrichment for enhancing LAM data and supporting digital humanities. Review article. El profesional de
la información, 28(1) https://doi.org/10.3145/epi.2019.ene.03