Next Article in Journal
Innovation Trajectories for a Society 5.0
Previous Article in Journal
Nowcasting India Economic Growth Using a Mixed-Data Sampling (MIDAS) Model (Empirical Study with Economic Policy Uncertainty–Consumer Prices Index)
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Metadata Schema for Managing Digital Data and Images of Thai Human Skulls

1
Department of Information Science, Khon Kaen University, Khon Kaen 40002, Thailand
2
Department of Anatomy, Khon Kaen University, Khon Kaen 40002, Thailand
*
Author to whom correspondence should be addressed.
Data 2021, 6(11), 114; https://doi.org/10.3390/data6110114
Submission received: 7 September 2021 / Revised: 4 November 2021 / Accepted: 8 November 2021 / Published: 10 November 2021
(This article belongs to the Section Information Systems and Data Management)

Abstract

:
This research was aimed at developing metadata that meets international standards for the purpose of managing digital data and images of Thai human skulls for medical studies. The research was conducted by applying the Metadata Lifecycle Model of the Metadata Architecture and Application Team. The model comprises four steps: requirement assessment and content analysis, identification of metadata requirements, metadata schema development, and metadata service and evaluation. The research outcome was a metadata schema composed of four modules, seven data element sets, and 29 pieces of data, each of which had six sets of property descriptions. Metadata evaluation conducted by three specialists in the field of anatomy and forensic medicine and three experts in the field of information science and metadata through free retrieval based on the Continuum of Metadata Quality in four aspects revealed that the experts were satisfied with the quality of metadata at a very high level: 100% for completeness, accuracy, and accessibility, and 94% for conformance to expectations. The developed metadata contain details that can be used to describe the characteristics of human skulls, with consideration taken in the development of the language used, retrieval, access, data exchange, and sharing. Thus, this novel metadata schema can be of use in management of digital data and images of human skulls for the purposes of medical studies, i.e., human anatomy and forensic anthropology.

1. Introduction

Studies on human skull studies were initially carried out in specific, individual fields, but over time researchers have begun to adopt a more multidisciplinary approach. Principles and methodologies have been applied with the use of tools or scientific equipment to study archaeological processes in parallel to the development of theoretical concepts and construction of methodologies in order to interpret/explain historical and cultural stories. This has led to studies and analyses of a wide variety of archaeological evidence in detail by means of standardized systems [1], thereby providing useful resources for intensive analytical studies of human skulls. Studies conducted under the archaeological perspective are directly related to at least two different disciplines, i.e., physical anthropology and gross anatomy in medicine [2].
Human skulls are important evidence that provides information physiologically linking the past and the present with significance in various aspects. Human skulls are the only type of evidence providing basic information about the gender and age of the dead, including their height and traces of uncommon characteristics that appear on bones or in the bone structure. These may indicate pathologies from general infection of bones or trauma from a certain cause. Studies of bone structure have led to an understanding of nutritional conditions in the past [2,3,4]. Analytical information of human skulls allows the interpretation of the lifestyle of a dead person. Traces found from the study of each part of the bone are regarded as evidence reflecting the behavior or actions of the person when alive. They relate to a certain behavior that the person routinely performed, thereby providing a clue as to what their occupation was [4].
In Thailand, a human skull is one type of archaeological evidence, according to Section 4 of the Archeological Site, Antiquities, Artifacts and National Museum Act, 1961 and the Amended Archeological Site, Antiquities, Artifacts and National Museum Act (Second Edition) [5]. The study of human skulls is an aspect of the study of physical anthropology and biology, since humans are a species of the animal kingdom. Studies of human origin and evolution and comparisons of humans in the past and present have been conducted to analyze specific characteristics in order to identify differences in human races [6]. When discovered tombs and their surrounding articles such as utensils and ornaments are investigated, researchers are able to solve puzzles related to historical people, environments, and cultures. These studies take into account archaeological, physical, anthropological, scientific and modern technological information; hence, details of basic human information, e.g., age at death, gender, height, race, ethnic group, possible social and cultural pictures of the past, lifestyles, and diseases, are obtained, enabling comparisons between prehistoric and present humans.
There are many learning resources and collections of bodies of knowledge in regard to human skulls. In Thailand, at present, the learning resources are anatomical museums, including Khondon Anatomical Museum; Faculty of Medicine Siriraj Hospital, Mahidol University; Anatomical Museum, Chulalongkorn University; Museum of Human Body, Faculty of Dentistry, Chulalongkorn University; and Anatomical Museum of Ajarn Kasem Kaewim, Songkhlanakarin Hospital. There are not many anatomical museums in Thailand, and a study by Chanpak showed that there is a constraint in terms of space for an anatomical museum to collect and exhibit articles, biopsies, and pieces of human organs. There are also constraints in terms of open hours for visits to these museums, distances, and rights to visit. Some anatomical museums have websites, but only some information is provided, while no virtual museum has been developed [7]. These research findings are in agreement with those of a study conducted by Princess Maha Chakri Sirindhorn Anthropology Center related to human skulls in Thailand. The research was based on a conceptual framework, theories, and methodology in physical anthropology and related fields such as human macro-anatomy, biological archaeology, and forensic anthropology. Information on human skulls has been compiled in many forms, including documents, research reports, articles, textbooks, and realis. There are many constraints in access to human skull realis, i.e., in terms of active usage, open hours, and rights of usage [8]. Advances in information technology, however, enable users to gain access to such information virtually, at any time by means of the internet. This is linked to the museum management dimension that emphasizes digital collections of human skull information that effectively solve the limitations.
The skull is the human bone structure that forms the human head and face in a complex form. Studies of human skulls are very useful, especially in regard to proof of identity. If there is adequate information from any part of the skull, scientific forensics will be able to analyze the correlation of the parts or components of the skull with various characteristics, such as sex, age, race, and ethnicity [8]. If systematic management of the data and images of human skulls are available and are based on various technologies, for instance, metadata, information corpuses, or an information system, the analyses and computation of information will yield tremendous benefits. However, research on human skulls in order to learn about the components of the skull, the number of bones, their names, and characteristics that compose the content of the skull are already available in textbooks or in the form of anatomy information. A system that compiles information in the aspect of information science comprises context or the information about the owner of the skull. This system necessitates collection of an adequate number of real cases, which is very complicated due to the source (a hospital) and consent of the owner. Additionally, with the missing content and context, it is impossible to analyze the structure or the information derived from the relation between the content and the context.
Metadata are a set of information developed structurally in order to describe in detail a set of information resources. Such descriptions cover the content, context, and structure, as well as the relations between the components used to describe the information resources. Metadata are produced for benefits in retrieval and management of information resources [9,10]. The metadata of each type of information are derived from a set of metadata elements established to explain the details of the information resource, for example, the title, the person responsible for production, the year of production, the content characteristics, and the format of the data file. In addition, the principles in format setting, value displaying, and encoding are established for the data in each component so that the computer can interpret the results. The principle and encoding approach is called the metadata schema [11]. Presently, a metadata schema has been developed using international standards to enable management of different types of data based on the characteristics of each information resource [12].
Studies of standard metadata for management of medical information demonstrated a widely known standard, i.e., Digital Imaging and Communications in Medicine (DICOM) [12]. This is an international standard for managing images in medicine and related data that establish the format of data to facilitate exchange of quality data useful for clinical purposes (https://www.dicomstandard.org/about-home, accessed on 2 February 2021). The standard was developed by the National Electrical Manufacturers Association (NEMA). The DICOM standard is composed of four modules: (1) series—explaining a patient’s images; (2) patient—explaining the patient; (3) image—explaining the images in detail; and (4) study—explaining the study or the test conducted with the patient [13]. Tirado-Ramos, Hu, and Lee noted that the DICOM standard is used to manage digital images in medicine. It explains specific information of a real object with the aim of exchanging the information of the objects with similar properties. Therefore, the DICOM standard compiles the characteristics of medical images obtained from CT-Scan, e.g., file name and image characteristics, including size, color, and resolution [13]. However, the DICOM standard cannot be used to manage data related to human physiological or anatomical aspects since it does not provide the management of details related to content. Moreover, other existing metadata standards include the Dublin Core Metadata Element Set [14], used to describe books and documents; the Metadata Object Description Schema (MOD) [15]; the Visual Resource Association (VRA Core) [16], used to describe visual arts, such as paintings, sculptures, and architecture; Categories for the Description of Works of Art (CDWA), used to explain arts, architecture, and cultural objects; and Performance Arts Metadata [17]. It is obvious that the existing metadata standards have been developed to manage different types of information resources, reflecting physical differences, varied content, and user needs [18]. Moreover, none of these standards focus on describing and linking the appropriate semantic data to medical data, especially human skull data, which are used for anatomical and forensic medical studies.
The management of human skull data in the field of information science can be studied based on information object analysis, which, according to Gilliland, involves the fact that an information object has three components, namely, (1) content data, (2) context data, and (3) structure data [19]. This is the basic concept used in data description for storing and retrieving information in various forms. The development of metadata, in particular, is necessary for describing information objects in a digital form [20]. This research thus applied this concept in analyzing information objects to analyze human skull data. Then, a metadata schema was developed to describe human skulls in order to store human skull data in the digital format. This metadata schema is different from existing ones, as it was specifically developed for describing the data of human skulls and the data derived from living human CT scan images and data. Moreover, the unique data on human skulls can be stored and calculated for forensic analysis and can be further used to verify human identity. It may also be useful for libraries and museums in the production of data corpus or for learning platforms for medical studies in the future.

2. Objectives

The aim of this research is to answer the following research question: how can internationally standardized metadata used to describe information and images of Thai human skulls store information and Thai human skull images for the purpose of medical studies?
The information and Thai human skull images used as examples in this research were obtained from the study “Craniometry Study of Skulls in Northeastern Thai Adults” by Tuamsuk, Nonsrichan, and Sirisilp [21]. The authors of this research permitted use of the information presented in their study, which was approved in terms of human ethics in research based on the Declaration of Helsinki and Good Clinical Practice Guideline (ICH GCP), as per the authorization document No. HE641189, issued on 29 March 2021. The research by Tuamsuk, Nonsrichan, and Sirisilp was conducted on 246 skulls of living Thai people from CT scan images obtained by means of a craniometry study. The study compiled significant information complete with multi-dimensional skull images that can be used in study programs in the field of human anatomy. The other outcome of this study is the development of the cranial index, which is helpful in identity analysis of people in the field of forensic anthropology [21].

3. Methodology

The current research was conducted by applying the Metadata Lifecycle Model of the Metadata Architecture and Application Team (MAAT) [22]. The model comprises four steps: (1) requirement assessment and content analysis, (2) identification of metadata requirements (3) metadata schema development, and (4) metadata service and evaluation. The methodology was based on the research and development approach, as illustrated in Figure 1.

3.1. Needs Assessment and Content Analysis

The information used in this study was obtained from the research study “Analysis of the Human Skull Data Using Information Object Analysis Concept” by Yosakonkun, Tuamsuk, and Tuamsuk [25], which was a quality research study based on content analysis, information object analysis, and interviews with medical specialists in anatomy, forensic medicine, and forensic anthropology, with the aim of evaluating the need for metadata development. The analytical results of the research by Yosakonkun, Tuamsuk, and Tuamsuk, based on information object analysis, can be concluded as follows [25]:
Content means the information existing in human skulls. Human skulls are composed of 14 pieces of bone: frontal bone, parietal bone, temporal bone, occipital bone, sphenoid bone, ethmoid bone, zygomatic bone, maxillary bone, Lacrimal bone, palatine bone, nasal bone, inferior nasal conchae bone, vomer bone, and mandible bone. Each bone has the following significant and specific information for the anatomical and forensic anthropological studies: (1) histogenesis of bone—there are 2 types of histogenesis, intramembranous ossification and intracartilaginous ossification [26]; (2) bone shape, which can be classified into 5 shapes: long bone, short bone, flat bone, irregular bone, and sesamoid bone; (3) landmark—there are 43 landmarks on a human skull, which are the points used to measure the size and shape of the skulls used in anatomy and forensic anthropology, identified by number, name, and definition on the basis of previous research works [21,27].
Context refers to the information not existing in the skull but rather indicates the background of the skull or the information of the owner of the skull image. The CT scan provides CT date, birthdate, age, sex, race, height, weight, body mass index (BMI), province of residence, and CT scan images.
Structure refers to the information or set of information that indicates the relations between content and content, content and context, or context and context. The structure in this research was aimed at managing human skull information to develop metadata for that could be useful in forensic anthropological analyses. The structure consists of craniometric length and cranial index; see Figure 2 [21].

3.2. Identification of Metadata Requirements

The researchers used the results of the first-step analyses of human skull information to draft the conceptual framework of metadata for Thai human skulls, arranging the data element sets based on the DICOM standards (DICOM) of NEMA [13]. The information was classified into four modules, with seven data elements based on the characteristics of information derived from information object analysis (Table 1).
Because the DICOM standards [13] are specific to the images of human skulls with the data sets focusing on patient and image data, the researchers adapted the concepts of Dublin Core Metadata to manage information objects [23] in order to describe the details of data elements for human skulls. The properties of each data element of Dublin Core Metadata [23] generally consist of four details: (1) element name, (2) label, (3) definition, and (4) comments, among which, name, definition, and comments were used in this research.

3.3. Metadata Schema Development

This step involved the production of a data element description in the metadata. The description regards the properties of data in order to build a common semantic understanding and demonstrate the uniqueness of each set of metadata. This can be read by the machine-understandable metadata. Single-word naming was conducted for syntactic specification, which is necessary for further coding or program writing in different languages, such as Extensible Markup Language (XML) [23].
Details of the information elements in this research were set based on the management standard of some information of Dublin Core Metadata [23] and DICOM [13] for those associated with a large amount of the patient and image information, as there is no information standard directly related to human skulls. The property of each piece of information in Dublin Core Metadata [23] comprises the 4 following items at least: (1) element name or name of data, (2) label, (3) definition, and (4) comment or description of the format or characteristics of information. Moreover, other properties can be added depending on each piece of data and usage. For example, URL means that the information is on a website that is linked to a respective source or that provides further details, while References means the reference source of the data. The data in the DICOM standard, on the other hand, are mostly the data used to manage medical-related images, the details of which have not been clarified. Thus, only the name that corresponds to this research was used in order to arrive at the same standard, and single-word naming was conducted in accordance with Dublin Core Metadata (Table 2).

3.4. Metadata Service and Evaluation

The metadata developed were produced as a storage and retrieval system in the form of a digital collection of Thai human skulls, using PHP language to write the MySQL Program as the databases and Open Archives Initiative—Protocol for Metadata Harvesting (OAI-PMH) [29] as the standard to assist in the compilation of metadata of the information in Open Archives. The system enables searching of and access to the metadata of all resources in the digital information corpus of skulls and can be the prototype for testing the management of information and digital images of Thai human skulls. Access is available at: http://localhost/thai_skull/ (accessed on 12 April 2021).
Metadata evaluation was conducted by three specialists in the field of anatomy and forensic medicine and three experts in the field of information science and metadata. The system was experimented on via free retrieval, and the metadata were evaluated using the evaluation form developed from the concept of the Continuum of Metadata Quality developed by Bruce and Hillmann [24]. The evaluation was then performed on four aspects, namely, completeness, accuracy, accessibility, and conformance to expectations. Informants were requested to complete evaluations forms, from which data were collected. The results showed high satisfaction with some suggestions for metadata revision, including the options for adding data elements for future development such as skull image views and demography data of patients.

4. Results

The outcome of the current research is the development of a metadata schema for the management of digital data and images of human skulls with the following particulars:

4.1. Structure of Metadata Schema

The structure of the metadata schema comprises 4 modules, 7 data element sets, and 29 pieces of data. Each piece of data contains 6 property items (Table 3).

4.2. Description of Metadata Schema

Below are the descriptions that can be used to describe digital data and images of Thai human skulls (Table 4).

4.3. Metadata Evaluation

Metadata evaluation conducted by three specialists in the field of anatomy and forensic medicine and three experts in the field of information science and metadata through free retrieval based on the Continuum of Metadata Quality [24] in four aspects revealed that the experts were satisfied with the quality of metadata at a very high level, 100% for completeness, accuracy, and accessibility, and 94% for conformance to expectations.

4.4. Linked Open Standard

The metadata schema for managing digital data and images of Thai human skulls was converted into RDF (Resource Description Framework) format to allow the metadata to be openly interchanged and used for other similar sets of data (Figure 3).

5. Discussion

Since DICOM is the standard for managing medical information, it does not involve content management or content related to anatomy, skeletal systems, or human skulls. The information in this research is both the content and the images of skulls that contain relatively high differences in details. However, the researchers based the study on conformance in the module name and element name, which followed the standard of DICOM or was at least comparable to it, thereby allowing the metadata to be of an international standard and useful for common use in the future. Comparative details are given in Table 5.

6. Conclusions

In conclusion, the development of metadata for the management of digital data and images of Thai human skulls was carried out on the principle that a human skull is an information object, which comprises a content, context, and structure, enabling an attribute setting for the skull according to the information management method to be used for the purpose of the description of information in many aspects. The data management approach discussed above is the basis for the development of equipment whose purpose is to store and search digital information [20], which is different from previous information resource management approaches. Formerly, emphases were placed on the collection of context information, principally including, for instance, name of author, topic, year of publishing, place of publishing, and publisher, without attention paid to the content and structure of the information resources that are also necessary for access [12]. Therefore, when the information is developed into metadata based on the approach that conforms to the international standards, i.e., setting the name, definition, format, and details of the information that can be used to describe the characteristics of human skulls, and when the language of access is taken into account for retrieval, access, and information exchange and sharing [23], the metadata become useful in managing digital data and images of skulls for medical studies. The fields that may benefit from this are human anatomy and forensic anthropology. The metadata schema was developed to describe human skulls in order to provide assistance in storing human skull data in the digital format. Although, this metadata schema used and adopted some elements from the existing metadata standards, including the DICOM and Dublin Core Metadata Element Set, it is significantly different due to the following reasons: (1) the metadata are developed specifically to describe human skull data; (2) the data are derived from living human CT scan images and data, and the unique data (such as landmarks and craniometric length) of each human skull can be stored and calculated for forensic analysis and can be further used to verify human identity. These metadata are in a novel form; the user will be able to use the information to study different elements of human skulls; and the information required for human identification is also available (empirical study) [30]. If the database system compiles a great amount of information and a high number of human skull images, they can be analyzed to demonstrate the appearance and relations with human characteristics in different aspects, such as races, domiciles, and ancestors.

Author Contributions

Conceptualization, S.Y. and K.T.; methodology, S.Y. and K.T.; software, W.C.; validation, P.T.; formal analysis, S.Y. and K.T.; resources, P.T.; writing—original draft preparation, S.Y. and K.T.; writing—review and editing, P.T. and K.T.; visualization, S.Y. and W.C.; supervision, P.T. and K.T.; funding acquisition, K.T. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and Good Clinical Practice Guideline (ICH GCP) and approved by the Institutional Review Board of KHON KAEN UNIVERSITY, THAILAND (Document No. HE641189, issued on 29 March 2021).

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

This research is supported by the Royal Golden Jubilee Program under the National Research Council of Thailand, Ministry of Higher Education, Science, Research, and Innovation, Thailand.

Conflicts of Interest

The authors declare no conflict of interest.

Nomenclature

Acronyms/AbbreviationsFull names
DICOMDigital Imaging and Communications in Medicine
NEMANational Electrical Manufacturers Association
CT ScanComputerized Tomography Scan
Dublin Core or DCDublin Core Metadata Element Set
MODMetadata Object Description Schema
VRA Visual Resource Association
CDWACategories for the Description of Works of Art
OAI-PMHOpen Archives Initiative—Protocol for Metadata Harvesting
RDFRDF (Resource Description Framework)

References

  1. Renfrew, C.; Bahn, P. Archaeology Theories, Methods and Practice; Thames and Hudson: London, UK, 1993. [Google Scholar]
  2. Chapman, R.; Kinnes, I.; Randsborg, K. (Eds.) The Archaeology of Death; Cambridge University Press: London, UK, 1981. [Google Scholar]
  3. Corruccini, R.S. An examination of the meaning of cranial discrete traits for human skeletal biological studies. Am. J. Phys. Anthropol. 1974, 40, 425–445. [Google Scholar] [CrossRef] [PubMed]
  4. Boyd, D.C. Skeleton correlates of human behavior in the Americas. J. Archaeol. Method Theory 1996, 3, 189–251. [Google Scholar] [CrossRef]
  5. Department of Fine Arts. Act of Ancient Sites, Antiquities, Artifacts, and National Museums, (Issue No.2) A.D. 2535; The Department: Bangkok, Thailand, 2003. [Google Scholar]
  6. Saengwician, S. (Ed.) Physical Anthropology of Skulls and Skeletons of Thai People; Mahidol University: Bangkok, Thailand, 2007. [Google Scholar]
  7. Chanpak, S. The Study of Guidelines for Improvement of Exhibition in the Museum of Anatomy Kong Don; Mahidol University: Bangkok, Thailand, 2009. [Google Scholar]
  8. Princess Maha Chaki Sirindhorn Anthropology Center. Thailand Physical Anthropology Database. Available online: https://www.sac.or.th/databases/physanth/app/about.php (accessed on 2 February 2021).
  9. Phillips, V.M. Skeleton Remains Identification by Facial Reconstruction. Available online: https://archives.fbi.gov/archives/about-us/lab/forensic-science-communications/fsc/jan2001/phillips.htm (accessed on 11 March 2021).
  10. Haynes, D. Metadata for Information Management and Retrieval; Facet: London, UK, 2004. [Google Scholar]
  11. Baca, M.; The Getty Research Institute. Introduction to Metadata, 2nd ed.; Baga, M., Ed.; The Getty Research Institute: Los Angeles, CA, USA, 2008; Available online: https://www.worldcat.org/title/introduction-to-metadata/oclc/199464527 (accessed on 11 March 2021).
  12. Woodley, M.S. Metadata matters: Connecting people and information. In Introduction to Metadata, 3rd ed.; Baca, M., Ed.; The Getty Research Institute: Los Angeles, CA, USA, 2016; Available online: www.getty.edu/publications/intrometadata/metadata-matters/ (accessed on 11 March 2021).
  13. NEMA. The DICOM Standard. Available online: https://www.dicomstandard.org/current (accessed on 2 February 2021).
  14. Dublin CoreTM. Metadata Initiatives. DCMI Metadata Terms. 2020. Available online: https://www.dublincore.org/specifications/dublin-core/dcmi-terms/ (accessed on 4 April 2021).
  15. Library of Congress. Metadata Object Description Schema (MODS). 2020. Available online: https://www.loc.gov/standards/mods/mods-schemas.html (accessed on 5 April 2021).
  16. Library of Congress. VRA Core Schemas and Documentation. 2015. Available online: https://www.loc.gov/standards/vracore/schemas.html (accessed on 6 April 2021).
  17. Getty Research Institute. Categories for Description of Works of Arts. 2019. Available online: https://www.getty.edu/research/publications/electronic_publications/cdwa/introduction.html (accessed on 4 April 2021).
  18. Caplan, P. Metadata Fundamentals for All Librarians; American Library Association: Chicago, IL, USA, 2003. [Google Scholar]
  19. Tirado-Ramos, A.; Hu, J.; Lee, K.P. Information object definition-based unified modeling language representation of DICOM structure reporting. J. Am. Med. Inf. Assoc. 2002, 9, 63–72. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  20. Gilliland, A.J. Setting the stage. In Introduction to Metadata, 3rd ed.; Baga, M., Ed.; The Getty Research Institute: Los Angeles, CA, USA, 2016; Available online: https://www.getty.edu/publications/intrometadata/setting-the-stage/ (accessed on 11 March 2021).
  21. Tuamsuk, P.; Nonsrijun, N.; Sirisin, J. Craniometry study of 3D-human skulls in Srinagarind Hospital, Khon Kaen University, Thailand. In Proceedings of the 37th Annual Conference of the Anatomy Association of Thailand, The Cultural Center of Lower Northern Region, Phitsanulok, Thailand, 7–9 May 2014. [Google Scholar]
  22. MATT. Metadata Lifecycle Model. Available online: https://metadata.teldap.tw/design/lifecycle_eng.htm (accessed on 2 February 2021).
  23. NISO. The Dublin Core Metadata Element Set; National Information Standards Organization: Bethesda, ML, USA, 2001; Available online: https://core.ac.uk/download/pdf/58953858.pdf (accessed on 2 February 2021).
  24. Bruce, T.R.; Hillmann, D.I. The Continuum of Metadata Quality: Defining, Expressing, Exploiting; American Library Association: Chicago, IL, USA, 2004. [Google Scholar]
  25. Yosakonkun, S.; Tuamsuk, P.; Tuamsuk, K. Analysis of the human skull data using information object analysis concept. Silpakorn Univ. J. 2021, in press. [Google Scholar]
  26. Namking, M. Skeleton system. In Basic Anatomy 1; Kerdkoonchon, M., Woraputporn, W., Amatayakong, P., Aiamsaard, S., Namking, M., Eds.; Faculty of Medicine, Khon Kaen University: Khon Kaen, Thailand, 2016; pp. 109–148. [Google Scholar]
  27. Nilprapan, A. Three-Dimensional Analysis of Thai Skulls Collected in Northeast Thailand. Master’s Thesis, Graduate School, Khon Kaen University, Khon Kaen, Thailand, May 1996. [Google Scholar]
  28. DICOM Library. DICOM Tags. Available online: https://www.dicomlibrary.com/dicom/dicom-tags/?fbclid=IwAR3esqvTbjlKIB2Iq5avRnrSfrd0ehmyFyF94IwUO1Va5GVLAIDXhcUlsm0 (accessed on 2 February 2021).
  29. Suleman, H. Introduction to the open archives initiative protocol for metadata harvesting. In Proceedings of the 2nd ACM/IEEE-CS Joint Conference on Digital Libraries, Portland, OR, USA, 14–18 July 2002; ACM Press: Roanoke, VA, USA, 2002; p. 414. [Google Scholar]
  30. Houck, M.M. (Ed.) Forensic Anthropology; Academic Press: Cambridge, MA, USA, 2017. [Google Scholar]
Figure 1. Research conceptual framework [13,20,22,23,24].
Figure 1. Research conceptual framework [13,20,22,23,24].
Data 06 00114 g001
Figure 2. Example of landmarks on human skulls identified by the reference numbers (in blue) and the line of craniometric length (in black) [21].
Figure 2. Example of landmarks on human skulls identified by the reference numbers (in blue) and the line of craniometric length (in black) [21].
Data 06 00114 g002
Figure 3. Example of metadata in RDF format.
Figure 3. Example of metadata in RDF format.
Data 06 00114 g003
Table 1. Conceptual framework of the metadata structure.
Table 1. Conceptual framework of the metadata structure.
ModuleModule DescriptionData ElementData Based on Information Object Analysis
SeriesData set on the content of human skullElement 1: BoneContent data
Element 2: LandmarkContent data
PatientsData set on the patient whose skull was CT scannedElement 3: PatientContext data
Element 4: Craniometric lengthStructure data
ImagesImage of CT scan of the patient’s skullElement 5: ImageContext data
StudyData set on the study (cranial index of the patient’s skull)Element 6: Cranial indexStructure data
Element 7: Standard indexStandard data
Table 2. Properties of the data elements applied in this research, adapted from DICOM Library [28].
Table 2. Properties of the data elements applied in this research, adapted from DICOM Library [28].
DICOM TagDICOM NameMetadata of Thai Human Skull
(0010,0020)Patient IDPatientID
(0010,0030)Patient’s Birth DatePatientBirthDate
(0010,0040)Patient’s SexPatientSex
(0010,0010)Patient’s AgeFPatientAge
(0010,1030)Patient’s WeightPatientWeight
(0010,1040)Patient’s AddressPatientAddress
(0018,9329)CT Image Fame Type SequenceCTImage
(0018,9329)View PositionViewPosition
Table 3. Structure of metadata schema for Thai human skulls.
Table 3. Structure of metadata schema for Thai human skulls.
ModuleData ElementDataProperty
Series1. Bone1.1 BoneName_English
1.2 BoneName_Thai
1.3 BoneHistogenesis
1.4 BoneTissue
1.5 BoneShape
2. Landmark2.1 LandmarkID
2.2 LandmarkName
2.3 LandmarkDescription
Patients3. Patient3.1 PatientID
3.2 CTDate
3.3 PatientBirthDate
3.4 PatientAgeName
3.5 PatientSexDefinition
3.6 PatientRaceFormat
3.7 PatientHeightComment
3.8 PatientWeightExample
3.9 PatientBMIReferences
3.10 PatientAddress
4. Craniometric length4.1 CraniometricLengthID
4.2 CraniometricLengthName
4.3 CraniometricPointToPoint
4.4 CraniometricLengthDescription
4.5 CraniometricLength
Image5. Image5.1 ViewPosition
5.2 CTImage
Study6. Cranial index6.1 CranialIndexName
6.2 CranialIndexValue
7. Standard index7.1 SkullType
7.2 StandardIndexValue
Table 4. Description of metadata schema of Thai human skulls.
Table 4. Description of metadata schema of Thai human skulls.
Module 1—SeriesThis Module Specifies the Data Regarding Bones and Landmarks on the Human Skull
Element 1: BoneElement set of data on the bones of human skulls
Name 1.1BoneName_English
DefinitionEnglish name of the bone
FormatText
CommentUse an English term as shown in an anatomical textbook
ExampleFrontal bone
References-
Name 1.2BoneName_Thai
DefinitionThai name of the bone
FormatText
CommentUse a Thai term as shown in the Dictionary of Thai Medical Terms or Thai textbook of Anatomy
Exampleกระดูกหน้าผาก (Thai language for Frontal bone)
References-
Name 1.3BoneHistogenesis
DefinitionThe origin or development method of the bone
FormatText
CommentThere are two methods: 1. intramembranous ossification and 2. intracartilaginous ossification
ExampleIntramembranous ossification
References-
Name 1.4BoneTissue
DefinitionCharacteristic of the bone’s tissue
FormatText
CommentThere are two characteristics: 1. compact and 2. spongy
ExampleCompact
References-
Name 1.5BoneShape
DefinitionShape of the bone
FormatText
CommentThere are five shapes: 1. long, 2. short, 3. flat, 4. irregular, and 5. sesamoid
ExampleFlat
References-
Element 2: LandmarkElement set of data on the landmarks on human skulls
Name 2.1LandmarkID
DefinitionIdentification number of the landmark on the human skull
FormatText
CommentThere are 43 landmarks on the human skull. Typically, a landmark ID starts from number 1 to 43. As the paired landmark appears on the left and right sides of the skull, the letter L or R shall be added as appropriate.
Example2
References-
Name 2.2LandmarkName
DefinitionName of the landmark on the human skull
FormatText
CommentName of all 43 landmarks on the human skull. For the paired-landmark appearing on the left and right sides of the skull, the letter L or R shall be added as appropriate.
ExampleGlabella
References-
Name 2.3LandmarkDescription
DefinitionDescription of the landmark on the human skull
FormatText
CommentA description of each landmark
ExampleMost anterior midline point on the frontal bone, usually above the nasofrontal suture
References-
Module 2—PatientsThis module specifies the data regarding the patients whose CT scan of skulls were studied in this set of data.
Element 3: PatientElement set of demographic data of the patient
Name 3.1PatientID
DefinitionIdentification number of the anonymous patient
FormatNumber
CommentA patient ID starts from number 1 to an n case.
Example1
References-
Name 3.2CTDate
DefinitionSkull CT scan date of each patient
FormatDate
Commentdd/mm/yyyy (A.D. year)
Example24 September 2009
References-
Name 3.3PatientBirthDate
DefinitionPatient’s birth date
FormatDate
Commentdd/mm/yyyy (A.D. year)
Example13 February 1966
References-
Name 3.4PatientAge
DefinitionAge of the patient as of the CT date
FormatNumber
CommentInput the age of the patient as of the CT scan date in numeric format
Example43
References-
Name 3.5PatientSex
DefinitionGender of the patient
FormatText
CommentInput M for male and F for female.
ExampleM
References-
Name 3.6PatientRace
DefinitionRace of the patient
FormatText
CommentInput a race of the patient. Note that all patients in the data set of this research are Thai.
ExampleThai
References-
Name 3.7PatientHeight
DefinitionPatient’s height
FormatNumber
CommentInput the patient’s height in centimeter
Example167
References-
Name 3.8PatientWeight
DefinitionPatient’s weight
FormatNumber
CommentInput the patient’s weight in kilogram
Example71.5
References-
Name 3.9PatientBMI
DefinitionValue of body mass index (BMI) of the patient
FormatNumber
CommentInput value of the patient’s BMI
Example25.53
References-
Name 3.10PatientAddress
DefinitionThe place of patient’s address.
FormatText
CommentThe place of patient’s address, in this data set is the name of the province of Thailand. Input an English name of the province according to the official name.
ExampleKhon Kaen
ReferencesNames of places and province of Thailand in English. http://www.thailaws.com/download/thaidownload/provinces_eng.pdf (accessed on 4 April 2021)
Element 4: Craniometric lengthElement set of data regarding craniometric length of the patient
Name 4.1CraniometricLengthID
DefinitionIdentification number of the craniometric length
FormatText
CommentThere are 26 craniometric lengths. The alphabet from A to V is used to identify each craniometric length.
ExampleD
References-
Name 4.2CraniometricLengthName
DefinitionName of each craniometric length
FormatText
CommentInput name of each craniometric length
ExampleMaximum front breadth
References-
Name 4.3CraniometricPointToPoint
DefinitionLandmark point-to-point ID that specified each craniometric length.
FormatText
CommentInput the landmark ID from the starting point to the point of each craniometric length
Example29L–29R
References-
Name 4.4CraniometricLengthDescription
DefinitionDescription of each craniometric length
FormatText
CommentInput the description of each craniometric length
ExampleDirect distance between the two frontotemporal areas is extended
References-
Name 4.5CraniometricLength
DefinitionThe length from landmark’s point to point, measured in millimeter
FormatNumber
CommentInput numeric value of the craniometric length of each patient in millimeter
Example106.12
References-
Module 3—ImagesThis module specifies the data regarding the images of CT scan of skulls of patients.
Element 5: ImageElement set of the image of CT scan of human skull of each patient
Name 5.1ViewPosition
DefinitionImage view of CT scan of the patient’s skull
FormatText
CommentThere are 6 views of the image in this data set: 1. anterior, 2. posterior, 3. superior, 4. Interior, 5. lateral left, and 6. lateral right.
ExampleAnterior
References-
Name 5.2CT_Image
DefinitionImage of CT scan of the patient’s skull
Format.PNG file
CommentUpload a CT scan image file. Link to location of the image file.
Example-
References-
Module 6—StudyThis module specifies the data regarding the cranial index of the CT scan of skulls of patients.
Element 6: Cranial indexElement set of the cranial index of the human skull of each patient
Name 6.1CranialIndexName
DefinitionName of each cranial index
FormatText
CommentInput name of each cranial index
ExampleCranial index
References-
Name 6.2CranialIndexValue
DefinitionValue of each cranial index in percentage as a result of calculation
FormatFormular
CommentAutomatic input from the "CraniometricLength" data and then calculate according to the pre-set formula. The value is presented in percentage.
ExampleMaximum breadth × 100
Maximum length
References-
Element 7: Standard indexElement set of the standard index identifying the type of the human skull from cranial index value
Name 7.1SkullType
DefinitionType of human skull that can be used to identify human identity in forensic anthropology
FormatText
CommentThere are several types of human skulls, for example, ultradolichocranial, hyperdolichocranial, dolichocranial, mesocranial, brachycranial, hyperbrachycranial, and ultrabrachycranial skulls
ExampleDolichocranial
References-
Name 7.2StandardIndexValue
DefinitionValue of each standard index for type of human skull in percentage
FormatText
CommentPercentage value or range of values for identifying the type of human skull
Example80–85
References-
Table 5. Comparison between structures and names of modules in this research and DICOM standards.
Table 5. Comparison between structures and names of modules in this research and DICOM standards.
Module NameDICOM StandardsMetadata of Thai Human Skulls
SeriesThis module specifies the attributes that identify and describe general information about the Series within a study.Data sets of human skull elements (this research only compiled bone information and landmarks, which are used for forensic anthropological analyses).
PatientThis module specifies the attributes of the Patient that describe and identify the Patient who is the subject of a study. This module contains attributes of the Patient that are needed for interpretation of the composite instances and are common for all studies performed on the Patient.Attributes of the patient whose skull was imaged can be used to study information of a skull in series, and the skull index can be analyzed. This research compiled information of Thai people whose skulls were CT scanned for the purpose of research.
ImageThis module specifies the attributes that identify and describe an Image within a particular series.There are details regarding the CT scan image sets of Thai human skulls that were imaged for research purposes in the patient information set.
StudyThis module specifies the attributes that describe and identify the Study performed upon the patient.The data sets on the analyses of patient skulls, resulting from measuring the lengths of different parts of the CT scan images and calculations (for use in forensic anthropology analysis, which is emphasized in this research).
EquipmentThis module specifies the attributes that identify and describe the piece of Equipment that produced a series of composite instances.Not specified, as there are no data sets for equipment (no application).
Referenceshttps://dicomiseasy.blogspot.com/2011/12/chapter-4-dicom-objects-in-chapter3.html?m=1&fbclid=IwAR06QFpD34WVkqCppuUO57wfd0EfLnQ1oKDzBKEC4sXDEJMBRgjhUK3WJMU (accessed on 4 April 2021)The results of skull data analyses in the research conducted by Tuamsuk, Nonsrichan, and Sirisilp [16] and interviews with doctors specializing in anatomy and forensic anthropology.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Yosakonkun, S.; Tuamsuk, P.; Chansanam, W.; Tuamsuk, K. Metadata Schema for Managing Digital Data and Images of Thai Human Skulls. Data 2021, 6, 114. https://doi.org/10.3390/data6110114

AMA Style

Yosakonkun S, Tuamsuk P, Chansanam W, Tuamsuk K. Metadata Schema for Managing Digital Data and Images of Thai Human Skulls. Data. 2021; 6(11):114. https://doi.org/10.3390/data6110114

Chicago/Turabian Style

Yosakonkun, Satapon, Panya Tuamsuk, Wirapong Chansanam, and Kulthida Tuamsuk. 2021. "Metadata Schema for Managing Digital Data and Images of Thai Human Skulls" Data 6, no. 11: 114. https://doi.org/10.3390/data6110114

Article Metrics

Back to TopTop