Standardization of scientific experimental data representation through ontology-based metadata schema
Halal is a wide area that involved multidisciplinary domains such as biotechnology and medical science in which data and information come from various sources such as laboratory instruments and machines. Halal is defined as the status of certain products that do not contain unpermitted ingredient...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2020
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| Online Access: | http://psasir.upm.edu.my/id/eprint/90509/1/IPPH%202020%201%20IR.pdf http://psasir.upm.edu.my/id/eprint/90509/ |
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| Summary: | Halal is a wide area that involved multidisciplinary domains such as biotechnology
and medical science in which data and information come from various sources such
as laboratory instruments and machines. Halal is defined as the status of certain
products that do not contain unpermitted ingredients. The halal determination for
various samples and ingredients were done using various laboratory instrument, at
which each instrument has a different structure and format of data. These make it
difficult for managing and integrating the data for analysis. Research areas involved
with data management and integration need to explore data standardization as it helps
in bringing data into a common format. Hence, it would help in collaborative research
as well as sharing of data and information. The problem addressed in this study is,
researchers in the determination of Halal components of products require data
standardization as it is hard in managing and analyzing scientific experimental data
from multiple laboratory instruments that have different structures and formats of data.
The objective of this research was to standardize scientific experimental data from
Halal Institute laboratory instruments. To accomplish such goals, an ontology schema
model was proposed to standardize and gives a controlled vocabulary of the scientific
experimental data from Halal Institute laboratory instruments. A metadata
representation structure, based on the proposed ontology schema, was also developed
to give a standard structure to the scientific experimental data representation as well
as simplified data that enables data retrieval and display.
Two types of evaluation were conducted in this study which was; ontology schema
evaluation and metadata representation structure evaluation. Both evaluations were
done using the data files from instruments in the laboratory for raw and processed
materials and liquid analysis, namely Gas Chromatography-Mass Spectrometry (GCMS) and High Performance Liquid Chromatography (HPLC) instruments. The
proposed ontology schema model was evaluated and validated based on completeness
and correctness analysis measures. It was to ensure that the proposed ontology schema
model was designed completely and correctly based on the grouped data and
information from the laboratory instruments.
Based on the ontology schema model evaluation, the completeness percentage of the
ontology schema model was 100%, conform to all of the grouped data Sample Info,
Result Info, Experimental Setup Info, and Graph Info from the laboratory instruments.
For the correctness percentage, the result of the ontology schema model correctly
conforming to the Sample Info data of GC-MS and HPLC instruments which were
50% and 43% respectively. The correctness percentage conforms to the Result Info
and Graph Info data of both instruments were 100%. For the correctness percentage
conformed to the Experimental Setup Info data of GC-MS and HPLC instruments,
was 96% and 86% respectively. These figures indicate that the average recall
percentage of the IEDOS correctly conforms to all of the grouped data was 84%.
Overall, the results gained were satisfactory although the results of the correctness
percentage conform to Sample Info data was slightly lower because of data selection
factors. Metadata representation structure evaluation and validation consists of
precision and recall analysis to measure the accuracy of metadata extraction from the
laboratory instruments data files. The precision percentages were 90% and recall were
100% for both GCMS and HPLC instruments data files. The results gained shows the
appropriate applicability of the proposed ontology-based metadata, in giving a
standardized structure for the scientific experimental data for these instruments. This
could positively facilitate the analysis of the scientific experimental data by giving the
same structure of data to be compared and evaluated. |
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