In the early morning of March 26, 2024, the Francis Scott Key Bridge in the Port of Baltimore collapsed after having one of its piers struck by the container ship DALI. Six members of a maintenance crew working on the bridge at the time of the collapse lost their lives. In the days and weeks that followed, the city of Baltimore sufered subsequent economic impacts, estimated at $15 million per day [ 1]. The port re-opened to full maritime operations on June 10, 2024. This industry track paper presents a model of the various impacts mentioned in media articles that covered the bridge collapse. The W3C Web Ontology Language (OWL) is used to identify key industry classes of the port's cargo trafic and use features of OWL to cross-walk various industry classification systems.
The various impacts of the bridge collapse are modeled at high level
in Figure 1. This OWL model is based on the ECLAC 2003 [
Impacts related to the bridge collapse are more relevant to the local community whereas impacts from the port closure may have a national and even a global impact. The time-frame also difers significantly as the Bridge collapse is expected to be rebuilt by 2028 (4 years) whereas the Port closure lasted for 76 days.
A classification system is by its own name, a system of classes and OWL provides a formalized class model. OWL features an Annotation property ”owl:equivalentClass” for equivalent OWL Classes and uses the Data property ”owl:sameAs” for identical OWL Individuals. It is important to note that in OWL, equivalent does not necessarily mean identical. Equivalence applies to two separate things that share the same extension of properties and subclasses. Identity applies to a single omy individual that has been represented more than once. Since we have modeled each of the four Industry †All data used in this paper is publicly available.
CEUR
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Classification Systems using classes, we will cross-walk the systems using equivalence as opposed to identity.
The first step performed in this study was to model each of the four industry classification systems into
an OWL model. Figure 2 shows a high level comparison of the four systems obtained by summarizing
their respective OWL model. The second step was apply the owl:equivalentClass Annotation property
to the equivalent classes across each model. We obtained a set of 2270 cross-references between NAICS
and SICS [
Listing of all Classification Systems reviewed during this study: • Standard Industrial Classification (SIC) 1938, OMB • International Standard Industrial Classification (ISIC) 1948, United Nations • North American Industry Classification System (NAICS) 1997 - OMB / ECPC • Global Industry Classification Standard (GICS) 1999 - Standard & Poor's (S&P) • Harmonized System (HS) 1988 - World Customs Organization (WCO) • Standard International Trade Classification (SITC) 1950 - United Nations • End-Use Commodity Category - Bureau of Economic Analysis • Advanced Technology Products (ATP) - USCB