Development of a Taxonomy for Indexing Web-Based Mining 


Safety and Health Research 

A F Glowacki 1 

1. 	 Computer Scientist, National Institute for Occupational Safety and 

Health, Pittsburgh Research Laboratory, 626 Cochrans Mill Road, 

Pittsburgh Pennsylvania 15236, USA. Email: aglowacki@cdc.gov 

ABSTRACT 

To solve the mining safety and health needs of the future, access to, and 

sharing of, timely and relevant information will be crucial. The next 

generation of the Web will provide tools (RDF, OWL, SPARQL, etc) to 

define and link content for more effective discovery, integration, and 

reuse across applications and organisations. A recent Gartner Research 

Report (Finding and exploiting value in Semantic Web technologies on 

the web, May 2007) predicts these technologies will begin to coalesce in 

ten years. 

Implementing this Semantic Web requires structured web content 

described via metadata (information about information). If an industry or 

enterprise bases its metadata on a common vocabulary, it becomes 

possible to share and reuse information. 

The National Institute for Occupational Safety and Health's (NIOSH) 

Mining web site provides access to more than 1500 NIOSH-developed 

publications, products, and topic pages on issues as diverse as ground 

control, respiratory diseases, and mine emergency management. As the 

site has grown, locating content has become increasingly difficult. To 

improve the searching process, a panel of internal experts representing all 

major research programs was established to develop a controlled 

vocabulary for indexing that content. The outcome is the NIOSH Mining 

Safety and Health Thesaurus, a faceted, hierarchical thesaurus containing 

hundreds of mining safety and health terms organised into 20 facets (eg 

diseaseJ'~ injuries· and disorders; hazardous events and exposures, 

equipment, engineering and administrative controls). 

One immediate goal of this project is to reduce the complexity of 

locating information on the NIOSH Mining web site by implementing 

metadata and faceted information retrieval techniques. Another goal is 

to stimulate discussion in the international mining community regarding 

developing metadata standards so the industry is ready to adopt future 

Semantic Web technologies to improve access to mining safety and 

health information. 

INTRODUCTION 

Since its inception in the 1990s, the World Wide Web has 

grown to tens of billions of documents. While search engines 

such as Goog1e and Yahoo do an impressive job of indexing 

this content, finding information is still difficult. Some 

problems include: 

• 	 a search for 'George Washington' (the US president) returns 

irrelevant content, such as pages about George Washington 

University or George Washington Bridge (false positives); 

• 	 a search on the word 'car' excludes pages where a synonym 

was used, such as automobile (false negatives); 

• 	 much information is locked away in databases that are not 

indexed by search engines; and 

• 	 a search returns tens or even hundreds of thousands of web 

pages, too much information for any human to process; 

To address these and other problems, the World Wide Web 

Consortium (W3C) is developing technolo.,gies for a nextgeneration Semantic Web. The W3C is the primary international 

standards organisation for the Web. Founded by Tim BernersLee, creator of the first web browser and many other core web 

technologies (HTML, HTTP, etc), the W3C is represented by 

more than 400 member companies, universities, and other 

organisations. 

As described by Berners-Lee, Hendler and Lassila (2001), the 

Semantic Web applies structure and meaning to web content, 

enabling software agents to automate the processing of data and 

perform sophisticated tasks without human intervention. It is an 

extension of the current Web: 

... in which information is given well-defined 

meaning, better enabling computers and people 

to work in cooperation. 

A scenario is presented where a hand-held web browser 

automatically schedules a physical therapy session, finding a 

provider in the patient's insurance plan, located within a 

specified driving distance, with an available appointment that 

does not conflict with the patient's calendar. 

While this future Web is far from a reality, many of the 

necessary base technologies have been developed under the 

auspices of the W3C and are already being used to develop 

powerful web applications. This paper presents an overview of 

these technologies and their potential for revolutionising the 

Web. It also presents a thesaurus that is under development at the 

National Institute for Occupational Safety and Health (NIOSH) 

as a preliminary step toward applying semantic meaning to 

mining safety and health information. 

OVERVIEW OF SEMANTIC WEB TECHNOLOGIES

The current Web is a collection of documents which can be 

individually retrieved and read by humans. The Semantic Web, 

on the other hand, focuses on data and information that can be 

manipulated by computers. Achieving this vision requires 

developing common frameworks and tools that allow information 

from diverse data sources to be integrated and combined, as if 

these information sources were one large database. Lam et al 

(2006) describes some of the necessary component technologies 

and tools for developing Semantic Web applications including: 

• 	 ontologies, or controlled vocabularies for representing 

information about a specific knowledge domain; 

• 	 standardised ontological languages for encoding ontologies 

to enable machine readability; and 

• 	 Semantic Web-aware tools, such as tools for querying 

and reasoning about information formatted in ontological 

languages. 

Ontologies 

Historically, the term ontology has been used to describe a 

wide range of classification systems of increasing complexity, 

including: 

• 	 Controlled vocabulary - a simple enumerated list of terms. 

• 	 Taxonomy - a controlled vocabulary organised into a 

hierarchical structure. The parent-child terms may have 

". 	 different types of implied relationships, including whole-part, 

genus-species and type-instance. 

• 	 Thesaurus - a taxonomy with associative relationships, in 

addition to the hierarchical ones. Terms can be defined as 

related, even if they do not have a parent-child relationship. 

Equivalence (synonym) relations are also permitted. 
However, for the purposes of the Semantic Web, ontologies 

extend the concept of thesauri by allowing for even more detailed 

semantic relationships among terms. The goal is to represent not 

just facts but knowledge, and to support inference and reasoning 

by both humans and software. According to the W3C (2oo4a), 

ontologies must specify the following concepts: 

• 	 classes (concepts in a domain), 

• 	 subclasses (relate more specific classes to more general 

classes), 

• 	 clearly-defined relationships that can exist among things, and 

• 	 properties (or attributes) that those things may have. 

Ontological languages 

Ontological (or knowledge representation) languages codify the 

semantic knowledge about a particular domain. In many cases, 

they are constructed from existing taxonomies and thesauri. They 

are intended for processing by computers, not to be read by 

people. The following ontological languages, in increasing level 

of complexity, are approved W3C recommendations: 

• 	 Resource Description Framework (RDF) (W3C, 1999); 

• 	 RDF Schema (RDF-S) (W3C, 2oo4b); and 

• 	 Web Ontology Language (OWL) (W3C, 2004c). 

RDF is a data model that provides limited semantic capability 

for describing resources and their relationships. A resource is 

anything that can be described, such as a book, photo, animal, 

person, or web page. RDF has roots in the Artificial Intelligence 

community. It is based on defining triplets consisting of a subject, 

predicate, and object, each of which is unambiguously defined. 

The means by which this is accomplished and the language 

syntax is beyond the scope of this paper. However, a simplified 

representation of two triplets is shown in Table 1. Based on 

this information, one can determine that the book with ISBN 

o307387 13 5 has the Title No Country for Old Men and is 

authored by Cormac McCarthy. Similarly, Cormac McCarthy is 

the creator of the book No Country for Old Men having ISBN 

0307387135. 

TABLE 1 

Sample triplets that could be encoded in RDF format. 

SUbject Predicate Object 

<isbn:0307387135> <hasTitle> No Country for Old Men 

<isbn:0307387135> <hasCreatoc> Cormac McCarthy 

RDF-S extends RDF with additional features, including the 

capability to define classes and subclasses of resources and 

instances of those classes. For example, the class-subclass 

relationships of a biological classification system (eg Species is a 

subclass of Genus, Genus is a subclass of Family, Family is a 

subclass of Order) can be represented. Members of a subclass 

inherit all attributes and relationships of the parent class. 

Therefore, defining a resource to be a member of a particular 

genus implies that it is also a member of all associated 

higher-level taxonomic groups. 

OWL adds even more semantic capabilities. For example, 

cardinality constraints can be defined (eg a pet can have only one 

owner). OWL also provides the ability to define enumerated 

classes. For example, weekdays can be defined as {Monday, 

Tuesday, Wednesday, Thursday and Friday}. Transitive properties 

can also be defined. For example, if resource A has a specific 

relationship to resource B, and resource B has the same 

relationship with resource C, the implication is that resource A 

also has that relationship with resource C. One very powerful 

feature is the ability to denote that two classes or instances from 

different ontologies are the same thing (eg a 'person' in ontology 

A is the same as a 'human' in ontology B). This allows for 

sharing of information even when two organisations are not using 

the same ontology. Although OWL was approved as a W3C 

recommendation in 2004, extensions are underway. 

Semantic Web tools 

Additional tools needed to fully support a Semantic Web include 

a standard for searching and aggregating information in RDF 

format. That has been addressed by the W3C (2008) SPARQL 

Protocol and RDF Query Language recommendation. Also 

essential are rules and inference engines which can reason and 

make inferences (derive new information) from facts and 

relationships stored in RDF. As explained by Shadbolt, Hall and 

Berners-Lee (2006), OWL contains some inference support, but a 

core language is needed for defining more powerful rules. The 

W3C Rule Interchange Format Working Group is currently 

addressing this problem. Finally, trust and copyright protection is 

a concern. For example, since a Semantic Web would aggregate 

information without human intervention, methods are needed to 

assure users that retrieved information came from trusted 

sources. Much work remains to be done in these areas. 

EVOLUTION OF THE SEMANTIC WEB 

While many core Semantic Web technologies have been 

established, they are still in their infancy. The Semantic Web is 

far from a reality, and some doubt it will ever be fully realised. 

Feigenbaum et al (2007) acknowledge that the grand vision of 

software agents performing automated tasks has not occurred, 

but describe a number of enterprise-level successes, particularly 

in the life sciences and health care fields. 

In a recent Gartner Research report, Cearley, Andrews and Gall 

(2007) estimate that the Semantic Web will evolve slowly over the 

next 20 years. It will begin with web sites implementing semantic 

hypertext, a simpler, though less powerful method of storing 

structured metadata directly within web pages. By 2012, 80 per 

cent of public web sites will use semantic hypertext and 15 per 

cent will use more extensive Semantic Web-based ontologies. 

Some domains will need more complex ontologies~::p:ld extensive 

formal vocabularies, such as life sciences, health care, digital 

libraries, defence, government, energy (the oil industry) and 

financial services. By 2017, the Semantic Web will begin to 

materialise, as standards evolve and vocabularies and ontologies 

being developed by various industries begin to mature. Therefore, 

the authors recommend that enterprises adopt Semantic Web 

technologies in incremental steps. For most enterprises, the 

approach will begin with semantic hypertext, with RDF and OWL 

ontologies reserved for more complex needs. 

SEMANTIC TECHNOLOGIES AND THE MINING 

INDUSTRY 

The mining industry shares many similarities with domains that 

the Gartner report predicts will need more sophisticated semantic 

techniques, particularly health, digital libraries, government and 

energy. Assuming the Semantic Web materialises, it is not 

difficult to imagine how it could impact the mining industry. 

For example: 

• 	 Hendler (2003) argues that these technologies can facilitate 

scientific collaboration among scientists at different 

institutions and across disciplines, enabling scientists to more 

easily share information and to explore related research from 

entirely different scientific fields. However, this will require 

joint initiatives between research scientists and information 

technologists, such as the e-Science initiative in the United 

Kingdom. 
• 	 Spivack (2006) envisions more efficient marketplaces where 

software agents learn about products, services, vendors, 

transactions and market trends and can connect them in 

optimal ways. 

• 	 Semantic Web techniques could facilitate integrating 

information across government agencies, as well as enable 

governments to more effectively target information for 

different audiences (citizens, businesses, etc). 

In many cases, the mining industry may be able to adopt 

ontologies and other formal vocabularies from other domains. 

For example, ANSIINISO Z39.85-2OO7 (the Dublin Core 

Metadata Element Set) provides a standard for tracking 

bibliographic metadata for digital materials (publications, web 

pages, etc), expressible in RDF-S. However, it is unlikely that 

domains outside of the mining industry will develop vocabularies 

suitable for tracking more mining-specific content. 

NIOSH is researching methods to better index and organise 

content on its Mining Safety and Health web site. The goals are 

to improve customer access to our content now, while preparing 

for integration with the next generation of the Web. The web site 

content currently includes more than 1500 publications, 

products, and web pages on topics as diverse as ground control, 

respiratory diseases, dust control, mine ventilation, explosions, 

explosives, hearing loss, diesel, electrical safety, ergonomics, 

emergency management, equipment design and education and 

training. The content is organised into topic pages covering these 

broad topics. However, that structure is ineffective for such a 

large amount of content. For example, the ground control area 

alone includes more than 300 publications. Furthermore, many 

publications relate to multiple research areas. A more flexible 

organisational structure is needed that allows content to be 

assigned to multiple, relevant categories. 

NIOSH conducted a literature search for suit&ble taxonomies, 

thesauri, or ontologies for indexing mining content, with 

particular emphasis on safety and health topics. The hope was 

to reuse existing ""'standards and vocabularies, rather than 

'reinventing the wheel'. Table 2 shows some of the more 

relevant taxonomies identified, which either already existed or 

were under development. 

While some of these classification systems contain useful 

terms for categorising mining safety and health-related web 

content, none are complete solutions for NIOSH. For example: 

• 	 The health industry has well-developed thesauri for indexing 

medical and health content, but most utilise advanced terms 

that are too complex for a non-medical audience. 

• 	 Several impressive occupational safety and health thesauri 

exist. However, they either don't address mining-specific 

issues, or they address them at a very general level. A 

preferable approach would provide high-level terms for 

classifying small collections of content, but more detailed 

terms for classifying larger collections. 

• 	 While NAICS categorises many sectors of the mining 

industry, it often groups them in ways that do not make 

sense from a health and safety standpoint. For example, 

commodities that do not have much in common with each 

other are placed in the same hierarchies. 

• 	 Many of these taxonomies are copyrighted or require a 

purchase fee, which limits their extensibility and reuse by the 

mining industry. 

THE NIOSH MINING SAFETY AND HEALTH 


THESAURUS 


Unable to find an existing taxonomy to meet its needs, NIOSH 

chose to develop a new one. While the focus is on developing a 

controlled vocabulary for indexing safety and health information, 

the taxonomy includes general-purpose mining terms that are 

applicable to other sectors of the mining industry. 

TABLE 2 

Sample taxonomies related to health, injury, safety and mining. 

Category Taxonomy 

Health/injury International Classification ofDiseases (ICD) 

Wodd Health Organization (2007) 

Occupational Injury and Illness Classification System 

Manual (OIlCS) 

US Department of Labor (2007) 

Safety Australian Occupational Health and Safety Thesaurus 

(AOHST) 

National Occupational Health and Safety 

Commission (2003) 

Thesaurus ofInjury Prevention Terminology 

Chang et al (2003) 

Injury Prevention and Safety Promotion Thesaurus 

(IPSP), under development 

Lawrence et al (2006) 

CIS Occupational Safety and Health Thesaurus 

International Occupational Safety and Health 

Information Centre (2001) 

Dictionary and Thesaurus ofEnvironment, Health 

and Safety 

us Department of Energy (1992) 

Mining, 

minerals and 

geosciences 

The Geoscience, Minerals and Petroleum Thesaurus 

(GeMPeT) 

Edinger and Barker (2003) 

Multilingual Thesaurus ofGeosciences (MULTHES) 

Gravesteijn et al (1995) 

WAND Minerals, Mining and Drilling Taxonomy 

Wand (no date) 

Industry 

classifications 

North American Industry Classification System 

(NAICS) 

US Census Bureau (2007) 

Approach 

The NIOSH Mining Safety and Health Thesaurus (NMSHT) 

is being developed as a faceted thesaurus compliant with 

ANSIINISO Z39.19-2005 (Guidelines for the Construction, 

Format, and Management of Monolingual Controlled 

Vocabularies) . 

A thesaurus approach was selected as it provides greater 

flexibility over other types of classification systems such as 

controlled vocabularies and taxonomies. In particular, associative 

relationships can be defined between terms, allowing for more 

structured semantic descriptions. While a thesaurus falls short of 

the power of an ontology, it provides a simpler starting point with 

potentialfor future expansion to an ontology. 

According to Batty (1998), a well-developed thesaurus is 

organised into one or more hierarchical structures, where concepts 

sharing a common characteristic are organised into families called 

facets. Adkisson (2005) describes how a faceted classification 

system might be implemented on an e-commerce web site that 

sells jewellery, allowing customers to browse products on more 

than one dimension, such as jewellery type or material of 

construction. Many current web sites use a faceted navigation 

approach, including amazon. com, overstock.com, and the recipe 

web site epicurious.com. 

A panel of internal content experts representing all major 

research programs was established to develop the initial thesaurus 

facets and terms. In most cases, these were branch chiefs of the 

respective focus areas. Other terms are being obtained by 

reviewing existing classification systems used within NIOSH, 

keywords assigned to individual publications by their authors, and 

from compilations of keywords which visitors have typed into the 

NIOSH Mining web site search engine. 
NIOSH Mining Safety and Health Thesaurus facets 

The NMSHT currently contains 20 facets: 

1. biological; 

2. dusts, gases and emissions; 

3. hazardous events and exposures; 

4. diseases, injuries, and disorders; 

5. measurement and analysis; 

6. engineering and administrative controls; 

7. education and training; 

8. equipment; 

9. geographic regions; 

10. industries; 

11. products and commodities; 

12. mining methods; 

13. populations and target audiences; 

14. physical phenomena; 

15. science; 

16. tasks and activities; 

17. work locations and environments; 

18 media types; 

19. types of materials; and 

20. NIOSH program areas. 

A portion of the engineering and administrative controls facet 

is shown in Figure 1. Much of the NIOSH Mining web site 

content discusses engineering and administrative solutions to 

specific safety and health problems. This figure shows some of 

the thesaurus terms for categorising content related to dust 

control, electrical safety, emission controls, equipment design, 

and explosives safety (a minus sign in front of a term indicates 

the hierarchy for that term is fully expanded; a plus sign 

indicates that child terms are not shown). 

'mm Ol1S~ o:Hltm! 

'" '#~lr ctlttam :syslems 

FHtr3TI0f1 s!,st'!nl$ 

'" P8ftfcte th;afi1~flg 

,. RtHn(?~,al of deposited dust 

",S@@Mng iJf d;u$t sources 

~SGufcewetijn9 

VVatef spraying 

* 'tl'J~illng dust 

~Etedr1cal 

IICircuit jJrotecTIon 

"" Ground ff@u!tllfotectiou 

¢ bt(H.mG' HHlflliofing 

,., OVtSr10tid proMtctiotJ 

'*' SnOiftclfcuit protgJjit)!1 

,. Sutge pmteC!ion 

'" Urlil€f'toftage pretectiDIl 

!lE!~ctf~Wl~ contact protedlon 

'"'Gtoundlng 

'*'lQCk{lut tag1Jut 

*Electn~ mSlJlatiofl 

¥ Stattc etedricif.:y eilrnlMUon 

ilEmi$siJJfi controls 

.~ EqlJiPIT'I€mt desf'@fl 

Ergon1:.r!nic des!@f1 

$ Escape and feSeW? 

Expiosv{es satet:t 

FIG 1 - A section of the NMSHT engineering and administrative 

controls facet. 

Figure 2 shows part of the dusts, gases and emissions facet. 

Three main terms of that facet (dusts, gases and emissions, and 

fumes) are expanded to show the child terms beneath them. 

Combining the facets in Figures 1 and 2, a web page or 

publication about a particular dust control method could be 

indexed by both the type of dust, and engineering control for that 

dust, covered within the content. A user browsing either facet on 

the web site would locate the same item of content. 

mDus!s 

*ltS:!JestuSdUSl 

*CoaidtfS't 

*OPM 

F!oatdust 

'* GraJn crust 

'* UmestBfU: dust 

+R®spit.al)!® dust 

4' Sflh;;{l dust 

$ >t~lQGd dust 

mm GasesitnG em!SShlnS 

,!' ,?.GBTtl:ana 

*it8fOsols 

¥ C@trHTlI1 d~otjd* 

Carbon monoMioB 

'* Compressed ~"ases 

* Die&tell e:m:aust 

* Ethy~ mBr;:aptane 

+ E~hJiene Clxiue 

~FtJmes 

$¥~/@jdlng ttBm@s 

'* Hy'QfQg>'~1I1

'* sllilide 

+·MetnanB 

+Nltrog·Bn 

NiiroClen tMtn:ide 

FIG 2 - A section of the NMSHT dusts, gases and emissions facet. "- J 

Figure 3 shows a detailed display for the thesaurus term pillar 

design, a term from t,e engineering and administrative controls 

facet. The figure illustrates the types of relationships tracked by 

the thesaurus: 

FIG 3 - NMSHT entry for the term pillar design. 

• 	 Equivalence relationship ('use for', abbreviated Up) - three 

terms are considered equivalent, or synonyms, of the 

preferred term pillar design. In this case, the terms are not 

true synonyms, but are treated as such to simplify the 

thesaurus. Content is indexed using the preferred term. All 

references to the synonyms would be redirected to the 

preferred term. In a book index, this can be visualised as an 

entry to 'see pillar design'. On a web site with free text 

search capabilities, a search on a non-preferred term could be 

automatically redirected to instead search the preferred term. 

• 	 Hierarchical relationship ('broader term', abbreviated BT) ­

the preferred term has one broader term, indicating that 

ground control is the parent term that appears one level up in 

the hierarchy. 
• 	 Associative relationship (,related term', abbreviated RT) ­

the preferred term has one related term, room and pillar 

mining (a term from the mining methods facet). This can be 

interpreted as 'see also Room and pillar mining', to direct 

users to a related topic of possible interest. 

While ANSIINISO Z39.19-2005 and OWL permit more 

complex types of relationships between terms, the thesaurus 

development software package being used to develop the 

NMSHT only permits the ones described above. At this stage, 

that is not a serious limitation. The next step of this project will 

validate the thesaurus by attempting to use it to index content on 

the NIOSH Mining web site. Further revisions will likely be 

needed and the thesaurus will be improved incrementally. 

CONCLUSION 

When the Web emerged in the 1990s, few imagined the extent to 

which it would grow in less than 20 years, nor the myriad of 

applications that would be built upon it. Today, it provides 

the means for communication and collaboration, e-commerce, 

entertainment, text messaging, video downloading, and numerous 

other uses. It is not outside the realm of possibility that the next 

20 years may bring even more astounding capabilities. 

Many of the world's most prominent computer scientists are 

determined to make that happen. Spearheaded by the inventor of 

the original Web, the W3C is laying the groundwork for the next 

generation of the Web. The vision is a Semantic Web, where 

semantic capabilities and intelligent software agents automate 

many of the tasks currently performed by humans. 

One key component of the Semantic Web is the development 

of ontologies for :r;epresenting knowledge within specific 

domains. This paper discussed a thesaurus of mining-related 

terms under development at NIOSH. The NMSHT focuses on US 

mining safety and health concerns, is monolingual (English) and 

does not yet have the capabilities of a true ontology. However, it 

may serve as a starting point for discussion regarding the 

requirements of a mining ontology that addresses the needs of 

the international milling community. These discussions will be 

important if the industry is to address its technological needs in 

2025 and beyond. 

ACKNOWLEDGEMENT

The Australasian Institute of Mining and Metallurgy copyright 

does not extend to this article with the United States of America. 

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