Economic ResearchWorking Paper No. 56
Mining patent data: Measuring innovation in the mining industry with patents

Alica Daly
Giulia Valacchi
Julio Raffo

May 2019

Mining patent data: Measuring innovation in the mining industry
with patents
Alica Daly
Giulia Valacchi
Julio Raffo1

Abstract
Traditionally, the mining sector has been considered a slow innovator compared to otherindustries, like the manufacturing or pharmaceutical industries. However, we observe an
upsurge in the innovation activity of the mining industry in the first half of the 2000s. During
this period, mining innovation started to increase rapidly after periods of stagnation anddownward trends. To conduct and in-depth investigation of the global trends and patterns
behind this structural change in mining innovation, we formulated a general search strategy
to identify patent activity in this sector. The strategy is repeatable over time and in multiple
databases. It enabled us to produce a dataset of patents in mining and mining-related
technologies. Using this newly-created database we identified at the basis of the structuralchange a switch away from refining technologies into exploration and environmental
technologies probably explained by the took over of the so-called 4th Industrial Revolution.
The types of actors active in the mining innovation also changed across time: there are now
many more individuals, research centers and universities innovating in mining and relatively
less companies. Finally, the country composition in the pool of mining innovation activity hasradically changed with the appearance of China on the global scene starting from early
2000.
Keywords: intellectual property, patents, patent data, mining, innovation, mining services,
METS
JEL code: O34; Q55; L71; L72; L64
Disclaimer
The views expressed in this article are those of the authors and do not necessarily reflect theviews of the World Intellectual Property Organization or its member states.

1 Corresponding author:

alica.daly@wipo.int. Part of this work was conducted when Giulia Valacchi was writing
her PhD thesis at the Centre for International Environmental Studies, Graduate Institute of Geneva.

Acknowledgments
This paper is the result of a research project conducted in the context of the Project onIntellectual Property (IP) and Socio-Economic Development – Phase II (CDIP/14/7). The
authors are grateful to the participants to the WIPO Experts Meeting on Global Innovation
Patterns in the Mining Industries (May 2017, Geneva), at which the initial approach to thesearch was first presented for their valuable feedback and suggestions. In particular, theauthors wish to thank Asrat Tesfayesus and Steve Melnick from the United States Patent
and Trademark Office (USPTO) for carefully reviewing the search strategy and Alvaro
Gonzalez Lopez from the National Institute of Industrial Property of Chile (INAPI) for testing
the search strategy and David Humphreys for his mining expertise. We would also like tothank the USPTO, INAPI, the National Institute of Industrial Property of Brazil (INPI), theCanadian Intellectual Property Office (CIPO) and IP Australia for the provision of data, as
well as Asrat Tesfayesus and Andrew Toole (USPTO) for their assistance with the SearchEngine tool.
NOTE: All the (publicly available) data, data catalogue and data schema, as well as SQL
and STATA scripts used and described in this paper can be obtained upon request.

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1.

Introduction

Products of the mining industry are an essential part of our lives. We need them to satisfy
our everyday needs. The growing worldwide population, together with the rising living
standards, increases the demand for minerals. The mining industry faces continuous
challenges to meet such demand and to fulfill the sustainability requirements imposed bypolicy makers. Innovation is a key instrument to address these challenges.
Traditionally, innovation economists have not considered the mining sector to be very
innovative (Scherer, 1984; Bartos, 2007). According to this view, mining firms are more
likely to be large and capital intensive in order to benefit from the economies of scale whenfacing a demand that relies mostly, if not only, on the price of mining commodities. Mining
firms have few incentives to differentiate through product innovation or branding. Most
innovations are related to cost-cutting processes, aiming to improve their narrow margins.
As a result, mining firms source new technologies from their own production engineering
departments or embedded in products and services obtained from specialized suppliers(Pavitt, 1984).
Nevertheless, there is compounding evidence to suggest not only that the mining sector isinnovative, but also that, recently, it is increasingly so. In most mining countries, this sector
often contains a disproportionate number of innovative firms compared to other sectors(Arundel & Kabla, 1998). In addition, the sector has observed a dramatic increase in all
innovation indicators since the early 2000s.
In Europe alone, around USD 657 million was spent on research and development (R&D) in
mining in 2015. Although it is still much lower than so-called high-tech sectors, such as
pharmaceuticals (USD 10,868 million) or chemical manufacturing (USD 7,416 million) in thesame year, it is still higher than agriculture (USD 654 million) and consumer electronics
manufacturing (USD 347 million)2.
We also observe that intellectual property (IP), particularly patents, have an increasing
importance for the mining industry. There were more mining related inventions looking forpatent protection in the last five years than all those accumulated from 1970 to 2000. Largemining enterprises and firms specialized in mining equipment, technology and services(METS) increasingly make use of IP in pursuing their internationalization strategy. Bothmining and METS companies operate in different countries and patents may help themsecure their IP across jurisdictions and appropriate the knowledge embedded in new
products and processes.
A patent is a legal right that is granted for any device, substance, method or process that is
new, inventive, and useful. Patents give the owner exclusive rights to exclude others fromcommercially exploiting the invention for a limited period of time. In return for exclusive
rights, patent applications must be published and must fully disclose the claimed invention.
As a result of this requirement, the body of patent literature reflects developments in scienceand technology. Furthermore, patent data is rich in information adjacent to technologicalinformation, such as temporal, geographic and bibliographical data. Through the extraction
and analysis of data associated with patent applications, it is possible to measure aspects ofinvention and economic researchers have long used patent applications as an indicator ofinnovative activity.
Using patents as a proxy for innovation is established in the literature (Acs, et al., 2002)
where patent data has been used as indicators of R&D output (Griliches, 1998), to measure
the mobility of inventors (Miguélez & Fink, 2013), and to assess international knowledge
2 See Eurostat (2018).

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flows (Jaffe & Trajtenberg, 1999). In doing so, we acknowledge the limitations of using
patents as a proxy for innovation raised and addressed in existing literature (Lerner & Seru,
2017). If not all inventions are patented, it is largely agreed that a patent embodies an
original result of an R&D activity undertaken by an entity. This applies as well to the case of
the mining industry.
With our search strategy, we can identify patents belonging to the mining sector. We findpatents to the mining sector in two ways. The first is based on technology. We combine
keywords found in abstracts and titles with patent classification marks to create our searchstrategy. The second search is a firm-based search. For the firm search, we make use oflists of mining and METS firms provided by the participating IP offices, as well as data from
Orbis. The results are combined to create a database of mining patents.
The analysis of this newly assembled database enables us to study the structural change inmining innovation in the first half of the 2000s. We compare the mining ecosystem before
and after 2005.
The rest of the paper is structured as follows. Section 2 defines technological innovation in
the mining industry, presenting trends that show evidence of a structural change around thefirst half of the 2000s. Section 3 describes how we created the taxonomy, used for the
search strategy, giving a brief introduction about the mining sector and identifying the partsof the mining value chain where innovation can take place. Section 4 describes therealization of the database as the combination of two distinct searches: the technology
search and the firm-based search. Section 5 presents the results of our analysis and section
6 offers concluding remarks.
2.

Increasing Trends in Mining Innovation

Types of Innovation
As in any other sector, mining firms innovate in their products, production processes ororganizational practices. As input for these innovation outputs, mining firms performresearch and development (R&D) activities, acquire of-the-shelf technologies – typicallyembodied in equipment and machinery – or acquire disembodied technologies suchoutsourced R&D or other technological services. However, measuring these innovation
traits is not always straightforward and this is particularly the case in the mining industry.
We discuss the general global trends of mining innovation as follows, discussing some limitsof these standard indicators.
An unequivocal global R&D expenditure trend is an almost impossible task. The global
mining related R&D expenditure of the last decade is likely to be around USD 140 billion3.
China (47 percent), the United States of America (22 percent), Australia (17 percent),
Canada (8 percent) and Europe (5 percent) are the largest contributors to this global figure.
In Europe alone, around USD 657 million was spent on R&D in mining in 2015 (Eurostat,2018). Although it is still much lower than so-called high-tech sectors, such as
pharmaceuticals (USD 10,868 million) or chemical manufacturing (USD 7,416 million), it isstill higher than agriculture (USD 654 million) and consumer electronics manufacturing(USD 347 million)4.
3 Estimation based on OECD (2019) data in constant 2010 USD.
4 These figures have been created by aggregating Business expenditure on R&D by NACE Rev. 2 activities

Mining and quarrying, Manufacture of basic pharmaceutical products and pharmaceutical preparations,
Manufacture of chemicals and chemical products, Agriculture forestry and fishing, and Manufacture of consumer
electronics, respectively. The data come from Eurostat (2018) and have been reported for the following
countries: Belgium, Bulgaria, Czech Republic, Denmark, Germany, Ireland, Greece, Spain, France, Croatia,

4However, a national R&D series may be able to shed some light on how the trend might
look. Figure 1 shows the spectacular increase of Australian mining R&D expenditure in the
2000s. In the first half of the last decade, the Australian mining sector more than doubled
R&D investment. In the second half, we observe that the investment in R&D by the sector
increased at a much higher rate than had been observed previously. In contrast, we also
observe that mining R&D expenditures have declined recently, coinciding to some extent
with the recent global financial crisis and slowdown.
Figure 1: Business R&D expenditure in mining in Australia, 1993-2016

Source: Australian Bureau of Statistics, Research and Experimental Development, Businesses(cat. No. 8104.0). Note: Business expenditure on R&D for ANZSIC Division B.

It is worth noting that aggregate mining R&D statistics often also include expenditure for theoil and gas industry. In the case for Australian mining R&D expenditures in 2015-2016,
about 33 percent relates actually to oil and gas R&D expenditures5. Similarly, many of theseaggregate R&D figures may or not include R&D performed by firms outside of the typicalmining industry definitions. For instance, the Australian statistics include R&D expenses
incurred by METS firms, but do not include R&D expenses relating to mining technologies
incurred by firms which are not classified as mining or METS nor public R&D related tomining.
With regard to product innovation, the mining industry is a little different to other economic
sectors. The discovery of entirely new products is extremely rare, suggesting that the scopefor product innovation in mining itself is very limited.6 While the discovery and developmentof newly mined products may be rare, the discovery of new commercial deposits of existingproducts is a key element of the mining activity. In fact, when talking about productinnovation in mining, it could be argued that it is the deposit or the mine that is really the
Italy, Lithuania, Hungary, Netherlands, Austria, Portugal, Romania, Slovakia, Finland, U.K., Iceland and Norway.
The numbers, which were given in million Euro, were then converted into million USD using the official exchange
rate EUR-USD for 2015 from the European Central Bank.
5 Only data from 2005 is separated into sub-divisions
6 Most mine products are simple commodities, but there are some exceptions such as industrial minerals soldbased on their chemical and physical properties, precious and semi-precious stones and new uses of existing
mining products.

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‘product’ rather than the mineral recovered from them. Viewed in this way, a company’s
expenditure on exploration becomes a part of its R&D expenditure, even though such
expenditure may not be recognized formally as R&D (Kreuzer & Etheridge, 2010).
While typical aggregate R&D figures do not include the exploration investments, there aresome estimations of the global magnitude of exploration expenditure. The rise in exploration
expenditure in the first half of the 2000s is also remarkable and similar to the R&D trend inAustralia. This noteworthy increase happened across all types of minerals (Figure 2). The
early 1990s also show an increase in the level of exploration expenditure, but of a muchsmaller magnitude compared to what was observed in the next decade. We also observe a
substantial decline after 2012.
Figure 2: Worldwide mineral exploration expenditure (USD bn) by commodity, 1994-2017

Source: S&P Global Market Intelligence, World Exploration Trends; The Economist.

These exploration figures have some limitations as well. First, they include all the activities
related with exploration, many of which might not be innovative. Second, exploration is only
one of the many segments of the mining supply chain where innovation can take place.
Third, it is not uncommon that mining companies outsource exploration efforts to smaller
companies specialized in prospecting. Mining companies take over or invest in thesesmaller companies only in the case of successful deposit identification, in a similar manneras large pharmaceutical companies do with small biotechnology companies.
Furthermore, process innovation and organizational innovation are critical to the mining
industry and are generally aimed at cost reduction. In many industries, the boundaries
between process innovation and organizational innovation are often blurred. This is certainly
the case for the mining industry. Typically, process innovation refers to any improvement of
the production process within the industrial plant. These include changes to the layout,
machinery and any method employed to produce a good or service.

6

Organizational innovation includes everything that happens outside of the production plant.
These include the logistics, management, financial and similar innovations.
In the case of mining, process innovation refers to any improvement happening within themine site, while organizational innovation is any improvement of operations outside the minepremises. However, several mining innovations will easily fit both definitions. For instance,
new exploration methods, such as a drone sending images to a computation facility, or new
transport systems, such as a system controlling loading deep inside the mine and offloading
in a port far away, are likely to happen at both the mine site and elsewhere.
R&D is an indicator of innovative activity. Specifically, it measures the input of the innovative
process. An alternative innovation indicator is patenting activity, which is rather an output
indicator as it measures potential innovation outputs. Patents are easily comparable acrossyears and countries. In order to identify the number of patents associated with mining
activity, we first need to define the different parts of the mining value chain and classify thedifferent technological contributions to the mining industry. This will be discussed in the next
section. Then section 4 will use this categorization to build the methodology for the
extraction of mining patents.
3.

Mining life cycle and value chain: Identifying mining technologies

Most mining operations typically follow a similar process. The primary input for any mining
activity is the land comprising the ore bodies to be extracted. The primary output is the
purified metal or coal, which are in turn primary inputs for a diverse array of manufacturingindustries. Value is created by converting the ore bodies to purified mineral or metal. Eachstage of the lifecycle can include innovation inputs in multiple areas of technology. The
lifecycle of mining, from discovery of an ore body to extraction of minerals and finally toreturning the land to its natural state consists of several distinct steps. The general view ofthe mining lifecycle is shown in Figure 3. The exploration stage includes activities such asore body discovery, mineral determination, resource estimation and feasibility studies. The
mining operation stage includes activities such as mine planning, design & development;mine construction, extraction of ore bodies and mineral processing. Once the ore has beenprocessed, then refining can occur. Each stage of the process is supported by services
such as transport, waste treatment and energy generation.
Figure 3: Simplified view of the lifecycle of a mine

Note: The mining sub-sectors presented in red text indicate the sub-sectors defined in the patent
mining taxonomy.

Based on previous work (INAPI, 2010; Francis, 2015; European Commission, 2016), we
noted the challenges in using a technological approach to define the mining industry. These
challenges include defining the non-core industries and deciding how much of them to bring
into the definition of mining, with the aim to minimize both false positives and false
negatives. However, we decided that it is necessary to define mining technologies as mining
firms also appear to innovate in industries other than mining, and therefore have patents inother technology areas. This hypothesis is confirmed by our data. If we only look at thepatents resulting from the firm search, we see that mining firms also have many patents

7

outside our mining categories. Moreover, there are many METS firms innovating within themining industry and therefore we could not rely on mining firms alone.
In this paper, only mining for minerals and coal are included; quarrying and oil & gas
extraction are excluded7. The definitions of technology sectors in the mining industry for the
purposes of this paper are based on the mine lifecycle and supply chain (Figure 3) andstages in the mineral extraction process.
Based on the knowledge domain and ownership required for each stage of the mining
lifecycle, and our knowledge of patent classifications, we chose to use the mining sub-sector
definitions presented in red in Figure 3 and defined in Table 1 for categorizing patents forthis working paper and the resulting patent dataset. Within each of the sub-sectors, we havealso defined further categories. For example, within processing, there are six categories.
The categories have been determined based primarily on how the International PatentClassification (IPC) divides the sub-sectors. The definitions for the categories are further
elaborated in Appendix C.

7 However, the database may still contain oil & gas related patents as they may refer to techniques that can also

be applied to minerals extraction.

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Table 1: Sub-sector definitions
Sub-sector
Definition for patent mapping
Exploration
The process of finding and exploration of the mineral deposit.
Geological logging; geophysical surveys to record the response of electrical, magnetic and gravity
measures; resource modelling; geological interpretation; block models; surveying and testing the nature ofborehole walls; analyzing minerals/ore by determining their chemical or physical properties; geochemistry.
Computer simulations of blasting, blast fragmentation analysis.
Exploratory drilling: earth or rock drilling tools and methods, such as sonic drilling and rotary air blast;
Apparatus for core barrel extraction; drilling control.
May also include Mine Operation activities such as: Drilling for blast holes
 Mine monitoring systems for ventilation, rock stress & seismic activity.
 Mapping of rock joint sets
Blasting
Blasting used as a method of accessing ore bodies in both open pit and underground mines.
Fuses, detonating devices; explosive compositions and blasting methods.
MiningMine site construction: access roads, tree clearing and top soil removal, processing plants, material handling(Minefacilities, stockpile areas, train loading facilities and waste disposal areas.
operation)
Technologies directly related to mining operations and excavation activities: ground control support, rockbolts, tunneling, stoping, removal of overburden, shaft sinking.
Underground mining equipment, open pit loading equipment: rope shovels and hydraulic shovels,
excavators, front-end loaders, ground engaging tools; surface miners, draglines, bucket wheels.
For hauling and conveying equipment, see also Transport.
Personal protective equipment; underground mine ventilation; safety refuge chambers; methane gas
drainage.
Subsea mining methods and equipment; extraterrestrial mining methods and equipment.
Data processing systems registering or indicating the working of machines relating to mines/mining.
Processing
Beneficiation. Processing of ore after it has been extracted from mines. Coal handling, including washingand screening.
Concentration of minerals by physical methods such as crushing, mill grinding, mechanical separation,
flotation and differential sedimentation; related methods, apparatus and reagents.
Also includes bioleaching.
Metallurgy
Chemical treatment of minerals to produce commercial pure metals.
Smelting; Electrometallurgy, pyrometallurgy and methods and apparatus.
Refining
Production or refining of metals, steel and alloys.
Refining consists of purifying an impure metal, where the final material is usually identical chemically to theoriginal one, only it is purer. It is distinguished from other metallurgical processes that involve a chemicalchange to the raw material.
Transport
In mine transport: hoistway equipment, haul trucks; conveyors for transporting ore to processing facilities.
Ex-mine transport: Vehicles adapted for load transportation; rail and railways.
Automated trucks and rail; checking devices for registering or indicating the working of vehicles; automatic
pilot; other vehicle control (see also Automation).
Construction of roads; Construction of, or surfaces for, roads.
Systems for controlling or regulating non-electric variables specifically for mining vehicles.
Shipping.
Automation
Remote controlled mining systems.
Navigation systems (see also Transport).
Electric digital data processing.
Measuring systems (see also Exploration).
Environmental Environmental aspects of mining such as rehabilitation of mining areas and treatment of waste materials
from mine sites, and mineral and ore processing.

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4.

Methodology

The selection of patents for economic analysis requires a search strategy to identify relevant
patents in databases. In general, economists do use high recall-low precision searchstrategies when retrieving patents for economic analysis. They often rely on patentclassification marks at a high level (such as class only) from well-established classification
systems that correlate industrial sectors to patent classifications (such as those described in
Schmoch (2008), Van Looy, et al. (2015) and Lybbert & Zolas (2014). This approach wasused by the European Commission in their Raw Materials Scoreboard (European
Commission, 2016).
Searches with IPC marks may also provide results with low precision, as some IPC classes
can cover a broad range of industries. For example, the WIPO technology field thatcomprises mining is Civil Engineering and comprises a number of other industries in(Schmoch, 2008).
This approach does not account for the intricacies of the patent classification system, where
examiners classify inventions based on what is claimed, which may be a more generalized
invention that is useful in the industry under investigation. All patents are assigned
classifications, based on classification schemes defined by patent authorities. These
classification schemes are used by patent offices to support the patent search andexamination process and are therefore structured according to technological principles. As aresult, if a technological principle is used in several products or processes, using such aclassification to select patents inherently includes patents which are not related to theindustry in question. In addition, patent classifications denote the inventive concept in apatent. For example, a grinder may be used in the mining industry, but the technicalfeatures of that grinder may also be the same for a coffee grinder. If the inventive technicalfeature of that grinder is the conical burr, the patent will be classified for that particularfeature.
Alternatively, the use of keywords to retrieve patents for economic analysis may seem likean attractive option. However, the way that patents are drafted may mean that many lists ofuses or ingredients are included in the text of a patent to allow the broadest scope ofprotection, again leading to a high recall-low precision outcome. In addition, the same words
can be used in multiple industries. For example, in this case we would like to retrieve
patents about mines, but not about land mines.
To overcome these low precision results, searches in technology fields often take the adviceof subject-matter experts who understand the field, and perhaps more importantly, fromprofessional searchers, who know how to find patent information in these areas (Trippe,2015). In the National Institute of Industrial Property of Chile (INAPI) patent landscape studyof the copper mining industry, patent examiners and industry experts were consulted to
identify relevant IPC subclasses and keywords (INAPI, 2010). They used the IPC
subclasses for the search strategy, and then applied the keywords as filters to narrow down
the results. One of the problems they reported with this approach was that they did not
identify relevant documents because they did not use keywords search terms.
INAPI did an additional search using the names of companies in the copper mining industry
in Chile. This approach of identifying patents in the mining industry was also utilized by IP
Australia. IP Australia posited that it is difficult to provide a definition of mining patents interms of a set of relevant IPC marks as typical mining technologies encompass a wide
variety of technologies. They obtained lists of operating miners and METS firms and usedthem to search patent databases. However, there are problems inherent in using applicant
names, as companies change names and spelling of company names may not be unified,inter alia. To overcome this issue, IP Australia advantageously used the Intellectual

10Property Government Open Data (IPGOD), which is linked to the Australian Business
Register, to uniquely identify Australian mining and METS firms. They also used the firmsthat identified their main business activity in these industries to include further relevant
firms8.
However, this approach only works for local firms and some firms that operate in the mining
industry may self-identify in other industries. Additionally, organizations such as universities
or public research organizations are generally listed in the education industry. To accountfor this issue, IP Australia extracted the IPC subclasses from the patent documents of mining
and METS firms and applied them as filters to patents filed by Australian universities andpublic research organizations. However, this then created a precision problem, as mining
and METS firms filed patents in industries both inside and outside the mining industry.
To overcome the limitations with technology searching and firm searching described above,
we used a multi-pronged approach in order to retrieve patents in the mining and METS
industries with high precision and high recall. In this paper, we describe a methodology for
obtaining a database of patents representing the mining industry, building on the work doneat IP Australia (Francis, 2015). The approach relies on a search based on technologicalinformation in patent databases, as well as data on mining and METS firms. Taking into
account the drawbacks mentioned above, the challenge of how to capture worldwide firms
and technologies produced by METS firms in a vast array of technological fields andscattered all around the world remained. For this reason, we sought the expertise andcollaboration of a number of IP offices: INAPI, the National Institute of Industrial Property ofBrazil (INPI), IP Australia, the Canadian Intellectual Property Office (CIPO) and the UnitedStates Patent and Trademark Office (USPTO).
The database was created using two searches. The first search was a technology search.
We chose to combine keywords found in abstracts and titles with classification marks tocreate our search strategy. In addition, the search strategy considered multiple languages.
This approach presented several benefits, including:

the retrieval of patents defining mining specific products and processes, for example,
the retrieval of grinders for use in the mining industry and eliminating coffee grinders,and,the elimination of irrelevant patent documents, such as patents relating to landmines, by advantageously using classification schemes as pre-search filters.

We assigned our mining taxonomy pre-search in order to make it the search modular andtherefore easier to combine or remove results after the initial search, if appropriate. The
search strategy is repeatable over time and in multiple databases, allowing contributions
from other offices using their own patent data.
The second search was a firm-based search. For the firm search, we made use of lists ofmining and METS firms provided by the participating IP offices, as well as data from Orbis.
The technology search
Data used
The technology search uses two datasets. The first is the 2017 autumn edition of theEuropean Patent Office’s Worldwide Patent Statistical Database (PATSTAT). PATSTAT
offers access to over 100 million patent records from more than 90 patent authorities.

8 For further details on the IP Australia approach see Francis (2015).

11

We also used patent data from WIPO’s patent family database, which is a combination of the
EPO PATSTAT database together with PCT national phase entries stored in the WIPO
Statistics Database.
Patent families
A patent family is a set of interrelated patent applications filed in one or morecountries/jurisdictions to protect the same invention. Applicants often file patentapplications in multiple jurisdictions, thus resulting in some inventions being recorded morethan once. In order to take this factor into account, WIPO has developed indicators related
to “first filed” patent families, which are defined as a set of patent applications interlinked
by – or by a combination of – priority claim, PCT national phase entry, continuation,
continuation-in-part, internal priority, addition or division. Patent families include patentand utility model applications. To avoid double counting, our statistics always refer topatent families as a unit, unless otherwise stated.
Search Strategy Development
For the reasons outlined above, we choose to combine keywords found in abstracts andtitles with classification marks to create our technology search strategy. In addition, thesearch strategy will consider multiple languages.
The first step in the process was to create a subset of patents that contained keywords
related to mining in the title or abstract. The keyword subset was created based on the
keywords listed in Appendix D. Six categories of keywords were used in five languages:
English, German, Spanish, French and Portuguese, the most frequently occurring languages
in the abstract and title tables of PATSTAT. Unlike most keyword searching, the keywords
were only searched in fields made in that language, i.e. English keywords were only
searched in English titles or abstracts. The keywords were searched in the titles andabstracts and assigned a general keyword term, listed in Appendix D.
A second subset of data was created by retrieving all patents comprising at least one E21(Earth or rock drilling; Mining) IPC or CPC mark. These two subsets of data were used as asubset of the whole PATSTAT database to search within, schematically represented in
Figure 4.
Some keyword exclusions are noted, such as mining NOT data mining. In the case ofpatents found based on keywords, observations of IPC subclasses that were not at all
related to the mining industry were excluded instead of using NOT strategies, which can beproblematic. For example, the keyword search retrieves a number of documents with the
French word porte-mine (mechanical pencil), so it is simpler to exclude the class B43 (writing
implements) from the subset of data, rather than exclude the term porte-mine in the searchstrategy. Similarly, we exclude the IPC class for land mines. IPC marks that are excluded
are noted in Appendix E.

12Figure 4: Schematic representation of search strategy

Taxonomy Assignment
For the purposes of statistical analysis, we wanted to identify a unique technology sub-sector
and category for each patent record. However, it is not straightforward to assign patents to asingle category. When examiners classify patents, they assign classification symbols
according to the technological features in patent applications. A patent application that
relates to multiple technological features can be assigned several IPC symbols. As a result,the patents in our mining dataset will inevitably be classified in multiple classes, andtherefore multiple mining categories.
On the other hand, rules that patent examiners follow when classifying patents9, such as therequirement to classify all inventive concepts, claimed or disclosed within the patentdocument can be a great help in assigning a single sub-sector for a patent. This is because,in general, such different inventive concepts are represented by different claims, alternative
variants or different categories of subject matter (for example, a product and a method of its
production), and, as such, one might consider the product to be the fundamental inventive
concept10. Therefore, we can assign a single category based on a hierarchical approach
where the product is the primary invention. IP Australia used this principle in the Patent
Analytics Study on the Australian Pharmaceutical Industry (IP Australia, 2015), where new
pharmaceuticals are generally classified in the IPC scheme in both section C andsubclasses A61K and A61P, whereas known chemical entities with a newly claimed
medicinal use are classified in A61K and A61P only. Therefore, if the patent application had
an IPC mark in section C, the fundamental inventive concept would be a new chemical

9 Guide to the International Patent Classification

http://www.wipo.int/export/sites/www/classifications/ipc/en/guide/guide_ipc.pdf
10 U.S. MPEP §905 https://www.uspto.gov/web/offices/pac/mpep/s905.html#ch900_d22347_283e8_366

13compound, whereas if there is no mark in section C and there is a mark in section A61K,
then the fundamental inventive concept would be a new pharmaceutical composition.
The same principle may apply in using the first type attribute in the 209 table in PATSTAT,
where the first-listed classification assigned by the examiner is the one that most completely
covers the technological subject matter of the disclosed invention. The first position symbol
is identified as the first mandatory symbol listed on the classification form11. However,experience has shown that the first listed mark cannot always be relied on for this purpose instatistical analysis because in some data systems and jurisdictions the classification marks
are merely listed alphabetically.
For these reasons, we chose to assign one category to each patent based on a manuallyassigned hierarchy of technologies that occur in the mining sector. To do this, eachcategory was assigned a mining category id number when performing the search and thenthe minimum of all the mining category id numbers assigned to each patent was taken to
determine the principal category for each patent. The mining category id numbers are listed
in Appendix F. For example, if a patent application is assigned both categories 3.3(separation) and 6.1 (exploration), then the minimum of 3.3 would be the final category forthat patent application. This in effect creates our own first mining category or fundamental
mining inventive concept for each patent.
Keeping in mind that the aim of the search strategy is for it to be modular and replicable, thisis when the IPC exclusions become important. The exclusions need to be given a mining
category id in order for them to be excluded by the minimization process. All IPC classes
listed in Appendix E are excluded. Generally, patents with excluded IPC marks are excluded
outright, even if they are classified in a mining category, (mining category id < 1) and someare excluded after the possibility of some mining categories higher in the hierarchy havealready been assigned. However, all exclusions were given a mining sector id(mining_top_id) of 100, enabling the easy filtering out of exclusions at any stage in theanalysis process.
Search QueriesWith the two subset of data generally referring to the mining industry, we took advantage ofour mining sub-sector and category classifications to assign each patent to its relevant
categories during the search process.
The search queries were based on the IPC and keyword combinations outlined in Appendix
B based on the overall understanding of the technology. For example, in the Floatation
category in the Processing sub-sector (see Table 2), the following search strings were used:

11 U.S.

(IPC or CPC)=B03D AND (IPC or CPC)=E21(IPC or CPC)=B03D AND ((abstract or title) contains (mineral OR ore))
IPC=(B03D 103/02 OR B03D 103/04 OR B03D 103/06 OR B03D 103/08 OR B03D
103/10)CPC=( B03D 1/021 OR B03D2203/02 OR B03D2203/04 OR B03D2203/06 OR
B03D2203/08 OR B03D2203/10)

MPEP §905 https://www.uspto.gov/web/offices/pac/mpep/s905.html#ch900_d22347_283e8_366

14

Table 2: Flotation category search strategy (portion of Appendix B)
Sub-sector

Processing

Category

Flotation

IPC/CPC

IPC
combination

keyword combination

B03D

E21

mineral OR ore

B03D 103/02 to /10
B03D
1/021
B03D2203/04 to /10

For the mining commodities, some differentiation is also possible, but it was considered too
difficult to separate based on product due to the nature of patent drafting. In addition,
outputs of mineral mining such as gold, iron and aluminum were not included as keywords
due to the likelihood of including many patents unrelated to the mining industry per se.
A more detailed assignment of search strategy and technology categories can be found in
the accompanying search strategy scripts.12
The final technology subset for analysis consisted of patents includes patents in Mining
sub-sectors (see Appendix F):










Blasting (mining_top_id = 1)
Environmental (mining_top_id = 2 or 102)
Processing (mining_top_id = 3 NOT mining_cat_id = 3.31)
Mining/Mine operation (mining_top_id = 4 or 9)
Transport (mining_top_id = 5)
Exploration (mining_top_id = 6 NOT mining_cat_id = 6.29)
Automation (mining_top_id = 10)
Refining (mining_top_id = 11)
Metallurgy (mining_top_id = 12).

The firm search
Data used
The second search was a firm-based search. For the reasons outlined above, we choose touse both mining and METS firms in our search. In order to do this, we made use of lists ofmining and METS firms provided by the participating IP offices, as well as data from Orbis.
Orbis
Orbis is a commercial database from Bureau van Dijck that contains information on morethan 120 million companies around the world. It focuses on the biggest players in themarket, which are also the most active ones in terms of research activity. It is a large
database but may not be comprehensive. For example, it may lack information aboutcompanies from developing countries. Each firm in the Orbis dataset has a unique firm id
called bvdid. The firms are categorized by the main sector of operation. We extracted firmand patent data from Orbis for firms in NACE classes corresponding to the relevant ISIC
classes for Mining and METS firms outlined in Appendix G. Data was extracted from theSeptemebr 2017 edition of Orbis.
Orbis also provides information on the patents held by a firm. Through the patent application
numbers, we matched the bvdid from Orbis with person_id in PATSTAT.

12 Available upon requests.

15

Australia
Australian firms were extracted from the Australian Business Register using ANZSIC classes
equivalent to the ISIC classes in Appendix G. Additional lists of Australian mining and METS
firms were also obtained from Geoscience Australia and the Department of Industry,Innovation and Science.
If the Australian mining or METS firm is a registered business in Australia, it has an
associated Australian Business Number (ABN). With the ABNs in hand, we extracted any
Australian patents associated with these firms from the 2017 edition of the IPGOD database,which links all Australian IP rights to firm information (Man, 2014). From the IPGOD, we
extracted person_ids from PATSTAT by either matching the Australian patent numbers or
the PATSTAT appln_id numbers given in the IPGOD.
United States
The USPTO provided a list of establishments from the National Establishment Time-Series(NETS) Database, retrieving establishments with a North American Industry Classification
System (NAICS) code for mining or METS equivalent to the ISIC classes in Appendix G, forheadquarters active in 2014.
Establishments were retrieved, rather than firms or headquarters, because the NAICS codefor different establishments associated with the same headquarters can be different. When
extracting the data, the USPTO observed that the NAICS for many headquarters were not in
the list of NAICS codes selected to represent the mining industry.
CanadaCIPO provided a list of company names involved in the mining sector in Canada, including
mining companies headquartered and/or active in Canada
Chile
INAPI provided a list of METS companies obtained from Fundación Chile and a list of large
mining companies operating in Chile obtained from the Mining Council of Chile.
BrazilINPI provided a list of mining companies obtained from the Brazilian National Department ofMineral Production (DNPM). DNPM only selected holders of active mining rights whenproviding the data.
Combined firm list
Each firm name provided was furnished with a unique firm identification number, which also
identified the source of the firm name.
Name matching
While we were able to extract person_id data from PATSTAT for the lists of firms from Orbis
and Australia, this was not the case for all the data. Clearly, name disambiguation andharmonization would add important value to our dataset, though the best matching approachpartly depends on the research question at hand.

16

The existing literature has disambiguated both inventor and applicant names, through theirnames as well as other information contained in patent documents and many statistical
databases are produced with names already disambiguated or harmonized. However, manyof these approaches are far from perfect (see (Raffo & Lhuillery, 2009) and name matchingover databases such as the PATSTAT database, which contains 55 million name records
from over 100 years, is not straightforward.
To create this dataset we used a combination of the MATCHIT matching algorithm in STATA(Raffo, 2015) and the “SearchEngine” (Doherr, 2017; Czarnitzki, et al., 2015). In essence,
the matching algorithms select pairs of patent applicants and firms, who are likely candidates
to be the same firm, due to homonymy or similarity of names. While every attempt wasmade to match all firms to patent applicants, we cannot exclude that some patents may havebeen missed due to false negatives. Since the lists of firms provided to us were for currently
active mining firms, we restricted the name matching to a subset of PATSTAT data from1990.
The resulting data was a list of firms matched with a person_id from PATSTAT, if the namewas found in PATSTAT. Disregarding false negatives, unmatched firm names means thatthose firms have no patents.
The combined firm list matched with PATSTAT person_ids was then used to extract all thepatent applications relating to mining and METS firms from the database.
Name cleaning
The results from the technology search and firm search were combined and the applicant
names were cleaned with a combination of probabilistic record linking in STATA (Wasi &Flaaen, 2015) and fuzzy matching in Open Refine.
5.

Analysis

This section describes the results of our analysis. The goal is to study the outcomes of thestructural change in investment in mining innovation observed in the early 2000s.
The patents in the mining dataset go back as far as 1826. However, in this section most of
the analysis is based on indicators related to patent families13 with an earliest priority date
between 1990 and 2015. This period of time is crucial for studying the surge of mining
innovation after 2005.
The total number of patent families in the mining database file between 1990 and 2015 is6,501,697. Out of those, 181,825 families were found in both the technology and firm
searches, 6,038,498 families were found in the firm search only and 281,374 families were
found in the technology search only (Figure 5). From these results, we can see that there is
only a small amount of overlap between the two search strategies. This demonstrates thatneither approach can be considered fully comprehensive, and the type of search done forpatent analysis really depends on the type of analysis that will be done on the data, in
addition to the types of data that will be linked to the patent data for analysis. For example, if
you have firm level expenditure data available, a firm-based patent search will be useful, but
used cautiously as firms may patent in multiple technology areas.

13 In the following analysis the terms patents and patent families are considered the same/used interchangeably.

17

Figure 5: Patent families potentially related to mining by source (earliest priority year
1990–2015, inclusive)

Source: WIPO Mining Database.

18

Comparison of patent families
We use patent families as our unit of analysis in order to identify single inventions or togroup closely related inventions together to avoid double counting of patent publications(UKIPO, 2015; Dechezleprêtre, et al., 2017; Martínez, 2011). However, there are multiple
definitions of a patent family. Figure 6 illustrates the differences in magnitude between two
types of patent families over time: INPADOC extended families (EPO, 2017) and first filed
families (chosen for analysis in this paper). Although there is between a one and four
percent difference between INPADOC families and first filed families in the technology
subset, the general trend of families is the same over time (see also Fink, et al.(2013) for
further discussion of WIPO patent families).
Figure 6: Comparison of patent family types, by earliest priority year

Source: WIPO Mining Database (technology subset).

From the technology search, we identified a total of 463,199 patent families filed between
1990 and 2015, inclusive. Figure 7 shows the number of patent families relating to mining
technologies filed since 1990. It shows a relatively steady number of inventions filed
between 1990 and 2003, with an exponential growth observed from the second half of the
2000s. Differently from R&D and exploration figures, we observe a slowdown but not areverse of trend after 2012.
Keeping in mind that trend in overall patent applications has continued to increase (thepatent surge) (Fink, et al., 2013), we also examine of the patent families from the technology
search as a share of all patent families over the same time period (Figure 8). Mining patents
have outpaced the overall patenting activity since 2004. After more of a decade of decline in
the 1990s and early 2000s, we observe the share of mining patents to almost double from to2004 to 2013. We can also see a slight fall since 2013, when the share fell back to 2009-10
levels in 2015 compare to the structural change.

19Figure 7: Patent families from the technology search, by earliest priority year

Source: WIPO Mining Database (technology subset)

Figure 8: Technology subset patent families as a share of all families, by earliest priorityyear

Source: WIPO Mining Database (technology subset)

20

Utility models
Utility models exist in some countries to protect innovations which do not fulfill standard
patentability requirements, but which may have an important role in a local innovation
system. Although a utility model is similar to a patent, it is generally cheaper to obtain andmaintain, has a shorter term and less stringent patentability requirements.
In this paper, patent families include both families associated with patent applications forinventions and families associated with utility model applications. One of the reasons there
may have been a large surge in patent filings after 2004 is the large rise in filings of utility
models since that time (Figure 9), which has risen from around 11 percent of total families in1995 to 42 percent of total families in 2015.
Figure 9: Comparison of patent types, by earliest priority year (technology subset)

Source: WIPO Mining Database (technology subset)

Top Innovating Mining Fields
As discussed above, we chose to assign a single mining category to each patent family inthe analysis. To see the difference between doing this and having multiple categories perpatent family, we have produced comparison data in Table 3. The most significant
difference between the two is that there are four times the number of patent families in themining category in the multiple-assignments compared to the single assignments (Table 3),
which is to be expected based on the search field. There are also a lot more automation
patents in the multiple-assignments compared to the single assignments, due to a vast
majority of automation patents also falling under the transport category. For this reason, we
also included an Automation flag as part of the data for analysis.

21

Table 3: Mining patents by category, 1990-2015
patent families
Miningmultiple sectors single sector
sub-sector
per family
per family
Automation
14,003
1,141
Blasting
2,831
2,814
Environmental
95,71358,426
Exploration
140,345
114,676
Metallurgy
13,338
4,868
Mining545,482
144,144
Processing
23,823
21,202
Refining
97,48088,362
Transport
35,59527,566Grand Total
663,322463,199
Source: WIPO Mining Database (technology subset)

We observe mining innovation all across these subsectors. The mining subsectors where
we observe more innovation are mining/mine operation (31.1 percent of total mining
innovation), exploration (24.8 percent) and refining of extracted materials (19.1 percent).
Other fields involve less innovation: blasting (0.6 percent), environmental improvements(12.6 percent), metallurgy (1.1 percent), processing (4.6 percent) and transport (6 percent)(Figure 10).
Figure 10: Mining technologies by subsectors, 1990-2015

Source: WIPO Mining Database (technology subset)

22

Figure 11: Distribution of mining technologies in subsectors by period, 1990-2015

Source: WIPO Mining Database (technology subset). Note: only the top six subsectors included.

Some subsectors have contributed to the recent mining innovation uptick more than others.
Comparing the distribution trends, there has been a switch away from refining mostly to
exploration and transport (see Figure 11). There is also a smaller share increase fromenvironmental innovation and processing subsectors. The industry’s technological responseto the extractive products demand surge seems to have put less emphasis on improving
refining methods. This may be a consequence of the declining quality of mined ores, which
may make it inefficient to invest in new refining techniques. Firms could prefer to dig newmines instead. The exploration and transport trends are likely to relate with the industry’s
increasing need to discover new deposits in farther locations to face rising demand.
Similarly, the increase in share of environmental technologies are probably linked with awider social and industry awareness of the environmental impact of mining activities.
In addition, the so-called fourth industrial revolution – namely advances in information
technology and artificial intelligence – may offer even more potential for raising productivity
in knowledge-based activities like deposit modelling (exploration), logistics (transport) or
waste management (environmental), among many other examples. Interestingly,
automation innovation in mining increased both in volume and share during the 1990s andearly 2000s when the overall mining innovation activity was relatively flat (see Figure 12).
Automation innovation had a slow start when mining innovation started to pick up its pace inthe second half of the 2000s. However, we now observe a spectacular second boom of
automation in both volume and proportion of mining patents, which is likely to relate with the
spread of digitalization.

23

Figure 12: Patents families in automation class over time

Source: WIPO Mining Database (technology subset)

Where is all this mining innovation originating from?
The distribution of economies contributing to mining technologies does not match one to one
with the typical mining producing ones (Figure 13). Only China and the United States gather
more than 10 percent in both mining output and innovation. The Russian Federation is the
only other economy to have more than 10 percent of mining output but it generated less than
1 percent of the mining innovation. Japan, generating more than 10 percent of theinnovation but producing less than 0.1 percent of the output, is the opposite case. On adifferent scale, some other economies have a relatively balanced output-innovation ratio as
China and the United States. Australia, Canada and Norway produce more than 1 percentof the mining output and generate about 1 percent of the innovation. Conversely, the United
Kingdom generates more than 1 percent of the mining innovation and produces slightly lessthan 1 percent of the output. One order of magnitude lower, Spain having about 0.1 percent
of both output and innovation is another example.
Countries such as Brazil, Chile, India, Indonesia, Iran, Iraq, Kazakhstan, Kuwait, Mexico,
Qatar, Saudi Arabia, South Africa, and Venezuela – in addition to the already mentioned
Australia, Canada, Norway and the Russian Federation – produce substantially more mining
output than Japan or even the United Kingdom, but they produce much less mining
innovation. On the contrary, countries such as Austria, Belgium, Denmark, Finland, France,
Germany, Italy, Netherlands, Poland, Republic of Korea, Sweden and Switzerland join Japanand United Kingdom in their disproportionate contribution to mining innovation given theirproduction. It is also important to note that these economies – including US, China,
Australia, Canada and Norway – not only generate most of the mining technologies but they
are also where most of the patent protection is sought for. Very few mining technologies
seek patent protection in countries with high mining output but relatively low innovative one.

24

Figure 13: Mining production and innovation by country, selected countries
100.000%
China

United States

10.000%Japan

Mining patent families (%)

Republic of Korea

Ukraine1.000%

FranceSwitzerland

0.100%

Austria

Belgium

Russian Federation

Germany

PolandUnitedKingdom

CanadaAustralia

Netherlands
FinlandSwedenNorwaySouth Africa

Brazil

Italy
Spain

India

Chile

Denmark

Saudi Arabia

MexicoArgentina

Venezuela

Kazakhstan

0.010%

KuwaitIndonesia

United Arab Emirates
Iran

Qatar

0.001%

Iraq
0.000%
0.000%

0.001%

0.010%

0.100%
Mineral production (%)

1.000%

10.000%100.000%

Source: WIPO Mining Database (technology subset) and Reichl et al (2018). Notes: sample
contains only top mineral producing and top mining patenting countries.

What explains these different patterns between mining production and innovation? One of
the most plausible explanations is that mining innovation – particularly breakthroughpatentable one – is more likely to happen in functioning innovation systems not necessarily
based on mining operation countries. The U.S., Japan, Republic of Korea, Germany, United
Kingdom and, lately, China are well-known technological hubs where innovation acrosssectors spurs more rapidly than the rest of the world (WIPO, 2018). These innovation
systems – and those from other OECD economies – host innovative stakeholders fromdifferent industries which are likely to develop mining innovation. Many METS companies
originate and conduct their R&D in countries which are not necessarily where they apply thetechnology, such as Japan, Switzerland or the Republic of Korea.

25

Figure 14: Mining innovation by top country of origin

Source: WIPO Mining Database (technology subset)

Undeniably, China, Japan, United States, Germany, Republic of Korea, France, United
Kingdom, Finland, Netherlands, and Canada were the largest contributors in volume to therecent mining innovation upsurge (Figure 14). These ten economies account for roughly 90
percent of all mining technologies. Within these, China observes the highest increase during
the last decade.
Contribution to the mining innovation boom did not come from the usual suspects
Despite China’s impressive growth in volume, this is not what explains the rapid increase in
the world’s mining innovation relative to all innovation. Indeed, China’s rapid innovation
increase for all technologies outpaces its mining innovation trend.
This is because the concentration of absolute mining innovation tells very little about thecountries’ technological specialization in mining. Many nations where mining operations are
conducted may have a disproportionate amount of mining innovation in comparison to theiroverall innovation. Moreover, given the different country size and propensities to patent,
comparing the overall levels of patenting activity between countries can be, to some extent,
misleading about where the most specialized mining innovation may reside.
In order normalize these effects, we use the relative specialization index (RSI), whichindicates as positive value implies that the country where mining innovation is more26

important than the average (Figure 15)14. A negative RSI means that mining innovation is
not particularly dominant compared to innovation in other industries.
Figure 15: Mining patents share by country, selected countries

Source: WIPO Mining Database (technology subset)

14 The RSI measures the relative share of mining innovation of a given country with respect to the share ofmining innovation of all countries. The RSI calculations are based on the following formula:
𝑃𝐶𝑀⁄ 𝑀
𝑃𝐶,𝑇𝑜𝑡

𝑅𝑆𝐼 = log10 (𝑃𝑀𝑊⁄𝑀) where 𝑃𝐶𝑀 is all mining patents from country C (in all technology fields); 𝑃𝐶,𝑇𝑜𝑡
is total

𝑃𝑊,𝑇𝑜𝑡𝑀
mining patents from country C; 𝑃𝑊
is total mining patents filed all across the world; 𝑃𝑊,𝑇𝑜𝑡 is total patents filed
across the world. The calculation considers the country of origin; for a technical definition of country of origin
please refer to Appendix H.

27

Figure 16: Mining relative specialization index (RSI), selected countries

Source: WIPO Mining Database (technology subset)

It is not surprising that countries where mining represents a significant part of the economic
activity are relatively specialized in mining innovation. Chile, South Africa, Australia,
Canada, the Russian Federation and China are mining producing economies where theshare of mining innovation exceeds the world’s average. Brazil and India, however, arenotable exceptions to this pattern. The US, another top producing mining economy, is only
marginally not specialized in mining technologies. While the relative ranking of countries did
not change radically before and after the mining innovation surge, we do observe that thedegree of specialization of many countries did change. This is also informative about theircontribution to the recent surge relative to all technologies.
In this respect, we observe that traditionally mining producing and specialized economies
such as Chile, South Africa, the Russian Federation and China have actually diminishedtheir specialization in mining innovation; and, thus, these economies have not contributed to
the recent relative upsurge. Australia and Canada, on the other hand, have increased theirmining relative specialization, which implies that these contributed to the overall surge.

28

Even if still not specialized in mining innovation, the United States of America and Brazil
have also contributed to the recent relative boom. During the last decade, these economies
decreased their negative relative specialization becoming almost positive. Japan and India
have continued to specialize outside of the mining domain, also contributing negatively to therecent relative surge.
As discussed above, the increase of mining innovations related to exploration, transport andautomation explain in part the recent surge. We now dig deeper to understand which are thecountries contributing the most to these subsectors booming (Figure 17). The first stylized
fact is that mining subsector specialization within countries is fairly stable in rank, but theycan vary substantially in their relative intensity.
Most of the increase in the exploration subsector is not coming from the traditionallyspecialized economies. All four specialized economies in exploration – namely Canada,
China, the Russian Federation and the US – diminished their relative specialization. China
even recorded a negative index after the surge. While still not specialized in exploration,
Australia, Chile and the Republic of Korea increased their relative specialization in thissubsector and are probably among the largest contributors to the exploration booming
relatively to the other sectors.
Among these economies, Chile was the only country specialized in mining transport thatdeepened its specialization. While still not specialized in transport, Australia was the only
other selected country that improve its relative specialization in this subsector. Brazil andChina remain specialized in mining transport but have both diminished their relative
specialization. Canada, the Russian Federation, the Republic of Korea and United States ofAmerica have been specializing even more outside of the transport domain.
The US, Canada and Australia, are more specialized in automation compared to lowermiddle income and upper-middle income nations such as China, Brazil, Mexico and India.
This is also the case of countries which are not particularly mining oriented, such as
Sweden, Singapore, Israel and Belgium. This is also because mining automation innovationis concentrated in METS firms (96.8 percent) rather than mining firms. It seems that mining
firms prefer to outsource this type of innovation. METS firms innovating in automation do notneed to be located in mining countries. They can conduct their R&D abroad and then sell
their technologies to operating miners. High-income countries have an advantage in hightech industries favoring the development of automated technologies. In addition, the higher
income economies also producing mining output have stronger economic incentives to makeuse of automation technologies in order to mitigate higher labor costs.
These patterns only apply partially to the dynamics of automation specialization within these
economies. Australia, the Republic of Korea and the United States of America reinforced
their relative specialization in automation in a remarkable fashion during the mining
innovation booming period. In contrast, Brazil and Chile’s specialization in automation
reversed in a similar spectacular way. Canada still is fairly specialized in automation but lost
some of its intensity during the last decade. The Russian Federation only deepened its lackof specialization in automation. Even if still extremely not specialized in automation, China
improved its automation RSI substantially.
The selected economies are particularly weak in environment specialization. Only Chile, theRepublic of Korea and the United States of America show a positive RSI for environmental
technologies. However, most of these economies are improving their specialization in thelast decade. In particular, the Republic of Korea deepened its environmental specialization.
Australia, Brazil, Canada, China and the Russian Federation improved substantially making
their RSI almost positive. Conversely, Chile and the United States of America are the only
ones in this sample that worsened the environmental specialization.

29

Figure 17: RSI by mining sub-sector, selected countries

Source: WIPO Mining Database (technology subset)

30

A complex mining innovation ecosystem
Companies and other stakeholders are accountable for the mining innovation boom.
Established companies – both mining and METS – created about two thirds of the mining
related technologies in our data. Individuals – likely on behalf of startup and microcompanies – originated almost a quarter of these technologies. Academic institutions
produced the remaining technologies, where public research organizations (PROs) anduniversities generated 9 and 6 percent, respectively.
Companies and individuals mostly carried out mining innovation. However, in recent
years, there has been a rise in the participation of universities in the innovation ecosystem(Figure 18). They were almost totally absent from the scene before the 21 st century. Thismay be the result of the increasing number of collaborations between universities andcompanies. More and more mining firms finance university programs focused on mining
studies to shape high-skilled human capital. For example, the collaboration between Valeand many universities in Brazil; the historical collaboration between Noranda and McGill
University in Canada; or the success of Cooperative Research Centres in Australia(Amburle, et al., 2019).
Figure 18: Number of mining patents over the years by type of stakeholder

Source: WIPO Mining Database (technology subset)

In most of the cases, mining companies establishing collaboration with academia hired thehighly qualified human capital directly, creating channel for the development of innovations.
This also explains why we observe very little co-patenting activity. In the period 1970–2015,
only 4 percent of total mining patents had two or more applicants. This share has been
constantly decreasing over time, from 9.3 percent in 1970 to almost 1 percent in 2015. Mostof the collaboration activity relates to individuals (71.7 percent) and private companies(25.7 percent). PROs (1.7 percent) and universities (0.8 percent) rarely appear as coapplicants, despite the above mentioned many collaborations with the private sector.

31This may due to specific and reserved contractual agreements among the parties involved
which may assign the patent only to the private partner.
Within the academic sector, PROs have seen a comeback in the mining ecosystem in recent
years. Historically, these institutions have been a large promoter of mining innovation from themid-70s to the beginning of the 90s. They were particularly present in the Soviet Union, where
80 percent of PRO mining patents originated from in the period 1970–1989. Since 1990, PROinnovation activity slowed down greatly until 2010. The fall of the Soviet Union explains in agreat extent this sudden drop of PRO patents. However, many other state-funded researchorganizations in the West also closed or diminished their operations during the 1990s, such as
the U.S. Bureau of Mines in 1995 and the U.K.’s Warren Spring Laboratory in 1994.
Accounting for 56 percent of PRO mining patents in the period 2000–2015, China-basedPROs explain at large their recent trend.
Despite the private companies are the largest contributor of mining technologies, only asmall portion of mining and METS firms file for patents. Within these, METS firms arearound 10 times more likely to file for patent protection than mining companies (Table 4).
About 3.8 percent of METS firms file patents compared to only 0.4 percent of mining firms.
Mining firms patent significantly less than firms in other sectors, such as pharmaceuticals(5.8 percent), chemical manufacturing (2.5 percent) and manufacturing of consumer
electronics (5.5 percent). However, their patenting rate is still much higher than the one
observed for firms in agriculture (0.05 percent).
Table 4: Mining firms with and without patents
Firm sector
METS

MiningOil & Gas
Quarrying

Coal
Metal ore
Nonmetallic mineral

Number of firms
With patents
Without patents
4712
3.8%
125,011
96.4%
174
0.3%
49,897
99.7%
321
0.4%
77,584
99.6%
53
0.9%
6,218
99.2%
838
1.5%
57,421
98.5%
649
0.3%
192,086
99.7%

Source: Orbis and WIPO Mining Database (firm subset)

The fact that mining companies get exclusive operation rights as a result of exploration may
explain in part this low. Firms finding new mineral deposits can obtain exclusive and timelimited rights over those resources in a manner similar to the patent system. Investments in
exploration innovation may be fully appropriated with such exclusive rights without the needto get patent protection. This parallel may help explain the low levels of mining firms withpatents. However, mining firms file most their mining technologies precisely in the
exploration sub-sector (Figure 19).

32

Figure 19: Mining and METS firms by technology, by earliest priority year

Source: WIPO Mining Database (firm subset)

Figure 20: Patent families of mining firms by WIPO technology field

Source: WIPO Mining Database (firm subset)

33

Still, the most of the patenting activity by mining firms is not related with mining technologies.
An analysis of the WIPO technology fields show that electrical machinery, apparatus andenergy is the largest field for mining firm patents in non-mining technologies (Figure 20)15.
Figure 21: Number of years METS and mining firms are active in patenting

Source: WIPO Mining Database (firm subset)

Figure 21 plots the number of years METS and mining firms in our database have filed apatent out of the 26 years between 1990 and 2015, inclusive. By comparing the two not only
do we notice that the number of METS firms with patents is substantially higher than that ofmining firms, but also they patent on average for a longer period of time. Only seven mining
firms patent in every year of the 26 years; compared to 224 METS firms. This again
highlights the central role that METS firms play in mining sector innovation.
A further reason for the recent surge in patents may be the increase in patents filed in China
by Chinese residents. Patent rights are territorial in nature, meaning that they only apply inthe jurisdiction of the patent office that grants the right. A patent applicant seeking to protect
an invention in more than one country has to file the patent application in each country ofinterest. We use this to approximate the countries in which the applicant wishes to market
their invention.
The propensity of patent applicants to seek protection beyond their national jurisdiction
differs markedly. For instance, in 2011, residents of China filed fewer than 20,000
applications outside of China, or only 4.54 percent of all the applications by Chinese
residents worldwide (Fink, et al., 2013; Miguélez & Fink, 2013). Chinese patent strategies
are further elaborated in (Kashcheeva, et al., 2014).
Countries where most of the mining innovation is protected are: China (33 percent of totalmining innovation), Japan (20.4 percent), the Russian Federation (13.4 percent) and the U.S.
15 Civil engineering contains the IPC classes broadly related to mining including also oil and gas drilling.

34

(10.7 percent)16. China entered only recently among the top filing countries (Figure 22)
following the boom in its economy after the 80s. After accession to the WTO, the Chinese
economy boomed and patent applications followed a similar pattern.
Figure 22: Top 10 jurisdictions for mining patents by earliest priority year

Source: WIPO Mining Database (technology subset)

In the mining technology subset, 46 percent of first filings have a Chinese origin. Out of
those, 99 percent are filed in China (Figure 23) and only 1.7 percent have multiple family
members, showing that Chinese applicants focus on filing in China. Contrasting that is first
filings originating in the United States, of which 59 percent are filed overseas and 76 percent
have multiple family members.
Combining the two approaches we can highlight whether innovation protected in certain
countries is mostly filed by resident or non-resident entities. Overall the share of resident
applications in mining is more than 59 percent which highlights a global preference forresident filings. But for some countries, resident filings are a large majority. This is the casein China with 90.7 percent and Japan with 89 percent of resident filings, while othercountries, such as the U.S., are below the average with only 52 percent resident filings. The
percentage of resident applications varies quite a lot across countries. While China, Japan,
the Republic of Korea, Germany and the United States of America have more resident filings
than non-resident ones, other countries like Australia, Canada, Chile and Brazil have alarger number of non-resident applications. This is probably due to the presence of big
multinationals, mainly METS firms, which are headquartered somewhere else but wish tomarket their mining-related products in these mining countries. This pattern follows closely
the one of general patent application (WIPO, 2018).

16 We compute these statistics using the jurisdiction in which the patent is filed.

35Figure 23: Origin of application for technology subset: Resident versus non-resident patentfilings

Source: WIPO Mining Database (technology subset)

China substantially increased its percentage of resident patents in the most recent period.
Chile followed the opposite path: its number of resident filings halved. This signals either aslowdown in patenting activity of national enterprises or the entrance of foreign firms on thelocal market. Given that patents are often used as a competitive instrument, it could also
reflect the willingness of foreign firms to block local enterprises from using their technologies
without their consent.

36

6.

Concluding remarks

This paper explored the recent boom in mining innovation. Even if an elusive target toinnovation typical measurements, mining innovation has been booming over the last morethan a decade. Australia, Canada, China, Europe and the United States of America
concentrate the largest share of global innovation measured as mining R&D expenditures,
exploration expenditures or mining technologies in patent data.
We then turned to the technological changes that be happening in the mining innovation
supply chain structure and in the geography of innovation. For this purpose, we provide afresh perspective on how to create a patent dataset for economic analysis by relying on
expert domain knowledge in both the mining industry and patent data. This data includes
the patenting activity of mining firms and the mining related patents not necessarily filed bythese firms. We documented how mining technologies can spur from other stakeholders
than mining related firms and how mining firms can be very active beyond mining innovation.
Our analysis showed how mining innovation spurs along the mining production lifecycle andvalue chain. In particular, recent mining innovation focused in exploration and refining
technologies. However, some subsectors have contributed more to the recent mining
innovation uptick more than others. In particular, there has been a decrease of the fromrefining technologies share in favor of those from exploration and transport technologies.
We interpret these results as a direct consequence of the demand surge of mineral productsin the same period. We also observe an increase of automation innovation in the mining
sector. These trends are not new for the industry, which observed an increase in the 1990s
and early 2000s. Nonetheless, we now observe a remarkable automation uptick.
The distribution of economies contributing to mining technologies does not corresponds withthe typical mining producing ones. Only China and the United States of America lead both inmining output and innovation. Australia, Canada and Norway also offer a relatively balanced
mining output and innovation. Other typical mining economies struggle to be present in theinnovation spotlight. The Russian Federation, Brazil and Chile are probably the best among
these, while the other ones generate very limited innovation outcomes. Indeed, mining
innovation is more likely to spur in functioning innovation systems not necessarily based onmining operation countries. Many developed economies not particularly relevant in mining
production contribute in a great extent to the global mining innovation. Japan, the Republicof Korea and many European economies are the top ones among these.
Despite China’s impressive growth in volume, it did little to the rapid increase in the world’s
mining innovation intensity as it has grown in all technologies at a faster pace. This was not
only the case of China. Traditionally mining producing and specialized economies such as
Chile, South Africa and the Russian Federation have all diminished their mining innovation
specialization. Conversely, Australia, Canada, the United States of America and Brazil haveincreased their mining relative specialization, which also means the contributed more to theglobal mining innovation intensity surge.
Most of the increase in the exploration subsector is coming from the increase in
specialization. Australia, Chile and the Republic of Korea increased their relative
specialization in this subsector and are probably among the largest contributors to the
exploration booming relatively to the other sectors. On mining transport, Chile and Australia
were the only country improving their mining transport specialization. The US, Canada andAustralia, are more specialized in automation compared to lower-middle income and uppermiddle income nations. The selected economies are fairly weak in environment
specialization. Only Chile, the Republic of Korea and the United States of America show apositive RSI for environmental technologies.

37

Companies and other stakeholders are accountable for the mining innovation boom.
Established mining and METS firms created about two thirds of the mining related
technologies in our data. Academic institutions produced the remaining technologies, where
public research organizations (PROs) and universities generated 9 and 6 percent,respectively. Despite the private companies are the largest contributor of mining
technologies, only a small portion of mining and METS firms file for patents.

38

ReferencesAcs, Z. J., Anselin, L. & Varga, A., 2002. “Patents and innovation counts as measures ofregional production of new knowledge.” Research Policy, Volume 31.7, pp. 1069-1085.
Amburle, R. et al., 2019. “Recent trends of innovation and IP use in the mining sector inAustralia.” In: Global Challenges for Innovation in the Mining Industries.
s.l.: Cambridge University Press.
Arundel, A. & Kabla, I., 1998. “What percentage of innovations are patented? Empiricalestimates for European firms.” Research Policy, 27(2), pp. 127-141.
Bartos, P. J., 2007. “Is mining a high-tech industry? Investigations into innovation andproductivity advance.” Resources Policy, 32(4), pp. 149-158.
Blundi, D. et al., 2019. “Technology appropriation and technology transfer in the Brazilian
mining sector”, s.l.: WIPO Economics Research Working Paper No. 53.
Bravo-Ortega, C. & Price Elton, J. J., 2019. “Innovation and intellectual property rights in the
Chilean copper mining sector: the role of the mining, equipment, technology andservices firms”, s.l.: WIPO Economics Research Working Paper No. 54.
Czarnitzki, D. et al., 2015. “Individual Versus Institutional Ownership of UniversityDiscovered Inventions”, Zentrum für Europäische Wirtschaftsforschung (ZEW),
Mannheim: ZEW Discussion Papers, No. 15-007.
Dechezleprêtre, A., Ménière, Y. & Mohnen, M., 2017. “International patent families: fromapplication strategies to statistical indicators.” Scientometrics, 111(2), p. 793–828.
Doherr, T., 2017. “Inventor mobility index: A method to disambiguate inventor careers”,
Zentrum für Europäische Wirtschaftsforschung (ZEW), Mannheim: ZEW Discussion
Papers, No. 17-018.
EPO, 2017. Patent families at the EPO [Online].
Available at:
http://documents.epo.org/projects/babylon/eponet.nsf/0/C9387E5053AA707BC125816A
00508E8D/$File/Patent_Families_at_the_EPO_en.pdf
European Commission, 2016. Raw Materials Scoreboard, s.l.: s.n.
Eurostat, 2018. Science and technology database, Business expenditure on R&D by NACE
Rev. 2 activity, s.l.: s.n.
Fink, C., Khan, M. & Zhou, H., 2013. “Exploring the worldwide patent surge”, s.l.: WIPO
Economics Research Working Paper No. 12.
Francis, E., 2015. The Australian Mining Industry: More than Just Shovels and Being the
Lucky Country, s.l.: IP Australia Economic Research Paper No. 4.
Griliches, Z., 1998. “Patent Statistics as Economic Indicators: A Survey.” In: Z. Griliches,
ed. R&D and Productivity: The Econometric Evidence. s.l.:University of Chicago Press,
pp. 287-343.
INAPI, 2010. Patentamiento en el cluster mineria del cobre: Análisis de presentaciones
realizadas en Chile, s.l.: s.n.
IP Australia, 2015. “A patent analytics study on the Australian Pharmaceutical Industry”,
s.l.: s.n.
Jaffe, A. & Trajtenberg, M., 1999. “International Knowledge Flows: Evidence from Patent
Citations.” Economics of Innovation and New Technology, 8(1-2), pp. 105-136.
Kashcheeva, M., Wunsch-Vincent, S. & Zhou, H., 2014. “International Patenting Strategies
of Chinese Residents: An Analysis of Foreign-Oriented Patent Families”,
s.l.: WIPO Economics Research Working Paper No. 20.
Kreuzer, O. & Etheridge, M. A., 2010. “Risk and Uncertainty in Mineral Exploration:
Implications for Valuing Mineral Exploration Properties.” AIG News.

39

Lerner, J. & Seru, A., 2017. “The Use and Misuse of Patent Data: Issues for Corporate
Finance and Beyond”, s.l.: NBER Working Paper No. 24053.
Lybbert, T. & Zolas, N., 2014. “Getting patents and economic data to speak to each other:
An ‘Algorithmic Links with Probabilities’ approach for joint analyses of patenting andeconomic activity.” Research Policy, 43(3), pp. 530-542.
Man, B., 2014. “Overview of the Intellectual Property Government Open Data”,
s.l.: IP Australia Economic Research Paper No. 2.
Martínez, C., 2011. “Patent families: When do different definitions really matter?”
Scientometrics, 86(1), p. 39–63.
Miguélez, E. & Fink, C., 2013. “Measuring the International Mobility of Inventors: A New
Database”, s.l.: WIPO Economics Research Working Paper No. 8.
OECD, 2019. Research and Development Statistics: Business enterprise R-D expenditure
by industry - ISIC Rev. 4, OECD Science, Technology and R&D Statistics (database):https://doi.org/10.1787/data-00668-en (accessed on 23 March 2019).
Pavitt, K., 1984. “Sectoral patterns of technical change: Towards a taxonomy and a theory.”
Research Policy, 13(6), pp. 343-373.
Raffo, J., 2015. MATCHIT: Stata module to match two datasets based on similar text
patterns, s.l.: s.n.
Raffo, J. & Lhuillery, S., 2009. “How to play the ‘Names Game’: Patent retrieval comparing
different heuristics.” Research Policy, 38(10), pp. 617-1627.
Reichl, C., Schatz, M. & Zsak, G., 2018. World Mining Data.
Vienna: ISBN 978-3-901074-44-8.
Scherer, F., 1984. “Using Linked Patent and R&D Data to Measure Interindustry
Technology Flows.” In: Z. Griliches, ed. R&D, Patents, and Productivity. s.l.:Universityof Chicago Press, pp. 417-464.
Schmoch, U., 2008. Concept of a Technology Classification for Country Comparisons,s.l.: World Intellectual Property Organisation.
Trippe, A. J., 2015. Guidelines for Preparing Patent Landscape Reports, s.l.: WorldIntellectual Property Organization.
UKIPO, 2015. The Patent Guide. Second Edition, Newport, United Kingdom: The
Intellectual Property Office.
Van Looy, B., Vereyen, C. & Schmoch, U., 2015. IPCV8-NACE Rev.2 Update (version 2.0),
s.l.: eurostat.
Wasi, N. & Flaaen, A., 2015. “Record Linkage using STATA: Pre-processing, Linking andReviewing Utilities.” Stata Journal, 15(3), pp. 672-697.
WIPO, 2018. World Intellectual Property Indicators 2018, s.l.: Geneva: World Intellectual
Property Organization.
WIPO, 2019. Global Challenges for Innovation in the Mining Industries. s.l.:Cambridge
University Press.

40

AbbreviationsABN
ANZSIC
CDIP
CIPO
CPC
DOCDB
DNPM
EPO
GDP
INAPI
INPADOC
INPI
IP
IPC
IPGOD
ISIC
METS
NAICS
NETS
PATSTAT
PRO
R&D
RSI
USPTO
WIPO:

Australian Business Number
Australian and New Zealand Standard Industrial Classification
Committee on Development and Intellectual Property (CDIP)
Canadian Intellectual Property Office
Cooperative Patent Classification
EPO master documentation database
Brazilian National Department of Mineral Production
European Patent Office
Gross Domestic Product
National Institute of Industrial Property of Chile
International Patent Documentation
National Institute of Industrial Property of Brazil
Intellectual property
International Patent Classification
Intellectual Property Government Open Data
International Standard Industrial Classification
Mining equipment, technology and services
North American Industry Classification System
National Establishment Time-Series
EPO’s Worldwide Patent Statistical Database
Public research organizations
Research and development
Relative Specialization Index
United States Patent and Trademark OfficeWorld Intellectual Property Organization

41

Appendix A: Technical notes
Patents included in analysis
When the full search results from the technology-based search were extracted, the dataset
included results that were not related to the mining industry, i.e. those which have amin_mining_cat_id that signifies an exclusion. These patents were removed from analysisof the technology data subset by removing cases where mining_top_id=100, and in order toeliminate patents that are related to oil and gas drilling, the cases wheremin_mining_cat_id=6.29 were also removed.
All patents were retained from the firm-based search in order to analyze which patents are
related to the mining industry, per our definition, and which patents are not.
Units of analysis
The main unit of analysis in patent data is the first filing of a given invention. Utility model
data is included.
The date of reference for patent counts is earliest filing date.
The origin of the invention is attributed to the first applicant in the first filing; whenever thisinformation is missing, the origin of invention is assigned by the following steps:
(i)
(ii)
(iii)
(iv)
(v)
(vi)

extract country information from the applicant’s address
extract country information from the applicant’s namemake use of the information from matched corporations (as described further
below);
rely on the most frequent first applicant country of residence within the same
patent family (using the extended patent family definition);rely on the most frequent first inventor’s country of residence within the same
patent family (again, using the extended patent family definition);for some remaining historical records, consider the IP office of first filing as aproxy for origin.

Definitions
Key definitions of patent related terms and concepts can be found in the glossary of theWorld Intellectual Property Indicators 2018 (WIPO, 2018).

42

Appendix B: Search strategy and categorization

Environmental

Blasting

Subsector

IPC/CPC

Fuses

E21

miningE21

miningReclamation of mining areas
Treatment of waste water frommetallurgical processes

F42C
C06B
C06C
C06D
F42B
3/
F42B2003/
F42D
E21B 29/02
E21B 31/16
E21C 41/32
C02F 103/10
C02F2103/10

Treatment of waste water

C02F

E21

Biological treatment of soil

B09C

Soil treatment

B09C

E21

Waste Disposal
Protection against radiation
Environmental
Technologies related to mineralprocessing
Technologies related to metal
processing
Crushing/grinding mineral
Crushing/grinding

B09B
G21F
Y02

E21
E21
E21

mining OR mine OR mineral OR ore
OR coalmining OR mine OR mineral OR ore
mining OR mine OR mineral OR ore
OR coalmining OR mine OR mineral OR ore
mining OR mine
mining OR mine OR mineral OR ore

E21
E21

mineral OR ore
mining OR mine OR coalmineral OR ore

E21

mineral OR ore

Blasting

Processing

Flotation

Separation

Processing

Bio-processing

Metallurgy
Pyrometallurgy
Casting/powder metallurgy
Furnaces
Coating
Electrometallurgy

1/10

Y02P

40/

Y02P

10/

B02C
B02C
B03D
B03D 103/02 to /10
B03D
1/021
B03D2203/04 to /10
B03B
B07C
B01D

E21

E21

ore

B01D 21/ to 43/
B01D2021/ to 2039/
B01D2221/04
B07B
B03C

E21
E21

mineral OR ore OR coal

B04B

E21

B04C
F26B
C12N
C12N

E21
E21

mining OR mine OR mineral OR ore
OR coalmining OR mine OR mineral OR ore
mining OR mine

E21

mining OR mine

E21

mining OR mine OR mineral OR ore
OR coalE21

mining OR mine OR mineral OR ore

E21
E21
E21
E21

mining OR mine OR mineral OR ore
mining OR mine OR mineral OR ore
mining OR mine OR mineral OR ore
mining OR mine OR mineral OR ore

E21mining OR mine OR mineral OR ore

C40B

Metallurgy

Combined with
IPC keyword

Category

C21C
C22C
C22F
F27D
B22
F27B
C23
C21D
C25

1/
9/

Subsector

Category

Combined with
IPC keyword
mining OR mine OR mineral OR ore
E21
OR coal

IPC/CPC

Transport

B61
Rail

B61D
B65G

Rail infrastructure

E01B

E21

B66

E21

mining OR mine OR mineral OR ore
OR coalmining OR mine OR mineral OR ore
OR coalHoisting

B66B
B66B
E04H

Conveying

B65G

E21

mining OR mine OR mineral OR ore
OR coalHauling

B60P
B65B

E21

mining OR mine OR mineral OR ore
OR coalE21

mining OR mine OR mineral OR ore

E21mining OR mine OR mineral OR ore
OR coal

VehiclesInfrastructure
Shipping
Containers

Control

Exploration

Exploration

11/
67/34 to 46

1/10 to 12
15/ to 19/
12/26

B60
B62D
G07C
5/
E21C 33/
E01C
E01F
G08G
B63
B65
B65D
5/28
B65D 88
G05D
1/
G05D 13/
G05D2201/021
G06F

mining OR mine

mineral OR ore

E21mining OR mine

G01V2210/

E21

G01V

E21

mining OR mine OR mineral OR ore
OR coalmining OR mine OR ore

E21mining OR mine OR mineral OR ore

E21mining OR mine OR mineral OR ore

44/

E21B

45/ to 49/

Core extraction
Methods or apparatus fordrilling
Drilling tools

E21B

25/ to 27/

E21B

1/ to 7/E21B
B24

10/ to 12/

E12B
E12B

15/to 23/
28/

E21B
E21B
E21B
E21B
E21B
E21B
E21B
E21B
G01N

31/
36/
37/
43/29
29/
33/
34/
40/ to 43/

Assays

E21

E21

E21B

Drilling - oil & gas

E21

mining OR mine
mining OR mine
mining OR mine OR mineral OR ore
OR coalG01B to G01D
G01H
G01S
G06T
H04B 13/02

Surveying and testing automatic control
Surveying and testing

Drilling

E21
E21

44

Refining

Subsector

Category

Non-ferrous

C21B
C21C
C21C
C22B

Inorganic chemistry

C01D to C01G

E21

mining OR mine OR mineral OR ore

Ground control support

E01F
E02D
F16B

7/04
5/74
13/

E21

mining OR mine OR mineral OR ore

E21D
E02F
F16

15/ to 23/
E21

mining OR mine OR mineral OR ore

E21mining OR mine

E21

mining OR mine

E21

mining OR mine

E21

mining OR mine OR mineral OR ore

E21mining OR mine OR mineral OR ore
OR coalFerrous

Excavation

Safety/rescue

ShaftsTunnels

MiningCombined with
IPC keyword

IPC/CPC

Ventilation

SubseaMining (original)

Extraterrestrial

1/
7/

E21C 25/ to 39/
E21C2035/
A41
A42
A62
B05
F21V 25/12
H04N
7/18
A42B
1/10
E21B 35/
E21F
5/ to 11/
E21F 17/18
C21D
9/44
E21D
1/ to 8/E21D
9/ to 13/
E21F 16/02
F24
F25B
F04D
F24F
E21F
1/
E21F
3/
B63B 35/
B63C 11/
B63B2035/
B63C2011/
E21B
7/12
E21B 15/02
E21C 50/
B27M
3/32
E02D
3/
E02F
5/22
F21
G06Q 50/02
H04M
1/18
H05B
E21C 41/
E21C 45/
E21F 13/ to 17/
F21L 23/
B64G
E21C

51/

45

IPC/CPC

Mining (additional)

G06K to G06Q
G07C
H01
H04
B06
B32
B62
B64
B67
B68
B81
B82
E0
F01
F02
F03
F04B
F04C
F04F
F15
F17
F23Q
F25D
F28D
B08

Mining (E21)
Mining (mining)
Mining (mine)
Mining (Ore)Mining (Ore*)
Mining (Mineral)
Mining (Coal)

Automation

Combined withIPC
keywordCategory

MiningSubsector

Automation

E21

mining OR mine

E21

mining OR mine OR ore

E21mining
mine
ore
ore*
mineral
Coal
G01C
G01S
G05B
G05D
G05G
G06F
G06N
G06T
H04L

E21

mining OR mine OR mineral OR ore
OR coal7/46

Appendix C: Sub-sector and Category definitions

Refining

Processing

Environmental

Blasting

Sub-sector Category

Definition

Fuses

Fuses (relating to mining)

Blasting

Explosive or thermic compositions; detonating or priming devices; fuses;
pyrophoric compositions; generation of gas for blasting or propulsion(chemical part); Blasting cartridges; Blasting methods (all relating to mining)
Cutting or destroying pipes, packers, plugs, or wire lines, located inboreholes or wells by explosives or by thermal or chemical means; Fishingfor or freeing objects in boreholes or wells combined with cutting or
destroying means

Reclamation of mining
areas

Reclamation of surface-mined areas

Treatment of waste
water frommetallurgical processes

Treatment of waste water from quarries or from mining activities

Treatment of waste
water

Treatment of waste water relating to mines/mining

Biological treatment ofsoil

Reclamation of contaminated soil (from mines/mining) microbiologically or byusing enzymes

Soil treatment

Reclamation of contaminated soil (from mines/mining)

Waste Disposal

Disposal of solid waste (from mines/mining)

Protection against
radiation

Protection against x-radiation, gamma radiation, corpuscular radiation or
particle bombardment; treating radioactively contaminated material relating
to mines/mining

Environmental

Technologies for mitigation of climate change relating to mines/mining

Technologies related tomineral processing

Technologies or applications for mitigation or adaptation against climatechange relating to the processing of minerals

Technologies related tometal processing

Technologies or applications for mitigation or adaptation against climatechange related to metal processing

Crushing/grinding
mineralCrushing, pulverizing, or disintegrating minerals/ore; milling and mills

Crushing/grinding

Crushing, pulverizing, or disintegrating in general; milling and mills relating tomines/mining

Flotation

Flotation and differential sedimentation of minerals/ore

Separation

Physical & chemical processes and apparatus for separating and mixing,
including:
Separating minerals/ore using liquids or using pneumatic tables or jigs;
Separation of suspended solid particles from liquids by sedimentation;
Filters; Filtering minerals/ores; Separating mineral particles from liquids;
Separation devices for treating liquids from earth drilling, mining; Separatingminerals from solids by sieving, screening, or sifting or by using gas currents;
other separating by dry methods applicable to bulk material; Magnetic orelectrostatic separation of solid materials from solids or fluids

Processing

Centrifuges; Apparatus using free vortex flow, e.g. cyclones; Drying solidmaterials or objects by removing liquid therefrom

Bio-processing

Microorganisms; enzymes and combinatorial chemistry (for bio-leaching ofminerals)

Ferrous

Metallurgy of iron: Manufacture of iron or steel; Refining of pig-iron; Cast
iron; Treating molten ferrous alloys, e.g. SteelNon-ferrous

Production or refining of metals; pretreatment of raw materials; Obtaining
metal compounds from mixtures, e.g. ores, which are intermediate
compounds in a metallurgical process for obtaining a free metal

Inorganic chemistry

Compounds of alkali metals, rare-earth metals and other metals

47

Metallurgy
Exploration

Metallurgy

Metallurgy of iron: Processing of pig-iron; Alloys; Changing the physicalstructure of non-ferrous metals or non-ferrous alloys

Pyrometallurgy

Details or accessories of furnaces, kilns, ovens, or retorts, in so far as they
are of kinds occurring in more than one kind of furnace

Casting/powder
metallurgy

Casting; powder metallurgy: Foundry moulding; Casting of metals; Making
and working metallic powder; manufacture of articles from metallic powder.

Furnaces

Furnaces, kilns, ovens, or retorts in general; open sintering or like apparatus

Coating

Metallurgy: Coating metallic material

Electrometallurgy

Metallurgy of iron: Modifying the physical structure of ferrous metals;
general devices for heat treatment of ferrous or non-ferrous metals or alloys;
making metal malleable by decarburisation, tempering, or other treatments
Metallurgy: Electrolytic or electrophoretic processes

Exploration

Electric digital data processing, relating to minerals/ore
Measuring length, thickness or similar linear dimensions; measuring angles;
measuring areas; measuring irregularities of surfaces or contours;
Measuring distances, levels or bearings; surveying; navigation; gyroscopic
instruments; photogrammetry or videogrammetry; Measurement of
mechanical vibrations or ultrasonic, sonic or infrasonic waves; Radio
direction-finding; radio navigation; determining distance or velocity by use ofradio waves; Image data processing or generation, in general; Transmission
systems in which the medium consists of the earth or a large mass of water
thereon all relating to mines/mining
Details of seismic processing or analysis relating tominerals/ore/mining/mines
Geophysics; gravitational measurements; detecting masses or objects;
tags relating to ore/mining/mines

Surveying and testing automatic control

Automatic control; Surveying or testing of boreholes and wells

Surveying and testing

Surveying of boreholes and wells; Testing the nature of borehole walls;
Formation testing; Methods or apparatus for obtaining samples of soil or well
fluids, specially adapted to earth drilling or wells

Core extraction

Apparatus for obtaining or removing undisturbed cores, e.g. Core barrels,
core extractors; Containers for collecting or depositing substances inboreholes or wells, e.g. Bailers for collecting mud or sand; Drill bits withmeans for collecting substances, e.g. Valve drill bits

Methods or apparatus
for drilling

Earth or Rock Drilling: Methods or apparatus for drilling; Rotary drilling;
Drives for drilling, used in the borehole; Drives for drilling with combined
rotary and percussive action; Special methods or apparatus for drilling

Drilling tools

Earth or Rock Drilling: Drilling tools; Accessories for drilling tools

Drilling

Earth or Rock Drilling: Well equipment or well maintenance; Drilling rods orpipes; Flexible drill strings; Kellies; Drill collars; Sucker rods; Casings;
Tubings; Handling rods, casings, tubes or the like outside the borehole;
Methods or apparatus for flushing boreholes, e.g. By use of exhaust air frommotor; Apparatus for displacing, setting, locking, releasing or removing tools,
packers or the like in boreholes or wells; Vibration generating arrangements
for boreholes or wells, e.g. For stimulating production; Fishing for or freeing
objects in boreholes or wells; Heating, cooling, or insulating arrangements
for boreholes or wells, e.g. For use in permafrost zones; Methods orapparatus for cleaning boreholes or wells; Obtaining a slurry of minerals
from wells, e.g. By using nozzles
Grinding; polishing (drilling and drill bits)

Drilling - oil & gas

Earth or Rock Drilling: Cutting or destroying pipes, packers, plugs, or wirelines, located in boreholes or wells, e.g. Cutting of damaged pipes, ofwindows; Sealing or packing boreholes or wells; Valve arrangements forboreholes or wells; Tubing catchers, automatically arresting the fall of oil-welltubing; Other equipment or details for drilling; Obtaining fluids from wells

AssaysInvestigating or analyzing minerals/ore by determining their chemical or
physical properties

48

Mining

Ground control support

Ground control support and working-face supports in mines
Devices affording protection against falling rocks; Means for anchoring
structural elements or bulkheads; Caps for supporting mine roofs;
Provisional protective covers for working space in mines; Anchoring-bolts forroof, floor, or shaft-lining protection; Mine roof supports

Excavation

Dredging; soil-shifting (for accessing mine sites)
Mining or quarrying: Cutting; slitting; dislodging; Machines which
completely free the mineral from the seam; Other methods or devices for
dislodging with or without loading; Devices for testing in situ the hardness orother properties of minerals; Mining picks

Safety/rescue

Protective garments relating to mines/mining, such as headwear, gloves,
respirators
Life-saving; fire-fighting relating to mines/mining; Methods or apparatus forpreventing or extinguishing fires for boreholes or wells; Devices preventing
sparking of machines or apparatus in mines; Flameproof or explosion-proof
arrangements
Mine safety devices; Rescue devices; Special adaptations of signaling or
alarm devices for mines; Mine rescue devices or other safety devices, e.g.
Safety chambers or escape ways
Devices for allowing seemingly-dead persons to escape or draw attention;
Breathing apparatus for accidentally buried person
Safety devices structurally associated with lighting devices:
Closed-circuit television systems, i.e. Systems in which the signal is notbroadcast

ShaftsMine shafts; Lining mine shafts; Sinking mine shafts; Raising mine shafts;
Mine shaft equipment, e.g. Timbering within the shaft

Tunnels

Mine tunnels; Galleries; Large underground chambers; Linings therefor;
Drainage of mine tunnels

Ventilation

Heating, cooling, ventilating relating to mines/mining

SubseaVessels or like floating structures adapted for mining purposes; Equipment
for dwelling or working under water; Means for searching for underwater
objects; Equipment or details for drilling specially adapted for underwater
drilling; Obtaining minerals from underwater

Mining (original)

The marks in this category were marks that were originally included in thedefinition of the mining industry/ mining related activities
Methods of mining or quarrying; Open-pit mining; Layouts therefor;
Methods of hydraulic mining; Transport specially adapted to undergroundconditions; Methods or devices for placing filling-up materials in undergroundworkings; Mine drainage; Methods or devices for use in mines or tunnels;
Non-electric hand-lamps for miners
Manufacture or reconditioning of tapered poles, e.g. Mine props; Improving
or preserving soil or rock, e.g. Preserving permafrost soil; Dredging; soilshifting for making embankments; for back-filling; Mine lighting; Data
processing systems or methods, specially adapted mining; Telephone sets
specially adapted for use in mines; Electric heating; electric lighting relating
to mines/mining

Extraterrestrial

Apparatus for, or methods of, winning materials from extraterrestrial sources

Mining (E21)

Earth or rock drilling; Mining (i.e. all patents with an E21 mark)Mining (mining)

All patents with mining in the title or abstract

Mining (mine)All patents with mine in the title or abstract

Mining (Ore)All patents with ore in the title or abstract

Mining (Ore*)All patents with a specific ore in the title or abstract (as listed in Appendix D).

Mining (Mineral)All patents with mineral in the title or abstract

Mining (Coal)

All patents with coal in the title or abstract49

Mining
Transport

Mining (additional)

These additional marks in this category were marks that were identified as
relevant through observing relevant patents based on keyword and firms
searches.
Generating or transmitting mechanical vibrations in general; Cleaning;
prevention of fouling; Layered products relating to mines/mining
Performing operations; transporting in general; Land vehicles for travellingotherwise than on rails; Aviation relating to mines/mining
Microstructural technology; Nanotechnology relating to mines/mining
Construction and Building relating to mines/mining
Machines or engines in general; engine plants in general; steam engines;
Positive-displacement machines for liquids; pumps; Rotary-piston, or
oscillating-piston, positive-displacement machines for liquids; Pumping of
fluid by direct contact of another fluid or by using inertia of fluid to bepumped; Fluid-pressure actuators; hydraulics or pneumatics in generalrelating to mines/mining
Liquid handling; Storing or distributing gases or liquids; Refrigerators; coldrooms; ice-boxes; cooling or freezing apparatus; Heat-exchange apparatus
relating to mines/mining
Recognition of data; presentation of data; record carriers; handling record
carriers; Counting of objects; Computer systems based on specificcomputational models; Data processing systems or methods; Registering orindicating the working of machines relating to mines/mining
Basic electric elements; Electric communication techniques relating tomines/mining

Rail

Railway systems; Locomotives; motor railcars; railway vehicles; Couplings
specially adapted for railway vehicles; Brakes or other retarding apparatus
peculiar to rail vehicles; Shifting or shunting of rail vehicles; Guiding railway
traffic; ensuring the safety of railway traffic
Mine cars

Rail infrastructure

Construction of railways; machines for making railways; Switches;
Crossings

ConveyingTransport or storage devices e.g. conveyors for loading or tipping

Hoisting

Hoisting; lifting; hauling;
Control systems of elevators in general specially adapted for mining hoists;
Lifts in hoistways of mines; Hoistway equipment for mines; Mining-hoist
operation; Winding towers for mines

Hauling

Vehicles adapted for load transportation or to transport, to carry, or tocomprise special loads or objects; Machines, apparatus, methods forpacking/unpacking

VehiclesWheels; Axles; Tyres; Vehicles for use on both rail and road; Air-treating
devices for vehicles; Propulsion of electrically-propelled vehicles; Powersupply lines, or devices along rails, for electrically-propelled vehicles; Motorvehicles; trailers
Checking devices for registering or indicating the working of vehicles
Trucks or other devices for transporting machines for slitting or completely
freeing the mineral from the seam

Infrastructure

Construction of roads; Construction of, or surfaces for, roads; Additional
construction work, such as equipping roads or the construction of platforms,
helicopter landing stages, signs, snow fences, or the like; Traffic control
systems

Containers

Conveying; packing; storing
Rigid or semi-rigid containers of polygonal cross-section, formed by foldingup portions connected to a central panel from all sides to form a container
body, with extensions of sides permanently secured to adjacent sides, withsides permanently secured together by adhesive strips, or with sides held inplace solely by rigidity of material
Large containers

50Automation

Control

Control of position, course, altitude, or attitude of land, water, air, or spacevehicles, e.g. Automatic pilot; Control of linear speed; Control of angularspeed; Control of acceleration or deceleration, e.g. Of a prime mover
Systems for controlling or regulating non-electric variables specifically formining vehicles

Shipping

Ships or other waterborne vessels; related equipment

Automation

Measuring distances, levels or bearings; surveying; navigation; gyroscopic
instruments; photogrammetry or videogrammetry; Radio direction-finding;radio navigation; determining distance or velocity by use of radio waves;locating or presence-detecting by use of the reflection or reradiation of radio
waves; analogous arrangements using other waves; Control or regulating
systems in general; functional elements of such systems; monitoring or
testing arrangements for such systems or elements; Systems for controllingor regulating non-electric variables; Control devices or systems insofar as
characterized by mechanical features only; Electric digital data processing
Computer systems based on specific mathematical models; Image dataprocessing or generation, in general; Transmission of digital information, e.g.
telegraphic communication relating to mines/mining

51

Appendix D: Mining keywords
Search terms use regular expressions. Unless otherwise indicated, the search terms were
word bound. Both regular, accented and Unicode characters were used for words withaccented characters.
Keyword term

searchlanguagedeenmining
es
fr

pt

mine

en
es
fr
pt

de

search term.*bergbau.*bergwerk.*
grubenbetrieb.*tagebau.*
goaf[s]?
goavesminingminer[ao][s]?
minería
mineur[s]?
minière[s]?
mineiro[s]?
mineração
minerador[a]?[s]?
mine[rs]?[s]?
mina[s]?
mine[s]?
mina[s]?
erz
erzen
mineralmineralienenmineral[s]?

esmineral(es)?

frMineralminérauxpt

minera[is|l]

en
es
fr
pt
de

ore[s]?
mena[s]?
minerai[s]?
minériokohle
coalcollieries
collieryhullahouillehulha

mineral

ore

en
coal
es
fr
pt

not

data mining
minería de datos

mineração de dados

mineral wool OR mineral fibre OR mineral fiber
OR mineral oil OR mineral water OR mineral
filleraceite[s]? mineral(es)? OR agua[s]?
mineral(es)? OR lana[s]? mineral(es)? OR
fibra[s]? mineral(es)?
huile[s]? minéral OR eau[x]? minéral OR
laine[s]? minéral OR fibre[s]? minéralóleo[s]? minera[is|l] OR água[s]? minera[is|l]OR lã[s]? minera[is|l] OR fibra[s]? minera[is|l]coal gas OR coal tar OR coal bed gas

alquitran de hullagas de houille52

Keyword term
ore: acanthiteore: argentite
ore: barite
ore: bauxite
ore: berylore: bornite
ore: cassiterite
ore: chalcopyrite
ore: chromite
ore: cinnabar
ore: cobaltite
ore: coltan
ore: dolomite
ore: galena
ore: hematiteore: ilmenite
ore: magnesite
ore: magnetiteore: malachiteore: molybdenite
ore: pentlandite
ore: pyrolusite
ore: scheeliteore: sperrylite
ore: sphalerite
ore: tantalite
ore: uraninite
ore: wolframite

searchlanguagesearch term

nota[ck]ant[h]?it[ae]?
argentit[ae]?
bar[iy]t[ae]?
bauxit[ae]?
ber[iy]l[o]?
bérylbornit[ae]?
cassiterit[ae]?
cassitérite
c[h]?al[ck]op[iy]rit[ae]?
c[h]?romit[ae]?
cinabrecinabrio
cinnabarzinnobercobaltit[ae]?
coltãcoltancoltándolomit[ae]?
galen[ae]h[a]?ematit[ae]?
hämatithématite
ilmenit[ae]?
ilménitemagnesit[ae]?
magnésite
magnetit[ae]?
malachit[ae]?
mol[yi]bdenit[ae]?
molybdänit
molybdénite
pentlandit[ae]?
pirólusita
pyrolusit[ae]?
scheelit[ae]?
sperr[yi]lit[ae]?
esfalerita
sphalerit
sphalérite
tantalit[ae]?
uraninit[ae]?
wolframit[ae]?

53Appendix E: IPC exclusions
Exclusion

IPC

Definition

Defensive ships

B63G

Mine-laying; Mine-sweeping; vehicles with offensive or defensive
arrangements

F41

Weapons

F42B 4/ to99/

Fireworks; Cartridge ammunition; Projectiles or missiles; Shotgun
ammunition; Practice or training ammunition; Arrangements on projectiles or
missiles for stabilizing, steering, range-reducing, range-increasing or fallretarding; Depth charges; Projectiles or missiles; Blasting cartridges

A61

Medical, veterinary or hygiene products

A01J

Manufacture of dairy products; Baking; equipment for making or processing
doughs; doughs for baking; Butchering; meat treatment; processing poultry
or fish; Foods or foodstuffs

Weapons &Ammunition

Pharmaceutical
Foodstuffs

A21 to A23
A01
A24

Tobacco; cigars; cigarettes; Footwear in general; Haberdashery;jewellery; Hand or travelling articles; Brushware; Furniture; domestic
articles or appliances; Sports; games; amusements; Other humannecessities in general; Clothing in general; Headwear in general; Lifesaving; fire-fighting in general; Agriculture; forestry; hunting; Animalhusbandry

Other humannecessities

A41 to A47
A62
A63
A99

Separating;mixing

B01F
B01J

Mixing (dissolving, emulsifying, dispersing); Chemical & physical processes
and apparatus, e.g. catalysis, colloid chemistry

B21
B23
Shaping (metal)
products

B25 to B27
B30
B31

Mechanical metal-working; Machine tools; metal-working not otherwise
provided for; Hand tools; portable power-driven tools; handles for hand
implements; workshop equipment; manipulators; Hand cutting tools;
cutting; severing; Working or preserving wood or similar material; nailing or
stapling machines in general; Presses; Making articles of paper, cardboard
or material worked in a manner analogous to paper

Turning; Boring

B32B

Layered productsWorking cement,
clay, stone

B28

Working cement, clay, or stone

Working plastics

B29

Working of plastics

Printing; writing

B41 to B44

Printing; lining machines; typewriters; stamps; Bookbinding; albums; files;
special printed matter; Writing or drawing implements; bureau accessories;
Decorative arts

Petroleum, gasor cokeindustries

C10

Petroleum, gas or coke industries; technical gases containing carbon
monoxide; fuels; lubricants; peat54

Exclusion

IPC

Definition

C01B
C01C

Chemistry

C03 to C05
C07
C08
C11 to C14
C30
C40
C99

Inorganic chemistry; Non-metallic elements; salts; Glass; mineral or slag
wool; Cements; concrete; artificial stone; ceramics; refractories; Lime,magnesia; Fertilizers; Organic macromolecular compounds; Polymers;
Organic chemistry; Animal or vegetable oils & fats; detergents; candles;
Bioinformatics; Biochemistry; microbiology; enzymology; mutation or
genetic engineering; Sugar industry; Crystal growth; Combinatorialtechnology; Tanning; Skins; hides; pelts; leather

Dyes; Dying

C09
D

Textiles; paper; Dyes; paints; polishes; resins; adhesives

Construction

E01D
E01H
E04

Bridges; Street cleaning; cleaning of permanent ways; Building

F01K

Heating; ranges; ventilating in general; Steam generation; Steam engine
plants; steam accumulators; engine plants not otherwise provided for;engines using special working fluids or cycles; Combustion apparatus;
combustion processes; Furnaces; kilns; ovens; retorts

Lighting;
heating

F22 to F24
F27

Measuring;
testing

G01K

Measuring temperature; measuring quantity of heat; thermally-sensitiveelements not otherwise provided for

Photography

G03G

Electrography; electrophotography; magnetography

Instruments

G1

Instruments

Bioassays

G01N

Electrical

H05K
H03

Printed circuits; casings or constructional details of electric apparatus;
manufacture of assemblages of electrical components; Basic electronic
circuitry

Electrical

H01

Basic electric elements in generalPowergeneration

H02

Generation, conversion, or distribution of electric power

33/

Bioassays

55

Appendix F: Sub-sector assignment
mining_top_id

mining_cat_lvl_1

1

Blasting

mining_cat_id
1.50
1.60
2.05
2.10

2

Environmental

3

Processing

4

Mining5

Transport

2.11
2.15
2.20
2.25
2.50
2.90
102.30102.40112.11
3.15
3.19
3.20
3.30
3.31
3.32
3.42
3.43
3.44
3.50
4.10
4.20
4.40
4.50
4.60
4.70
4.90
5.10
5.15
5.20
5.30
5.35
5.40
5.50
5.60
5.70
5.90

mining_cat_lvl_2
Fuses
Blasting
Reclamation of mining areas
Treatment of waste water from metallurgicalprocesses
Treatment of waste water
Biological treatment of soil
Soil treatment
Waste Disposal
Protection against radiation
Environmental
Technologies related to mineral processing
Technologies related to metal processing
Treatment of waste water
Crushing/grinding mineral
Crushing/grinding
Flotation
Separation
Separation
Separation
Processing
Processing
Processing
Bio-processing
Ground control support
Excavation
Safety/rescue
ShaftsTunnels
Ventilation
SubseaRail
Rail infrastructure
Hoisting
Conveying
Hauling
VehiclesInfrastructure
Containers
Control
Shipping

56

mining_top_id

mining_cat_lvl_1

6

Exploration

9

Mining10

Automation

11

Refining

12

Metallurgy

109

Mining (kw only)

mining_cat_id
6.10
6.12
6.15
6.17
6.21
6.22
6.25
6.29
6.35
9.50
9.60
9.70
9.80
9.90
9.97
9.98
10.00
11.10
11.20
11.30
12.10
12.11
12.12
12.13
12.14
12.15
109.10109.20109.30109.40mining_cat_lvl_2
Exploration
Surveying and testing - automatic control
Surveying and testingCore extraction
Methods or apparatus for drilling
Drilling tools
Drilling
Drilling - oil & gas
AssaysMining (original)
Mining (additional)
Extraterrestrial
Mining (E21)
Mining (additional)
Mining (mining)
Mining (mine)
Automation
FerrousNon-ferrous
Inorganic chemistry
Metallurgy
Pyrometallurgy
Casting/powder metallurgy
Furnaces
Coating
Electrometallurgy
Mining (Ore)Mining (Ore*)
Mining (Mineral)
Mining (Coal)57

Appendix G: Relevant ISIC groups
This table outlines how the ISIC classes were assigned to a mining sector for the firm datasubset. Equivalent assignments were used for corresponding industrial classifications, suchas ANZSIC for Australian firm data. For example, ANZSIC class 0600 Coal Mining iscorresponds to ISIC division 5 Mining of coal and lignite.

METS

C

Class

B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B
B

Group

MiningMiningMiningMiningOil & Gas
Oil & Gas
Oil & Gas
MiningMiningMiningMiningMiningQuarrying
Quarrying
Quarrying
Quarrying
Quarrying
Quarrying
Quarrying
METS
Oil & Gas
support
METS
METS
-

Division

Firm
SectorSection

ISIC Rev. 4

05
051
052

0510
0520

061
062

0610
0620

071
072

0710

06

07

0721
0729
08
081
089

0810
0891
0892
0893
0899

09

Description

Mining and quarrying
Mining of coal and lignite
Mining of hard coal
Mining of lignite
Extraction of crude petroleum and natural gas
Extraction of crude petroleum
Extraction of natural gas
Mining of metal ores
Mining of iron ores
Mining of non-ferrous metal ores
Mining of uranium and thorium ores
Mining of other non-ferrous metal ores
Other mining and quarrying
Quarrying of stone, sand and clay
Mining and quarrying n.e.c.
Mining of chemical and fertilizer minerals
Extraction of peat
Extraction of salt
Other mining and quarrying n.e.c.
Mining support service activities

B

091

0910

Support activities for petroleum and natural gas extraction

B
C
C

099

0990

Support activities for other mining and quarrying
Manufacturing
Manufacture of machinery and equipment n.e.c
Manufacture of general-purpose machinery
Manufacture of lifting and handling equipment
Manufacture of special-purpose machinery
Manufacture of machinery for mining, quarrying andconstruction

28
281

C

2816
282
2824

58

Appendix H: Relative Specialization Index
This table lists the RSI in mining for all countries in the technology data sub-set. The country
is indicated with the 2-digit ISO code. We present the RSI for both periods: 1990–2004 and2005–2015.
RSI (specialization in Mining)
ISO code
AD
AE
AG
AM
AN
AO
AR
AT
AU
AZ
BA
BB
BD
BE
BG
BH
BM
BO
BR
BS
BW
BY
BZ
CA
CD
CH
CL
CN
CO
CR
CS
CU
CY
CZ
DD
DE
DK
DO
DZ
EC
EE
EG
ES
FI
FR
GB
GD
GE

1990-2004
0.482
0.686
0.51
0.625
-0.226
0.312
0.206
0.467
0.244
0.243
0.101
0.376
-0.3850.555-0.122
0.389
0.837
0.272
0.331
-0.082
1.01
0.194
0.045
-0.09
0.322
0.461
-0.2050.163-0.127-0.091-0.434-0.3240.224-0.2420.436
0.107-0.4750.106-0.011-0.1061.439
0.331

1990-2015
0.096
0.43
0.304
0.383
0.631
0.855
-0.221
0.118
0.285
0.401
-0.175-0.2620.447-0.0570.241
0.253-0.3440.643-0.109
0.228
0.332
0.327
-0.3130.349
1.031-0.198
0.89
0.176
0.065
-0.308
0.211
0.497
0.094
0.037
-0.246-0.215-0.166-0.7530.059-0.1010.224-0.025-0.5
0.125-0.086-0.101
1.11
0.223
59

GH
GN
GR
GT
HK
HN
HR
HU
ID
IE
IL
IN
IR
IS
IT
JO
JP
KG
KN
KP
KR
KW
KZ
LB
LI
LT
LU
LV
MA
MC
MD
MH
MK
MN
MO
MR
MT
MU
MX
MY
NA
NE
NG
NI
NL
NO
NZ
OM
PA
PE
PH
PK
PL
PT

0.385
-0.3340.435-0.647-0.083-0.261
0.065-0.263-0.461-0.099-0.092-0.438-0.506-0.382-0.1070.904-0.318
-0.07
1.065
0.786
0.605
-0.4320.837-0.206-0.158-0.409-0.5361.439
0.555-0.159
0.616
-0.04
0.811
0.295
-0.379
0.939
0.574
0.337
0.012
0.732
-0.253
1.218
1.207
0.574
-0.5820.681-0.2750.429
0.241-0.4870.304-0.711-0.494-0.232-0.3730.103-0.366-0.587-0.23-0.12-0.321-0.541-0.848-0.2560.801-0.145-0.164-0.307
0.171
0.913
0.433
0.512
-0.4580.611-0.279-0.4-0.095-0.465
0.467
0.186
0.614
-0.73
0.508
-0.4840.332
0.187-0.227-0.0330.291-0.1950.695-0.0520.808-0.135
1.306
0.845
0.536
-0.459
0.132
0.532
-0.29
60

QA
RO
RS
RU
SA
SB
SC
SE
SG
SI
SK
SL
SM
SN
ST
SU
SY
TD
TH
TJ
TM
TN
TR
TT
UA
UG
US
UY
UZ
VC
VE
VN
VU
YU
ZA
ZR
ZW

0.469
0.012
0.604
0.519
0.36
-0.089-0.464-0.2030.038
0.411-0.262
0.477
-0.17
0.652
0.304
-0.7580.177
0.42-0.608
0.315
0.692
1.071
-0.013-0.807
0.491
0.931
0.699
0.962
-0.667
0.889
1.616
0.392

0.089
0.288
-0.026
0.447
0.73
1.508
0.291
-0.117-0.287-0.381-0.0220.265-0.641
0.271-0.2770.544-0.2280.906-0.2470.128
0.31-0.599-0.586
0.224
0.485
0.633
-0.007-0.654
0.404
1.181
0.877
0.09
0.695
-0.728
0.773
1.508
0.411

61