Platform Guidelines

PATENT ANALYSIS

Patent data are retrieved using the Derwent Innovation suite[1], a comprehensive solution developed by Clarivate Analytics[2] that combines intellectual property, scientific literature, news and business information, integrated with powerful analytics in a robust ICT platform. Derwent Innovation includes the database of more than forty patent offices worldwide and 90% of the world’s top filers.

Elaboration of raw data retrieved from Derwent’s database is performed using RINA Consulting’s proprietary software tools.

Multiannual Trend

Patenting trends are useful to understand the dynamics of a sector, in particular:

  • The number of patents submitted per year gives an indication of the sector’s liveliness;
  • The number of applicants gives an indication of the sector’s level of crowding;
  • The slope of the patenting curve helps identifying the average position of the sector’s technology families along the path of technology evolution.

In the following figure, for example, the curve depicts the actual number of patents filed in the thematic area of Materials for Additive Manufacturing (AM).

Other examples are the following graphs, reporting main filing locations or main assignees/applicants, for a specific patent dataset:

 

Patent ApplicantThe organisation or individual applying for a patent.

Patent Assignee – The organisation to which a patent is assigned ownership; typically the inventor’s employer.

Patent Filing LocationsThe various geographic or legal jurisdictions in which an invidual invention has had patent protection attempted.

Another example of trend graph is the one reporting main IPC codes for a patent dataset, as the one reported in the following figure:

The International Patent Classification (IPC), established by the Strasbourg Agreement 1971, provides for a hierarchical system of language independent symbols for the classification of patents and utility models according to the different areas of technology to which they pertain. A new version of the IPC enters into force each year on January 1 [3].

The classification represents the whole body of knowledge which may be regarded as proper to the field of patents for invention, divided into eight sections. Sections are the highest level of hierarchy of the classification; then there are:

  • Classes
  • Subclasses
  • Groups/Main Groups
  • Subgroups

 

Each section is subdivided into classes. Classes are the second hierarchical level of the classification.

Each class comprises one or more subclasses. Subclasses are the third hierarchical level of the classification.

Each subclass is broken down into subdivisions referred to as “groups,” which are either main groups (i.e., the fourth hierarchical level of the classification) or subgroups (i.e., lower hierarchical levels dependent upon the main group level of the classification).

The IPC – Assignee Bubble Chart

The bubble chart is another analysis tool that can be used to describe the patent scenario emerging from an extrapolated dataset. In the bubble chart are reported main IPC codes; the size of each bubble representing the number of patents that are classified with that specific IPC code; position along y-axis (height on the graph) representing the number of different assignees (or applicants) that used the specific IPC code in their patents. Position of bubbles along x-axis is a function of the number of patent applications that have been submitted in the last 5 years of the considered time interval (for example 2012-2017 for a dataset retrieving data from 2000 to 2017). This way, position of bubbles on the graph allows us to define, schematically, four different areas that can be characterized by more or less competitiveness (according to the number of different applicants per IPC code; i.e. the height on the graph), more or less innovativeness in the investigated technology (according to the percentage of patent applications submitted in the last years); or even if a technology domain (as defined by IPC codes) can be considered “mature” or investigated only for a short period of time.

Bubble Graph – Four areas schematic division, according to number of investor and innovation degree of a technology

Most interesting areas on the graph are those positioned in the right side; precisely, in the lower part, innovation has a little number of investors (alias potential competitors when deciding to invest in that specific technology area), while in the upper right zone , even if technology is quite recent, there are many investors (probable presence of a technological breakthrough).

 

ThemeScape Map

The Themescape map is draft utilizing the proprietary Themescape tool of the Derwent Innovation suite. A content map is a visual representation of a collection of documents organized by thematic content. This helps analyze large data sets. Themescape performs a semantic analysis on the titles and abstract of papers and groups papers on the basis of top recurrent words.

Content maps group records with common conceptual terms (topics) together. Peaks represent a concentration of documents about a specific topic and show the relative relationship of one record to another. This helps you perform “at a glance” assessments of large data sets.Each peak has a dark black label that identifies the key terms in that area. The distance between peaks shows the relationship between records in those areas. Peaks that are close together have similar content, represented by a light gray label.

As you move away from the peaks, lines represent changes in relative document density. These are known as contour lines. Dots on the map represent individual records.

In the following slideshow are reported, for the field of Products made by Additive Manufacturing:

  1. The map of recurrent topics automatically generated by the Themescape tool, on the basis of a semantic analysis of title and abstracts of papers;
  2. The map of recurrent topics reporting the positioning of the Top 5 players, giving indication on the main topic of patenting activity;
  3. The analysis of the map, highlighting the most recurrent topics of research in the field of exploration selected by the present search,  according to the punctual analysis of papers included in each cluster of the map.

Patent Cooperation Networks

Tracing co-application in patents allows identifying cooperation networks among companies and/or technology providers. This provides important insights on the positioning of companies on the market and on the establishment of relationships with other stakeholders.

In the examples below, an analysis is reported regarding the co-application scheme between Stratasys Ltd, Object Geometries Ltd and Object Ltd (two different brands used by Stratasys) and BG Negev Technologies & Applications Ltd. a company that helps the university and its faculty translates their inventions and academic achievements into commercially valuable products by facilitating technology transfer to existing companies or by creating new companies established around these inventions.

The size of bubbles indicates the number of occurrences of an entity.

Following figure reports a co-application map based on a set of data analyzed regarding patenting activity of General Electric with the indication of main IPC4 categories.

Squares indicate entities, while triangles indicate IPC4 classes. Size of the icons depends on the number of occurrences.

This view enables highlighting common fields of development of different applicants, depicted as links through the definition of the IPC codes. For example, we can see that there is a patent collaboration between General Electric and BAker Huges around a specific technological domain, as defined by the B23P code, described in the following table.

B23P OTHER WORKING OF METAL; COMBINED OPERATIONS; UNIVERSAL MACHINE TOOLS

 

Detailed analysis of relevant patents

The most relevant patents are analyzed in detail. For each of them a fact sheet is provided, featuring the following information:

  • Title
  • Title DWPI: Title-DWPI is a concise, descriptive, English-language title edited by Clarivate Analytics  to highlight the content and novelty of the invention
  • Publication Number (Kind Code)
  • Inventor(s)
  • Publication Date
  • Current IPC
  • Abstract DWPI: The enhanced abstract prepared by the DWPI editorial team of Clarivate Analytics. Abstract-DWPI can contain one or more of the following sections: Novelty, Detailed Description, Use, Advantage, Drawing Description.

The Fact-sheet can be visualized by clicking on the summary table, as the one reported here below, as example.

Assignee/Applicant HEWLETT PACKARD DEVELOPMENT CO
Publication number Publication date Priority date IPC Current
US10052825B2 21/08/2018 2013-05-13 | 2014-05-09 B29C006700 | B29C003516 | B29C0064153 | B29C006420 | B29C0064386 | B29K010500 | B33Y003000
Title Three-dimensional printer with cooled protective sheet separator
Abstract The three-dimensional printer has a print mechanism (100) with a separator (124) located before a recoater in a print direction (108). The separator is arranged to separate the protective cover from uppermost layer of deposited material to provide access for recoater to spread the layer of flowable green material on to uppermost layer of material on a material bed (102). The separator has a cooling surface (152) in thermal communication with uppermost layer of deposited material. The cooling surface is at a lower temperature than the temperature of temperature regulating element (146).

 

LITERATURE ANALYSIS

Massive literature data are retrieved using Derwent Innovation[1] suite, permitting to search scientific papers from the Web of Science database.

Web of Science[4] includes over 20,000 peer-reviewed, high-quality scholarly journals published worldwide (including Open Access journals); over 190,000 conference proceedings; and over 90,000 editorially selected books. It gives access to multiple databases that reference cross-disciplinary research, which allows for in-depth exploration of specialized sub-fields within an academic or scientific discipline.

Single articles of interest can be downloaded from free or paid sources.

Multiannual Trend

Literature trends are useful to highlight the interest in a technology family and/or the level of involvement of a company/university/research centre.

A sample search is reported below, concerning papers published between 2008 and 2018 dealing with Materials for Additive Manufacturing (AM). The total number of published papers for 2018 is still partial.

Authorship and Affiliation

The affiliation of authors publishing a paper, corresponds to the institution where the research was conducted, representing in fact the institution funding the research.

The analysis of most recurrent Organisations permits to select the research centres, universities or industrial players most active in a specific research field.

An example of most active organizations in the field of Materials for Additive Manufacturing (AM) is reported in the following Figure.

From the analysis of Organization, usually led by Research Centres and Universities, it is possible to select also Industrial players supporting research papers publication.

ThemeScape Map

As for the Patent analysis, a map of most recurrent terms, can be created through the ThemeScape tool of the Derwent Innovation suite.

ThemeScape is a data analysis tool that creates content maps from Derwent Innovation patent data, enhanced patent data from DWPI, and scientific literature content. A content map is a visual representation of a collection of documents organized by thematic content. This helps analyze large data sets.

The map of recurrent topics automatically generated by the Themescape tool, on the basis of a semantic analysis of title and abstracts of papers selected for the domain of Materials for Additive Manufacturing (AM) is reported here below as an example.

Papers co-affiliation networks

Similarly to co-application in patents, tracing co-affiliation in papers allows identifying cooperation networks among universities, research centres, industrial companies and start-ups. This provides important insights on the collaborations active in a specific research field and on the establishment of relationships between different stakeholders.

In the example below the collaborations of the University of Shieffield in the field of Materials for AM are reported as example.

The size of bubbles indicates the number of occurrences of an entity.

Detailed analysis of relevant papers

Papers of interest are analysed in detail. A factsheet is reported for each of them, featuring the following items:

  • Title;
  • Abstract (original);
  • Authors;
  • Organizations;
  • Publication year;
  • Source;

The Fact-sheet can be visualized by clicking on the summary table, as the one reported here below, as example.

Title Fatigue properties and material characteristics of additively manufactured AlSiW10Mg-Effect of the contour parameter on the microstructure, density, residual stress, roughness and mechanical properties
Publication date Organisation Authors
2018 European Space Agency | RUAG Schweiz AG | EOS GmbH Electro Opt Syst Beevers, E | Brandao, AD | Gumpinger, J | Gschweitl, M | Seyfert, C | Hofbauer, P | Rohr, T | Ghidini, T

 


[1] https://www.derwentinnovation.com

[2] https://clarivate.com/

[3] http://www.wipo.int/classifications/ipc/en/preface.html

[4] https://clarivate.libguides.com/webofscienceplatform/woscc

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