| Overview - The Need Description | | | | spite of the competencies of the team carrying |
| In today's global environment, a highly successful | | | | out the data extraction and the seamless |
| innovation and technological market leader will | | | | processes in place, the search results are bound |
| have the following attributes: | | | | to be prone to contain spurious records. Hence, it |
| 1. A strong basic R&D investment; | | | | is one of the main objectives of this layer to |
| 2. A large body of skilled scientists and engineers; | | | | cleanse the data and make it free from spurious |
| 3. A flexible and skilled work force; | | | | records. The records normalization methodology |
| 4. Reliable utilities and other infrastructure; | | | | followed here typically involves consolidation of |
| 5. Competitive investor and tax environment; and | | | | company names i.e patent assignee names, |
| last but not the least., | | | | categorization of technology etc. For ensuring |
| 6. Information on the patent landscape. The | | | | error-free normalization, the patent databases |
| importance of the information on patent | | | | again form the source to obtain the corporate |
| landscape is of high relevance to this whitepaper. | | | | tree information. Many a times, it is the patent |
| Business Challenges | | | | landscaping team's competency that determines |
| - 100% unambiguous patent landscape information | | | | the technology classification of patents. Hence it is |
| for effective decision making | | | | imperative that a cross functional team include a |
| - Competitive and integrated patent portfolio with | | | | variety of subject matter experts to provide a |
| far reaching strategic goals | | | | solution at crunch times. |
| - Organization wide collaborative platform for brain | | | | Layer Three - Data Integration, Patent Valuation |
| storming ideas | | | | Data integration is nothing but the collation of multi |
| - Monitor and track the competition from potential | | | | source, multi platform information into a |
| patent infringements cost effectively | | | | recognizable format. This layer also is quite |
| The solution sought by the R&D community | | | | responsible for the elucidation of the taxonomy |
| from enterprises to tackle the highlighted business | | | | into a mind map that is deemed useful by |
| challenges is 'beyond information technology and | | | | enterprises for organization of patents etc. The |
| intellectual property information'. | | | | specific tools to draw the mind map prove handy. |
| Four Layers - The nexus with Intellectual Property | | | | For Eg. Mindpro Manager. Further, an interactive |
| (patents) and Information Technology | | | | mind map that is responsive to mouse clicks |
| The following four layered approach for capturing | | | | serve a great deal in the data integration. Data |
| patent information will present itself to be unique | | | | integration is also about the extrapolation of |
| in elaborating the 'Beyond Information Technology | | | | missing information on the results obtained from |
| and Beyond Intellectual Property' strategy. | | | | the previous layers. For eg., its not always that |
| The proposed 4 layered framework is expected | | | | the patent assignee information is presented on |
| to be a value added solution that marks one of | | | | the patent. Hence it is mandatory that the team |
| the best approaches. This will also deliver the | | | | rely on the non patent literature for this purpose. |
| much needed focus to research strategy. | | | | However, in realtime situations, even the use of |
| Beyond Information Technology | | | | non patent literature does not serve the |
| The fundamental problem addressed by the | | | | requirement, so an in depth primary research is to |
| products of information technology i.e the | | | | be conducted in a comprehensive manner. |
| software tools belonging to the patent analysis | | | | Patent Valuation through primary research |
| genre does not usually justify the purpose i.e | | | | Primary research capabilities that enables data |
| comprehensive patent analysis. Interactive Web | | | | gathering from patent holders, which in turn helps |
| page disseminating patent information that is | | | | understand if the patent exists as a prototype |
| more readily reproducible and accessible, than | | | | with demonstrable results at lab stage for non-life |
| traditional forms of scholarly & pedagogical | | | | science patents. For life-sciences, understanding |
| communication is the need of the hour. The | | | | the in-vivo models used for tests and results |
| patent information captured on the interactive | | | | there-of. Further, understanding of toxicology data |
| webpage usually involves a cross functional team | | | | in life-sciences to interpret and ensure the multiple |
| to work in tandem. The following sections of this | | | | use of a specific patent proves beneficial. The |
| article would evolve a deep understanding on the | | | | primary research data collected in this phase |
| four layered approach required for capturing the | | | | simply stands incomparable with any of the |
| patent information. The approach mentioned here | | | | secondary research data made available from the |
| would throw light on changing facet of the | | | | varied data sources. Hence, the approach to |
| researcher's requirement to include the patent | | | | conduct primary research should be well |
| information while determining the research focus. | | | | formulated with adequate hypothesis drawn on |
| Beyond Intellectual Property | | | | need basis. |
| During yester years, file sharing networks | | | | Layer Four - Data Presentation |
| concerning patent data or the so called patent | | | | Data presentation layer is formulated with the |
| databases have grown into what is today the | | | | help of the wiki. Wiki is an excellent collaboration |
| largest, most diverse and most accessible patent | | | | tool and can be used for sharing information within |
| archive in history. Even though the availability of | | | | distributed teams. In addition to wikis, a careful |
| inexpensive internet bandwidth and storage space | | | | assessment from the enterprises' requirements |
| still divides the global north from the global south, | | | | revealed the need for a dashboard. The |
| one of the most far-reaching results of file sharing | | | | dashboard is a Web 2.0 solution that works inside |
| is that there is now access to information | | | | the web browser. Categorization of the patents |
| everywhere. Of particular interest is the question | | | | shown on the dashboard is done based on the |
| of the archive: In a time where file-sharing | | | | taxonomy arrived in the initial layers. The |
| networks constitute the largest repository of | | | | dashboard also houses information on patent |
| patent data that has ever existed, the focus | | | | distribution by company and timeline; one can click |
| shifts from individual users with interests in | | | | on the patents to read the title/abstract/claim |
| particular patent files to organized groups and | | | | information. The patent documents in pdf formats |
| institutions and their desire to organize, keep | | | | can be tagged, rated and filtered for future use. |
| available, backup and make accessible this patent | | | | Dashboard is a simple, yet powerful tool for |
| data. Today's approach demands that enterprises | | | | collaboration and is used by dozens of the world's |
| with a research focus deal less and less with | | | | largest companies for sharing and managing large |
| "content providers" (that dump information onto | | | | quantities of patents, products and scientific |
| consumers) but more and more with "context | | | | literature. |
| providers" (that infuse information into social | | | | Benefits / Returns expected |
| networks of production). | | | | The four layered approach mentioned in this |
| Layer One - Data Extraction | | | | whitepaper has been deployed in numerous tier I |
| The myriad amount of patent information made | | | | organizations belonging to a wide industry choice. |
| available from the various patent databases | | | | However, the following benefits are inevitable in |
| around the world is a challenge to comprehend | | | | due course for any organization (large or small) |
| and extract. The concept of patent searching in | | | | incorporating the best practices mentioned. |
| these databases has evolved into an explicit genre | | | | 1. Save hundreds of hours per research project |
| in science. Patent searching is one of the ways of | | | | adding up to thousands of saved hours - worth |
| extracting data pertinent to a specific knowledge | | | | several hundred thousand dollars |
| domain. The other information reservoirs could be | | | | 2. Help create new product strategies that can |
| attributed to the whitepapers, presentations, | | | | result in multi-billion dollar new product |
| domestic & international space journals and | | | | opportunities |
| finally the third party websites. Patent searching | | | | 3. Save litigation costs (several million dollars per |
| science for the purpose of patent landscaping | | | | lawsuit) from potential patent infringement |
| firstly begins with the preparation of a background | | | | lawsuits |
| study to form a search concept table. This study | | | | White space analysis |
| involves the detailed information search amongst | | | | Apart from the above benefits derived, the |
| the patent and non patent literature available from | | | | identification of white spaces proves to be the |
| the sources cited previously. A search concept | | | | much needed competitive edge on a seamless |
| table serves as a platform to organize & | | | | patent analysis exercise. White space analysis |
| streamline the search operation made on the | | | | involves the break down of patent classification |
| various relevant patent databases for any topic. | | | | into smaller segments with exactly 7 to 15 |
| This method of patent searching serves as an | | | | patents. This allows the research to be focused |
| index to parse through the various search | | | | on a specific area that is deemed cash rich for |
| concepts used along with the keywords in the | | | | future product development. The white space |
| form of a search string. Also, data extraction | | | | analysis helps to spot the opportunities from the |
| layer is to include the preparation of search | | | | crowded areas of patenting. Marking a cross |
| strategy. For Example: The search strategy table | | | | against a specific ingredient indicates its usage. |
| is concerned with the area of searching and that | | | | Finally, the white spaces in the table show |
| this table mainly consists of the number of hits | | | | opportunities for a company to venture out and |
| for each search query executed, issue/publication | | | | get patents. |
| date against each search query executed etc. | | | | Conclusion |
| The attempt to execute this layer i.e the | | | | Though the conventional IT has been facilitating |
| extraction of data must be done with utmost | | | | the emerging needs of R&D efforts inside an |
| care. Otherwise, the entire objective to seek the | | | | enterprise, the concept of making use of the |
| patent landscape and hence obtain focus to the | | | | layered approach support to the researchers |
| R&D is vulnerable to get derailed as the | | | | remain un-touched. Enterprises seeking such a |
| other three layers heavily rely on this very first | | | | service from the global knowledge service leaders |
| layer for their effectiveness. | | | | tend to garner greater return on investment for |
| Layer Two - Data Analysis & Data Cleansing | | | | the funds allocated from the Enterprise R&D |
| The approaches derived for this layer is based on | | | | budget. |
| the outcome from the data extraction layer. In | | | | |