What Is Patent Data?

If you want to understand the patent landscape outside of your industry, using data analytics is the way to go. If your business produces products or services that are similar to yours, other industries may be looking to license your technology to save R&D costs. Patent data also allows you to identify potential acquisition targets. By combining similar businesses, you can create greater synergies and growth opportunities. To learn more, read on! Here are some common attributes of patent data.

Common attributes of patent data

Patent data are available publicly, and are useful for many reasons. Inventors use them to gauge their market needs, development teams use them to find potential partners, managers use them for market research, and policy makers use them to propose improvements. These files have already undergone many reviewers before being included in patent databases. As such, they often have little need for quality control. However, there are a few common attributes of patent data that make them particularly valuable.

Several common attributes of patent data include inventor, publication number, invention title, description, abstract, and more. Many databases also record inventor sex, which can help gauge gender parity in inventions. Despite the numerous benefits of patent data analytics, there are some challenges to this type of data. Here are some common attributes that must be addressed to ensure accurate results. To avoid problems associated with incomplete data, choose a patent data vendor that offers sample datasets.

Publicly available patent documents are the primary source of patent data. These documents contain detailed information on products and their current state. This information is up-to-date and has a clear legal status. Patent literature collections include official bulletins and bibliographic collections, as well as articles that describe particular problems. Past judicial decisions can also be included. Although it is not possible to patent an existing product, a new use for an existing product can be patented.

Patent data contain user privacy and key technological innovation information. If data is leaked, it will be useless for relevant parties, including applicants, patent reviewers, and reexaminers. Consequently, these attributes are highly valuable and should be protected against leakage. A new generation of patent review and retrieval systems and big data processing techniques have been developed to protect the sensitive information contained in patent data. These new techniques are being used in various industries to help protect patent data.

Sources of patent data

The sources of patent data can be divided into two categories: public disclosure from government and commercial data analysis firms. Public disclosure includes data that has undergone limited processing and offers limited search functions, while commercial data firms offer extensive organization and more comprehensive information. However, these sources have many limitations, which can lead to flawed analyses. The following sections will review some of the most common sources of patent data and their limitations. You can also find links to a comprehensive list of all patent data sources.

iEdison: This database includes patents awarded through the NIGMS SBIR/STTR program. It includes patents reported in neither database, as well as those that are reported officially through the iEdison database. Of these, 49 percent of the patents have a grant citation in the Government Interests section. For both of these databases, underreporting is a common problem.

Patents View: This dataset contains millions of patent records. It is organized by countries, and includes patents that were issued in the US, Canada, and Europe. Patents View Data enables researchers to compare inventors’ IP portfolios and identify their trends. Patents View data also offers interesting data visualizations. These are just a few of the sources of patent data available online. With these sources, you can build a database that suits your research needs.

Biological data: Patent documents include samples that were originally isolated from named places. These may also be taken from a wider geographical area. Rarely, patent documents also include georeferenced coordinates. However, it is possible to obtain material that originates from unspecified places through third-party sources, such as DNA sequence databases, proteins, and habitats. It is vital to remember that patent documents do not claim to represent the entire world, so references may not be 100% accurate.

Genetic material: While it is possible to obtain genetic material from Areas Beyond National Jurisdiction, it is difficult to trace the source of the specimen. Consequently, specimens obtained from areas that have high biodiversity are likely to have been obtained through third-party sources. Biological data: Biological patents are often published in peer-reviewed journals, but this information is not always available. WIPO is also considering a proposal to make it mandatory for patents to disclose the source of genetic material.

Methods of assessing quality of patent data

Currently, there are several methods of assessing the quality of patent data. One approach relies on evaluating patent databases using metrics that measure specific technical fields. These metrics include the number of patent families with either a PCT application or a title in one of the IP5 offices. In addition to the metrics themselves, the database may also include other information, such as citations or geographic coverage. The method also allows for the evaluation of the overall quality of the data, which will allow researchers to determine which patent databases are the best for their purposes.

Another way to assess patent data is to use the ISR index, which shows the patent quality of China to be below the average of other high-income nations. The decline in the ISR index is largely related to the decline in PCT citations for Chinese patents. Meanwhile, citations to the other countries in the comparison group are generally stable. USA, Germany, Korea, and Japan have the highest average value for ISR, while China follows with 32.1%.

Quality assessment of patent data should be based on standardized standards that can be applied across industries and organizations worldwide. For instance, IPQ and HPQ can be estimated using an automated system that links patents to products. Both of these measures are critical to the commercialization of an invention and can help patent professionals determine the quality of the patents they collect. Further, IPQ and HPQ scores are required to make an accurate assessment of the quality of patent data.

In the US, the USPTO measures the quality of its patent data using three major types of metrics: product indicators, process indicators, and perception indicators. The USPTO focuses more on customer satisfaction, monitoring the timeliness of patent grant procedures and customer service. The EPO, however, has a much more sophisticated system that includes metrics for these factors. The method adopted by USPTO is also suitable for assessing patent data.

Criteria for selecting a patent database

When you’re looking for a patent database, make sure you’re choosing one that covers every jurisdiction. Patents are a type of statutory negative right that excludes others from making, selling, or using your invention. Patents are only granted to new or innovative inventions that are not previously patented. Because of this, it’s essential to research the state of the art before filing for a patent. Patent databases provide this information in a user-friendly format.

The databases are particularly useful for patent agents, who can quickly find relevant documents relating to their field. Patent databases also contain documents pertaining to specific types of patent application, which makes it easier for the agents to search for relevant patent documents. In addition, a patent database can help agents track down relevant documents and avoid conflicts of interest. In other words, it’s crucial to find an agent who is not affiliated with competitors.