The development background and intelligent application advantages of open source data

What is open source data?

Open source data refers to data lawfully collected from publicly available and publicly available sources. In simple terms, open source data is data that anyone can access, modify, reuse and share. Some data may require attribution or compliance with certain agreements before use and distribution.

What is the development background of open source data?

With the development of network technology, big data resources are increasingly abundant, and open source data is the main body of big data, accounting for more than 95% of the entire data volume.

The methods of obtaining open source data are also gradually diversifying. Data sources In addition to some traditional media and their networked products, social media, online communities and intelligent search engines have also become new service media for data acquisition.

During the development of open source data, governments, institutions, and independent organizations have actively opened the data floodgates so that the public can access them freely and easily. While continuously providing data, governments, institutions, organizations, and later enterprises are paying more and more attention to obtaining specific information from open source data, and the open source data market is expanding rapidly.

In April 2022, the US Federal Bureau of Investigation (FBI) spent $27 million to purchase Babel X social media monitoring service, setting a record for the highest amount of open source information purchased by the US government (civilian sector).

According to a research report released by the international market research company "Facts and Factors" in March 2021, by 2027, the global open source information market share based on open source data will increase to 32.049 billion US dollars, with a compound annual growth rate of 23.72%.

What are the advantages of intelligently applying open source data?

Since global data is updated every moment, open source data analysis naturally needs to be continuous. However, traditional manual methods are obviously unable to deal with massive data, and it is difficult to complete data analysis. Therefore, artificial intelligence technology plays an important role in the collection, fusion and governance of open source data. Its advantages are as follows:

1. Scalability:

Artificial intelligence, machine learning, and automation tools can scan and identify large amounts of multi-source heterogeneous data (such as image recognition, speech recognition, and text recognition), reducing the time spent by analysts collecting and processing data so that they can focus on extracting relevant research and judgment information.

2. Accuracy:

Artificial intelligence can achieve comprehensive and consistent processing, realize data content extraction, sentiment analysis, event element extraction, intelligent data screening and deduplication, and maximize the avoidance of errors in analysis.

3. Task effectiveness:

AI-driven open-source data analytics can be used for real-time assessments, alerting you to existing threats and opportunities. At the same time, the intelligent system can support sustainable tracking and evaluation. Especially in identifying internal risks in the organization or supply chain, the support for decision makers can form a regular, accurate, and real-time closed loop, and its timeliness plays an important role in establishing strategic and tactical advantages.