Linked Open Data: Interesting data sources and AI applications
Linked Open Data is a way to publish metadata in a machine-readable format. Increasingly, it is becoming the basis for digital personal assistants and machine learning algorithms. Its popularity is accelerating rapidly, and it’s gaining ground in the field of AI. Linked Open Files and the GraphDB are some of the most popular datasets available. Using these datasets in AI research and development can benefit both human and machine users. The data is a rich source of knowledge that can be accessed by machine learning and artificial intelligence applications. The open nature of Linked Open Data allows for a rich set of queries to be created, boosting knowledge discovery and data-driven analytics. Among the benefits of using Linked Open Files is that they make it easier to integrate data from multiple sources and make it easier for researchers to integrate a variety of datasets. Hence, it’s important to develop a standard approach to linking Linked Open Files and AI projects.
The Open Data Principles:
As per the Open Data Institute (ODI) whereas openness is defined by Open Knowledge Foundation (OKFN) classify open data when anyone can freely access, use it as pet applications, modify if needed and share for any purpose. OKFN and ODI have created well-known licenses for the same.
Linked Data is a form of structured data that allows for the exploration of a large collection of data. It helps in finding related data and makes it possible to integrate it with other types of data. With a Linked Open File, it’s possible to combine many different types of data. Moreover, this type of structured information is free from duplicate records and is available to all users and organizations. So, how can Linked Open Files help AI applications?
Open linked Data applications:
Currently, a number of European Union projects involve the use of Linked Open Data. Some of these projects are EU Open Data Portal, PlanetData, DaPaaS (Data-and-Platform-as-a-Service), and LinkedOpenData 2. The EU Open-Data Portal provides thousands of data sets. Another project, GeoNames, provides RDF descriptions of more than seven million geographical features worldwide.
In the Digital Humanities, Linked Open Data has emerged as an important source of data for AI. However, these datasets are still in their infancy and there is much work to be done to harness the power of Linked Open-Data. In particular, archival Linked-Data has been explored using machine learning techniques, which are now largely being used by academics in AI. Further, a range of case-studies has been published in the field.
In addition to Linked Open Data, open-data can be used to uncover the power of AI applications. For example, it can be used to identify crime hotspots. These are defined geographic areas where crimes occur. These hotspots can help predict crime types and timing. By comparing crime statistics, the data can be analyzed to identify the best places to commit crimes. It will also improve the efficiency of law enforcement agencies by reducing the costs associated with criminal activity.
Linked Open Data can also be used to create artificial intelligence models. As an example, a Linked Open Data API can be used to search for a given word. A wiki can be an excellent example of a wiki. This technology has the potential to transform the industry. The underlying technology is a critical part of AI, and this language can be utilized to build new systems that benefit the user. The Linked Open Data API is a graphical interface that makes it possible for people to access and analyze vast amounts of data. By using a wiki-based environment, people can interact with the data and create new products. In addition to AI applications, Linked Open Data has also been used to create new tools to support machine learning. The use of a wiki environment allows for a greater variety of applications.
Real-time Linked Dataspaces (RLD): Real-time Linked Data Spaces (RLD) are a Dataspace (RLD) as a data platform for intelligent systems within smart environments.
Linked Open Data supports organizations to contextualize proprietary knowledge. By enabling open data to be linked and interlinked, companies can use the data to develop more intelligent products. Linked Open-Data will also help the organizations leverage their existing proprietary knowledge. It will also allow them to better understand and apply AI to their business. These datasets will help them make better decisions and will help them improve their services. So let us start using linked open datasets.