Linked data, few words..

2019-03-20 | Dejan Petrovic

Linked data is a concept that aims to make Web content more connected and oriented according to the data. The term is less rigidly defined than the terms of the semantic web, perhaps we can talk about it as a standard. In the main people working on the Linked data are focused on getting the context of any content, assist in the classification of unique guidelines and references, to improve the experience in using tools of the Semantic Web.

The idea of linked data is the integration of many existing components at the data, platforms and applications. Linked Data is engaged in the following areas of application application:

- Display entities: Define who, what, when and where on the Internet. The entities include the meaning and contain context. Simplest, the entity is a line in the list of statements that are organized by type, such as people, places, products, where each unique.

- Annotation entity: It is the finding and recording the entities if they exist in an unstructured content such as Web pages, blogs or comments on the forums. Here we have several tools such as Facebook OpenGraph, HTML5 Microdata, RDFS and hCard microformat.

- Identification and traceability: The entities best contribute to the semantic ecosystem when they are connected with the URI (Uniform Resource Identifier). URI is an ideal point of connection, identification and access to the entity because it is accessible through lots of photos and readable by computer. Point of connection entities, should provide traceability, properties and information about relationships with other entities.

- Find entities: Some enthusiasts are able to all day annotating content to a level where as understood by people and machines. There is no magical tool that would automatically do it completely, but the new technology and tools to search unstructured data improving all the time. The aim of these techniques is to identify the entities, the identifier of the context and type. It is often combined with techniques developed heuristic approach.

(Example: Named entity recognition - NER)

- Translation and approval entities: A variety of ontologies and / or knowledge base of terminology and their properties set the task to a single entity, for example. Local business can appear in multiple lists of entities. How is the entity URI-defined arms, which is unique, it is the tools the task of search and finding the same entity in different data sets.

- Connections: The entities are part of the story. The real power of the Semantic Web lies in connecting different types of entities, such as employees with companies, politicians with donors, brands with stores and so on. Graphs, network entities, ie. how the entities are connected, give the true meaning of the semantic web.

Posted by : Dejan Petrovic