In the era of Big Data and Open Data, a massive and heterogeneous collections of documents (from text to multimedia) are created, managed and stored electronically. to make these documents more usable, a manual and/or automatic indexing process allows to create a representation of documents by a set of metadata, descriptors and social tags. These representations then make it easier to find information in a massive and scalable collection of documents from different sources (social networks, open data, …) to respond to user information needs (user requests). Numerous research studies have been carried out to propose indexing approaches depending on the type of indexed documents. Also, the evolution of indexing Methods, documents representation, electronic content, Big Data and Open Data. This paper presents a state of the art of approaches and methodologies ranging from manual and automatic indexing to algorithmic methods in the era of Big Data and Open Data.