For this reason, in [123], Kiran and Babu explained that the framework for distributed data mining algorithm still needs to aggregate the information from different computer nodes.
By virtue of the server API for synchronization, the Client synchronizes the data, including PDF files, to the server, and users can use multiple Clients from different computers in an integrated manner without manually copying the data.
Before Ascii, computer manufacturers had their own systems for encoding letters and numbers, making it difficult or impossible to exchange data between machines from different computer makers.
The proposed methods rely on many different techniques from different computer science fields.
Together with cloud sourcing facilities (data being stored online on trusted servers), they overcome the need to install specific software while still offering the possibility to access and edit data from different devices (desktop or laptop computer, smartphone, tablet), the underlying operating system as well as the place they are in (work, home, airport, visited lab).
Rather than using Web Technologies to serve web pages for human renders, it uses these web technologies to share information in a way that can be read automatically by computers, enabling data from different sources to be connected and queried [4].
Consequently, there is need for an approach, which allows researchers to access and handle their data on their own computer and import data from different sources and collaborators.
It is also possible to resume work on another computer or to join data from different projects by simply copying the files.
With the server computer in one office of the building, the Compaq continually sent and received data from different offices, floors, and outside the building.
