Digitizing scientific data and data retrieval techniques

TL;DR

This paper discusses the importance of structured data formats and metadata in scientific data management, highlighting recent advancements in standards, protocols, and search technologies that improve data retrieval and accessibility.

Contribution

It reviews recent progress in scientific data management, focusing on standards, protocols, and search technologies that enhance data accessibility and future-proofing.

Findings

Advancements in data standards and protocols improve data archiving.

New search technologies enable faster and more robust data retrieval.

Structured formats like XML ensure long-term data accessibility.

Abstract

Storing data is easy, but finding and using data is not. It is desirable that the data is stored in a structured format, which can be preserved and retrieved in future. Creating Metadata for the data is one way of creating structured data formats. Metadata can provide Multidisciplinary data access and will foster more robust scientific discoveries. In the recent years, there has been significant advancement in the areas of scientific data management and retrieval techniques, particularly in terms of standards and protocols for archiving data and metadata. New search technologies are being implemented around these protocols, which makes searching easy, fast and yet robust. Scientific data is generally rich, not easy to understand, and spread across different places. In order to integrate these pieces together, a data archive and an associated metadata is generated. This data should be stored in a format that can be locatable, retrievable and understandable, more importantly it should be in a form that will continue to be accessible as technology changes, such as XML.