add OVERVIEW.md

Author: dimitri-yatsenko

OVERVIEW.md

@@ -1,24 +1,20 @@
 # DataJoint Overview
 
-DataJoint is a library for interacting with scientific databases integrating computational dependencies as part of the data model. It is an ideal tool for team projects working on shared data-centric computational workflows.
+DataJoint is a library for interacting with scientific databases that support computational dependencies as part of the data model. 
+DataJoint serves as a principal framework for organizing data and computations in team projects.
 
-## Why use databases in scientific studes?
-
-Many scientists are reluctant to use databases due to their perceived unwieldiness, opting instead to use file repositories for managing their shared data. [Gray, 2005](https://arxiv.org/abs/cs/0502008)
-
-Yet databases provide several key advantages when it comes to sharing structured dynamic data:
+Databases provide several key advantages when it comes to sharing structured dynamic data:
 
 1. **Data structure:** databases communicate and enforce structure reflecting the logic of the scientific study.
 2. **Concurrent access:** databases support transactions to allow multiple agents to read and write the data concurrently.
 3. **Consistency and integrity:** database provide ways to ensure that data operations from multiple parties are combined correctly without loss, misidentification, or mismatches.
 4. **Queries:** Databases simplify and accelerate data queries -- functions on data to obtain precise slices of the data without needing to send the entire dataset for analysis. 
 
-## What does DataJoint bring?
 DataJoint solves several key problems for using databases effectively in scientific projects:
 
 1. **Complete relational data model:** database programming directly from a scientific computing language such as MATLAB and Python without the need for SQL. 
 2. **Data definition language:** to define tables and dependencies in simple and consistent ways.
 3. **Diagramming notation:** to visualize and navigate tables and dependencies.
 4. **Query language:** to create flexible and precise queries with only a few operators.
 5. **Serialization framework:** to store and retrieve numerical arrays and other data structures directly in the database.
-6. **Support for automated distributed computations:** for computational dependencies in the data.
+6. **Support for automated distributed computations:** for computational dependencies in the data.