The document defines open data as information that anyone can freely use, reuse, and redistribute, emphasizing requirements for attribution and share-alike conditions. It outlines a 10-point evaluation framework to assess the openness of datasets based on criteria such as availability, accessibility, and licensing. The impact of open data is highlighted in contexts such as governance, transparency, and economic innovation, particularly in developing countries across multiple domains.

1. Open definition
impact
context
Open Definition: A piece of data or content is open if anyone is free to use, reuse, and redistribute it – subject only, at most, to the
requirement to attribute and/or share‐alike.
http://opendefinition.org/#sthash.h042nQvT.dpuf
ODDC Open Data 10‐point Evaluation 8 principles of Open Government Data McKinsey
1 Does the data exist? Data must be complete Data must be accessible
2 Is it available online in digital form? Data must be primary Data must be machine readable
3 Is the data machine readable? Data must be timely Data accessible free or at negligible cost
4 Is the data available in bulk? Data must be accessible Data must be license‐free
5 Is the dataset available free of charge? Data must be machine readable
6 Is the data openly licensed? Access must be non‐discriminatory
7 Is the dataset up‐to‐date? Data formats must be non‐proprietary
8 Is the publication of the dataset sustainable? Data must be license‐free
9 Was it easy to find information on the dataset?
10 Are linked data URIs provided?
Open
data’s
Impact
GOVERNANCE TRANSPARENCY & ACCOUNTABILITY ECONOMIC (INNOVATION/PERFORMANCE)
Context
in which
open data
is used
Developing countries
Multiple domains at national
and supra‐national level
Seven domains at national level
(education, transport, healthcare, etc.)
 Contested
 Unique