Network operators and researchers frequently use Internet measurement
platforms (IMPs), such as RIPE Atlas, RIPE RIS, or RouteViews for, e.g.,
monitoring network performance, detecting routing events, topology discovery,
or route optimization. To interpret the results of their measurements and avoid
pitfalls or wrong generalizations, users must understand a platform's
limitations. To this end, this paper studies an important limitation of IMPs,
the \textit{bias}, which exists due to the non-uniform deployment of the
vantage points. Specifically, we introduce a generic framework to
systematically and comprehensively quantify the multi-dimensional (e.g., across
location, topology, network types, etc.) biases of IMPs. Using the framework
and open datasets, we perform a detailed analysis of biases in IMPs that
confirms well-known (to the domain experts) biases and sheds light on
less-known or unexplored biases. To facilitate IMP users to obtain awareness of
and explore bias in their measurements, as well as further research and
analyses (e.g., methods for mitigating bias), we publicly share our code and
data, and provide online tools (API, Web app, etc.) that calculate and
visualize the bias in measurement setups