Data quality has an important role in building confidence in the products produced by an institution. Quality assurance forms an integral part of statistics production at any statistical office. Several factors make international migration statistics unreliable when using traditional or non-traditional methods.
During the censuses, it is a challenge to capture all emigrants, when all members of the households reside abroad, and information regarding irregular migrants is often difficult to collect, etc. Another limitation is related to timeliness: data is collected once in several (about five or ten) years.
The population register can be considered as an adequate data source for collecting migration statistics since it contains various sets of individuals' characteristics. The frequency of its updating and the accuracy of the information recorded are factors critical to the quality of the statistics to be computed. It has to be emphasized that such events as a change of the person's residence within the state, as well as a departure from state to live abroad, has to be declared by the person (physically or via online notification, depending on the country), which is not always done, as updating residency information might be a very complex process (OSCE/ODIHR, 2009). Under certain circumstances, it might be a challenge to capture internal migrants, as well as international ones (e.g. person's movement within the Schengen area, as no checks are carried out at the borders between the Schengen Member States).
Other administrative sources, such as e.g. border control data, can be also used for producing migration statistics but it suggests quantitative rather than qualitative data.
Thus, coverage is one of the main challenges when it comes to the production of migration statistics. MPD can measure migration regardless of the person's statement (i.e. reported place of residence). Big Data can provide alternative solutions and fill some data gaps.
Privacy and ethical aspects. The issues of privacy, surveillance, and fundamental rights are important aspects of mobile positioning. Any study conducted with the use of MPD must ensure the individual's personal privacy, avoid discrimination and respect fundamental rights, as the data may contain sensitive information. The information should not allow identifying an individual(s) on geographical or temporal grounds, that is, it should not be possible to extract individual(s) movements from the MPD. Every cell has a certain geographical coverage area and unique identity code, as in the Cell-ID method. To keep confidentiality, mobile operators can aggregate anonymous geographical data from log files, such as location points or movement vectors, and data users can use this for scientific purposes or planning.