This page lists some Frequently Asked Questions (FAQ) about the IPIS Open Data, and helps you understand the meaning of the different columns and values that occur in the data. If you still have questions, don’t hesitate to contact us!

1. Frequently Asked Questions

1.1. FAQ’s about IPIS Open Data in general

Which data does IPIS publish?

IPIS publishes a selection of its datasets, which originate from our data collection campaigns. These datasets have been reviewed and processed. When collecting new data, we may install a delay of up to 6 months between the publication of a report and the disclosure of the information as Open Data. We take care not to publish data on which we do not feel confident enough, or data that, if disclosed, could potentially endanger people on the ground.

Currently, the main dataset in the IPIS Open Data is about artisanal mining sites in eastern DR Congo. Since 2009, surveyor teams visit mining sites in the field, meet with miners and complete predefined mobile phone questionnaires. The data collected in the field cover a wide range of information including number of workers, techniques and procedures of extraction, tools and protective equipment, production figures, child labour, presence and interference by state and non-state armed actors, roadblocks near and at the mining sites, conflicts and violence, presence and activity of state services, cooperatives and legal status.

Since 2019, we also publish data about artisanal mining sites in northwest Tanzania, Zimbabwe and Central African Republic.

You can find the IPIS reports in which IPIS data are analysed through our publications page.

1.2. FAQ’s about IPIS DRC mining site data

How does IPIS determine where to send teams?

We ask several stakeholders to advise us on the areas and mining sites we will visit. These stakeholders include CAMI, BGR, IOM and USAID. We also use detailed maps from the Royal Museum for Central Africa in Tervuren, Belgium, and maps from the UN, to gather knowledge in the location of artisanal mining sites.
Additionally, we consult with researchers and state agents that know their region very well. They provide us with information such as the number of mines they expect to be in the selected area.

When planning which areas and mines to visit, we take two goals into account:

  • To map as much mining sites as possible in eastern DRC, also in the remote areas.
  • To revisit the most important mining sites, or sites for which we know about recent major changes. Some examples of areas we try to revisit regularly are Kalehe, Shabunda and Misisi in South Kivu.

Additionally, the donor of a mapping project may have specific requests as to which sites to focus on (e.g. only validated sites, production of certain mineral(s) only,…).

How does the security on the ground influence which mines are visited?

We take the security of our surveyors very seriously and constantly evaluate with them which areas are safe enough to be visited. In 2013-2014, we were not able to visit all of the planned mine sites because of security. In 2015, the situation was different and our methodology and field-communication systems were improved, leading to a wider coverage extent.

To what extent is the sample of mines intended be, or likely to be, representative of the population of ASM mines in the Congo?

We strive for our dataset to be as representative as possible of the small scale mining sector in eastern DRC. For the following sub-cases, we would state:

  • Representative for all ASM mines in Congo? – No. Eastern DRC has its specific context with armed actors playing an important part. Other regions in DRC with small scale mining activities that have their own set of characteristics. One example is the small scale diamond mines in the Kasaï provinces.
  • Representative for all mines in a particular province(s), such as North and South Kivu? – Yes. We do believe that our data is relatively complete and representative of these areas. Treating the statistics from our data per type of mineral improves their accuracy.
  • Representative for all mines of particular mineral (e.g. 3Ts or gold) – No. Each region in eastern DRC has its specific context. Only within the principal provinces covered by IPIS, the data is representative per mineral.

2. Open Data Dictionary

To help you understand the columns and values in our Open Data tables, we’re defining them in different open data dictionaries. If you still have questions, don’t hesitate to contact us!

Columns and values in the IPIS DRC mining site data

The following concerns the table cod_mines_curated_all_opendata_p_ipis.

Open data dictionary DRC English 

Open data dictionary DRC French

Columns and values in the IPIS Tanzania mining site data

The following concerns the table tza_mines_curated_all_opendata_p_ipis.

Open data dictionary Tanzania English

Columns and values in the IPIS Zimbabwe mining site data

The following concerns the table zwe_mines_curated_all_opendata_p_ipis.

Open data dictionary Zimbabwe English

Columns and values in the IPIS Central African Republic mining site data

The following concerns the table caf_mines_curated_all_opendata_p_ipis

Open data dictionary CAR French

Open data Dictionary CAR English