## 1 Introduction  
The New Radio (NR) standard of 5G cellular networks promises to connect a massive number of heterogeneous devices, accommodate high data rates, and support low latency applications [1, 2]. The 5G NR supports a large variety of use cases with diverse requirements and in particular enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and massive Machine-Type Communications (mMTC) [3]. In addition to traditional broadband services, novel applications that can benefit from 5G include logistics and shipping, smart grids, smart factories, agriculture, extended reality, healthcare, mission-critical services, and autonomous driving [4, 5, 6].  
The 5G NR operates over two different frequency ranges. Frequency Range 1 (FR1) includes sub-6 GHz frequency bands, which are also referred to as _low-band_ (up to 2 GHz) and _mid-band_ (up to 6 GHz) [7]. Frequency Range 2 (FR2) includes the millimeter-wave (mm-wave) band, from 24.25 to 52.6 GHz.  
A significant number of commercial 5G networks are currently under deployment in the mid-band, and in particular in the 3.3-3.8 GHz spectrum portion, called Band n78, which offers a good trade-off between coverage and capacity [8; 9; 10; 11; 12]. Therefore, understanding signal propagation characteristics in the mid-band is particularly important especially in the urban scenario where most of the 5G deployments are taking place.  
Various 5G use cases target indoor scenarios, such as smart buildings with different types of sensors, factory automation, object tracking in a factory, remote control of robotic machinery, and automated vehicles in logistic applications, to mention a few [13; 14; 15; 16]. Currently, these scenarios are likely to be addressed via outdoor deployments of 5G Base Stations (BS). This emphasizes the need for understanding propagation characteristics in outdoor-to-indoor scenarios.  
There are a few works performing outdoor-to-indoor measurements to characterize the communication channel at around 3.5 GHz in different scenarios such as urban microcell [17], urban macrocell [18], non-line of sight [19], residential buildings [20], multiple-input-multiple-output (MIMO) in an office building [21], dense urban [22], and university buildings [23; 24].  
A few investigations of 5G channel characterization in the mid-band were also carried out for channel modeling purposes in both outdoor-to-indoor [25; 26; 27; 22] and indoor-to-indoor [28; 29; 30; 4; 31; 32; 33; 34; 35; 36] scenarios. However, none of the above investigations makes use of measurements collected _in the wild_, i.e., on commercially deployed 5G networks. Furthermore, there is currently no available dataset including measurements collected on commercial 5G networks. Additionally, the datasets used in the aforementioned studies are not publicly available.  
This paper fills the above gap by making open-source a dataset of outdoor-to-indoor measurements collected on commercial 5G mid-band systems deployed in an urban scenario. To the best of our knowledge, this is the first work to provide a large-scale dataset of measurements performed over commercially deployed 5G mid-band networks in an outdoor-to-indoor scenario.  
The paper is organized as follows. The experimental setup and data collection methodology are discussed in Section 2. Section 3 describes the collected data, including an explanation of the dataset structure, while Section 4 draws conclusions and identifies future work made possible by the use of the provided dataset.