How can the data produced by scientific analyses of materials be made truly comparable, reusable, and accessible, despite the diversity of formats, instruments, and investigation methods?
Can we imagine a shared environment capable of collecting and coherently interpreting information obtained through different techniques, making it easier to consult and compare?
ADE (Automatic Detector Element) was conceived as a first step in this direction.
The project addresses one of the main challenges in archaeometric analyses: the strong heterogeneity of spectroscopic data, which varies according to instruments, acquisition parameters, and environmental conditions. Even minor variations can shift the position or intensity of peaks in spectra, leading to recognition errors and making comparisons between studies or laboratories difficult.
Developed through the integration of several PhD projects, ADE is a web application designed as a practical and transparent tool for managing, processing, and interpreting spectroscopic data. Its aim is to harmonise and calibrate data collected using different instruments, overcoming the fragmentation of formats and the absence of shared protocols that have so far hindered the creation of interoperable databases.
In its first phase, the project focuses on XRF (X-Ray Fluorescence) analysis applied to ceramic materials, using portable instruments such as the Vanta C (Olympus), Elio (Bruker), and Tracer (Bruker). The workflow is organised into several stages aimed at obtaining qualitative information from raw data without relying on proprietary software, and subsequently defining quantitative results through empirical calibration:
• collection and standardisation of raw data (spectra and CSV files) along with the associated instrumental and environmental parameters;
• construction of a reference catalogue based on spectra and certified ceramic standards;
• development of an automatic calibration system to correct deviations caused by different instruments or settings;
• testing of a model for identifying and correcting errors in elemental detections, through thresholds and control conditions.
This phase represents a feasibility study intended to test the robustness and reliability of the method. Thanks to its modular architecture, the system can be expanded to include other spectroscopic techniques, with the long-term goal of creating an interoperable and scalable environment for the management of analytical data on material heritage.

From a technical perspective, ADE is a single-page web application developed in Python, using the Dash framework and the Plotly library. The platform is organized into three functional layers:
• an intuitive user interface for data upload and visualization;
• an event-driven system ensuring synchronization between client and server;
• a data engine dedicated to parsing and automatic normalization of CSV, TXT, and Beamspectra files.
Pre-processing procedures, implemented with NumPy and SciPy, include noise reduction (smoothing), automatic peak detection, and comparison with the standard emission lines of the Lawrence Berkeley National Laboratory, with interactive real-time graphical output.
An automatic reporting module generates TXT, CSV, DOCX, PDF, and ZIP files, while a dedicated Beamspectra module enables the calculation of slope, offset, and mean energy values, ensuring compatibility across instruments and formats.
Looking ahead, ADE acts as an operational bridge between laboratory practice and digital knowledge, designed to connect analytical data with the knowledge graphs of archaeological and archaeometric research, beginning with the SHARED project (Semantic-based Heterogeneous Archive for Reusable Exchangeable Data in Archaeology and Archaeometry).
Based on CIDOC CRM standards and aligned with FAIR principles (Findable, Accessible, Interoperable, Reusable), ADE aims to make analytical workflows traceable, comparable, and reusable, contributing to the development of an open, semantically rich, and interoperable data ecosystem for cultural heritage research.
Project coordinated by:
Lorena Bravi
Martina Naso
Massimiliano Puntin
lorena.bravi@uniroma1.com
martina.naso@uniroma1.com
massimiliano.puntin@uniroma1.com