Musical Instruments in Ancient Mesopotamia (MIAM) A Semantic Media Wiki Database and Lexicon

This is a presentation of a research project which aims to collect, classify and interpret musical instruments, their terminology, iconography and contexts, based on texts, images and original finds. The outcome is presented in an online database and lexicon based on Semantic MediaWiki technology.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-03
DOI
https://doi.org/10.5281/zenodo.15837712
Primary Topic
Ancient Near East History
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Musical Instruments in Ancient Mesopotamia (MIAM) A Semantic Media Wiki Database and Lexicon

Dahlia Shehata, Tomash Shtohryn, Benedetta Bellucci
Zenodo (CERN European Organization for Nuclear Research)
Ancient Near East History
article

Musical Instruments in Ancient Mesopotamia (MIAM) A Semantic Media Wiki Database and Lexicon

Dahlia Shehata, Tomash Shtohryn, Benedetta Bellucci
article en

Abstract

This is a presentation of a research project which aims to collect, classify and interpret musical instruments, their terminology, iconography and contexts, based on texts, images and original finds. The outcome is presented in an online database and lexicon based on Semantic MediaWiki technology.

Zenodo (CERN European Organization for Nuclear Research)
University of Würzburg (DE)
Quality Education
Openalex Percentile: Top 8%
Ancient Near East History
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.