Datasets and Data Dictionaries

This page provides freely-downloadable access to data outputs created by the Australian Cultural Data Engine in cooperation with our partners.

Before using any ACD-Engine data, please consult our data workbook here. This interactive workbook provides details on the project, our partners, the data extraction and cleaning process, and the ACD-Engine data architecture, as well as bespoke analytics showcasing the potential these datasets afford for digital cultural research.

  • These seven datasets comprise unified materials from our partner datasets AusStage, Circus Oz, DAQA, DAAO, and the Summerhayes Family Collection, merged into a unified dataset architecture. For more information on this architecture, see the ACD-Engine Data Workbook and the Data Dictionaries on this page.

    To access original materials, which may have been updated since our latest extraction, as well as helpful additional analytical tools and visualisations based on their individual data, we encourage researchers to visit our partner databases directly.

    ACD-Engine Unified Dataset – Event

    Download CSV (GZIP file, 103.6 MB)

    Download JSONL (GZIP file, 104.9 MB)

    Download XLSX Sample (14.5 MB)

    ACD-Engine Unified Dataset – Organisation

    Download CSV (GZIP file, 38.5 MB)

    Download JSONL (GZIP file, 38.6 MB)

    Download XLSX Sample (2 MB)

    ACD-Engine Unified Dataset – Person

    Download CSV (GZIP file, 190.6 MB)

    Download JSONL (GZIP file, 191.4 MB)

    Download XLSX Sample (20.7 MB)

    ACD-Engine Unified Dataset – Place

    Download CSV (GZIP file, 12.7 MB)

    Download JSONL (GZIP file, 12.7 MB)

    Download XLSX Sample (1.1 MB)

    ACD-Engine Unified Dataset – Recognition

    Download CSV (GZIP file, 996 KB)

    Download JSONL (GZIP file, 998 KB)

    Download XLSX Sample (153 KB)

    ACD-Engine Unified Dataset – Resource

    Download CSV (GZIP file, 27 MB)

    Download JSONL (GZIP file, 26.8 MB)

    Download XLSX Sample (3.3 MB)

    ACD-Engine Unified Dataset – Work

    Download CSV (GZIP file, 8.9 MB)

    Download JSONL (GZIP file, 8.9 MB)

    Download XLSX Sample (1.5 MB)

    To Cite These Datasets

    To cite these datasets, you may use the following suggested format: Ivy Zheng, Justin Munoz, David Carlin, Scott East, Chris Hay, Joanna Mendelssohn, John Macarthur, David McMeekin, Deborah van der Plaat, and the ACD-Engine Team, ‘[Dataset Title]’, Australian Cultural Data Engine, August 2023, acd-engine.org/datasets.

  • The ACD-Engine Unified Dataset contains variables drawn from selected datasets generated from our partner databases. The ACD-Engine Unified Data Dictionary explains the meaning of each variable.

    The individual partner data dictionaries explain each database’s distinctive variables and how they have been translated into the ACD-Engine Unified Dataset architecture. These will be of value to researchers using subsets of the larger unified datasets, and comparing them with new data extractions from individual databases.

    Download ACD-Engine Unified Data Dictionary (XLSX, 169 KB)

    Download AusStage Data Dictionary (XLSX, 31 KB)

    Download Circus Oz Data Dictionary (XLSX, 16 KB)

    Download DAAO Data Dictionary (XLSX, 73 KB)

    Download DAQA Data Dictionary (XLSX, 60 KB)

    Download Summerhayes Family Collection Data Dictionary (XLSX, 13 KB)

    To Cite These Data Dictionaries

    To cite these data dictionaries, you may use the following suggested format: Ivy Zheng, Justin Munoz and the ACD-Engine Team, ‘[Data Dictionary Title]’, Australian Cultural Data Engine, May 2023, acd-engine.org/datasets.

  • These datasets feature in ACD-Engine publications and data analysis, and draw on existing materials found in our partner databases that have been subsetted, supplemented, merged and/or interlinked with other resources to answer specific research questions.

    To access original materials, which may have been updated since our latest extraction, as well as helpful additional analytical tools and visualisations based on their individual data, we encourage researchers to visit our partner databases directly.

    DAAO Selected Biographical Dataset

    This dataset presents metadata and full text biographies for 2,188 artists represented in Design and Art Australia Online. Beginning in December 2021 with a data extraction from the DAAO database, Zheng and the ACD-Engine team selected key columns to create a list of all biographical entries, separating them from works, groups, and other entities. The team then filtered out draft and deleted entries, leaving over 17,000 public-facing entries. Many of these entries were stubs, or relate to artists whose careers mainly took place outside the scope of the ACD-Engine project (1945-present). This smaller selection of 2,188 biographical entries represents the artists which had all or most of the following key variables filled in – primary name AND/OR surname, gender, birth year, career start year, and broad artistic role – and were not born before 1900 or whose career had not ended before 1945. Of these, all but 54 also had prose biographical data available. The raw data for 500 of these entries, selected on the basis of their importance to Australian art history, have been supplemented by East, Mendelssohn and Mora, with particular emphasis on artist residence locations and periods, birth places, and languages. This dataset contains the 22 variables listed in the ‘DAAO Codebook'; in future versions of this dataset, we intend to include additional columns found in the DAAO database, including geocoding details for places and links to related entries.

    Download DAAO Selected Biographical Dataset v.1.1 (CSV, 2.4 MB)

    Download DAAO Selected Biographical Dataset v.1.1 (JSON, 9.8 MB)

    To cite this dataset, you may use the following suggested format: Scott East, Joanna Mendelssohn, Aneshka Mora, Ivy Zheng, and ACD-Engine Team, ‘DAAO Selected Biographical Dataset’, November 2022, Australian Cultural Data Engine, https://www.acd-engine.org/data/data-outputs.

    To cite this description, you may use the following suggested format: Ivy Zheng, Nat Cutter, Tyne Daile Sumner and ACD-Engine Team, ‘DAAO Selected Biographical Dataset Description’, October 2022, Australian Cultural Data Engine, https://www.acd-engine.org/data/data-outputs.

  • [Please note: These codebooks are legacy items. For the most up-to-date variable descriptions, please consult our Data Dictionaries]

    Our codebooks include information about where our data come from and how they were collected. The codebooks accompany each dataset and include a list of the variables included in the dataset and what those variables measure. They can be used by researchers, historians, social scientists, data scientists, and anyone conducting digital humanities work using cultural data.

    AusStage Codebook

    Download AusStage Codebook v2.0 (PDF, 238 KB)

    To cite this codebook, you may use the following suggested format: Trent Ryan, AusStage and Contributors (2003-22), and ACD-Engine Team, ‘AusStage Codebook v.2.0’, June 2022, Australian Cultural Data Engine, http://hdl.handle.net/11343/315743.

    This project and the codebooks and datasets acknowledge AusStage: ©️ AusStage and contributors, CC BY-NC-SA 4.0.

    DAAO Codebook

    Download DAAO Codebook v2.0 (PDF, 371 KB)

    To cite this codebook, you may use the following suggested format: Trent Ryan, Scott East, Joanna Mendelssohn, and ACD-Engine Team, ‘DAAO Codebook v.1.1, November 2022, Australian Cultural Data Engine, http://hdl.handle.net/11343/308420.

    DAQA Codebook

    Download DAQA Codebook v1.0 (PDF, 243 KB)

    To cite this codebook, you may use the following suggested format: Trent Ryan, Deborah van der Plaat, John Macarthur, and ACD-Engine Team, ‘DAQA Codebook v.1.0’, June 2022, Australian Cultural Data Engine, http://hdl.handle.net/11343/315742.