Jupyter Notebooks for Generous Archive Interfaces

Mari Wigham; Liliana Melgar Estrada; Roeland J.F. Ordelman

doi:10.1109/BigData.2018.8622203

Jupyter Notebooks for Generous Archive Interfaces

Mari Wigham, Liliana Melgar Estrada, Roeland J.F. Ordelman

Human Media Interaction

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

4 Citations (Scopus)

284 Downloads (Pure)

Abstract

To help scholars to extract meaning, knowledge and value from large volumes of archival content, such as the Dutch Common Lab Research Infrastructure for the Arts and Humanities (CLARIAH), we need to provide more ‘generous’ access to the data than can be provided with generalised search and visualisation tools alone. Our approach is to use Jupyter Notebooks in combination with the existing archive APIs (Application Programming Interface). This gives access to both the archive metadata and a wide range of analysis and visualisation techniques. We have created notebooks and modules of supporting functions that enable the overview, investigation and analysis of the archive. We demonstrate the value of our approach in preliminary tests of its use in scholarly research, and give our observations of the potential value for archivists. Finally, we show that good archive knowledge is essential to create correct and meaningful visualisations and statistics.

Original language	English
Title of host publication	2018 IEEE International Conference on Big Data (Big Data)
Editors	Yang Song, Bing Liu, Kisung Lee, Naoki Abe, Calton Pu, Mu Qiao, Nesreen Ahmed, Donald Kossmann, Jeffrey Saltz, Jiliang Tang, Jingrui He, Huan Liu, Xiaohua Hu
Pages	2766-2774
Number of pages	9
ISBN (Electronic)	978-1-5386-5035-6
DOIs	https://doi.org/10.1109/BigData.2018.8622203
Publication status	Published - 24 Jan 2019
Event	IEEE International Conference on BIG DATA 2018 - The Westin Seattle, Seattle, United States Duration: 10 Dec 2018 → 13 Dec 2018 http://cci.drexel.edu/bigdata/bigdata2018/index.html

Conference

Conference	IEEE International Conference on BIG DATA 2018
Country/Territory	United States
City	Seattle
Period	10/12/18 → 13/12/18
Internet address	http://cci.drexel.edu/bigdata/bigdata2018/index.html

Keywords

Digital Humanities
Audiovisual archives
multimedia access
Big Data
Visualisation
jupyter notebooks

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10.1109/BigData.2018.8622203

13.WighamAccepted author version, 764 KB

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Wigham, Mari ; Melgar Estrada, Liliana ; Ordelman, Roeland J.F. / Jupyter Notebooks for Generous Archive Interfaces. 2018 IEEE International Conference on Big Data (Big Data). editor / Yang Song ; Bing Liu ; Kisung Lee ; Naoki Abe ; Calton Pu ; Mu Qiao ; Nesreen Ahmed ; Donald Kossmann ; Jeffrey Saltz ; Jiliang Tang ; Jingrui He ; Huan Liu ; Xiaohua Hu. 2019. pp. 2766-2774

@inproceedings{f9522016e8e44fa2b5edcdae8ca6aa74,

title = "Jupyter Notebooks for Generous Archive Interfaces",

abstract = "To help scholars to extract meaning, knowledge and value from large volumes of archival content, such as the Dutch Common Lab Research Infrastructure for the Arts and Humanities (CLARIAH), we need to provide more {\textquoteleft}generous{\textquoteright} access to the data than can be provided with generalised search and visualisation tools alone. Our approach is to use Jupyter Notebooks in combination with the existing archive APIs (Application Programming Interface). This gives access to both the archive metadata and a wide range of analysis and visualisation techniques. We have created notebooks and modules of supporting functions that enable the overview, investigation and analysis of the archive. We demonstrate the value of our approach in preliminary tests of its use in scholarly research, and give our observations of the potential value for archivists. Finally, we show that good archive knowledge is essential to create correct and meaningful visualisations and statistics.",

keywords = "Digital Humanities, Audiovisual archives, multimedia access, Big Data, Visualisation, jupyter notebooks",

author = "Mari Wigham and {Melgar Estrada}, Liliana and Ordelman, {Roeland J.F.}",

year = "2019",

month = jan,

day = "24",

doi = "10.1109/BigData.2018.8622203",

language = "English",

pages = "2766--2774",

editor = "Yang Song and Bing Liu and Kisung Lee and Naoki Abe and Calton Pu and Mu Qiao and Nesreen Ahmed and Donald Kossmann and Jeffrey Saltz and Jiliang Tang and Jingrui He and Huan Liu and Xiaohua Hu",

booktitle = "2018 IEEE International Conference on Big Data (Big Data)",

note = "IEEE International Conference on BIG DATA 2018 ; Conference date: 10-12-2018 Through 13-12-2018",

url = "http://cci.drexel.edu/bigdata/bigdata2018/index.html",

}

Wigham, M, Melgar Estrada, L & Ordelman, RJF 2019, Jupyter Notebooks for Generous Archive Interfaces. in Y Song, B Liu, K Lee, N Abe, C Pu, M Qiao, N Ahmed, D Kossmann, J Saltz, J Tang, J He, H Liu & X Hu (eds), 2018 IEEE International Conference on Big Data (Big Data)., 8622203, pp. 2766-2774, IEEE International Conference on BIG DATA 2018, Seattle, Washington, United States, 10/12/18. https://doi.org/10.1109/BigData.2018.8622203

Jupyter Notebooks for Generous Archive Interfaces. / Wigham, Mari; Melgar Estrada, Liliana; Ordelman, Roeland J.F.
2018 IEEE International Conference on Big Data (Big Data). ed. / Yang Song; Bing Liu; Kisung Lee; Naoki Abe; Calton Pu; Mu Qiao; Nesreen Ahmed; Donald Kossmann; Jeffrey Saltz; Jiliang Tang; Jingrui He; Huan Liu; Xiaohua Hu. 2019. p. 2766-2774 8622203.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Jupyter Notebooks for Generous Archive Interfaces

AU - Wigham, Mari

AU - Melgar Estrada, Liliana

AU - Ordelman, Roeland J.F.

PY - 2019/1/24

Y1 - 2019/1/24

N2 - To help scholars to extract meaning, knowledge and value from large volumes of archival content, such as the Dutch Common Lab Research Infrastructure for the Arts and Humanities (CLARIAH), we need to provide more ‘generous’ access to the data than can be provided with generalised search and visualisation tools alone. Our approach is to use Jupyter Notebooks in combination with the existing archive APIs (Application Programming Interface). This gives access to both the archive metadata and a wide range of analysis and visualisation techniques. We have created notebooks and modules of supporting functions that enable the overview, investigation and analysis of the archive. We demonstrate the value of our approach in preliminary tests of its use in scholarly research, and give our observations of the potential value for archivists. Finally, we show that good archive knowledge is essential to create correct and meaningful visualisations and statistics.

AB - To help scholars to extract meaning, knowledge and value from large volumes of archival content, such as the Dutch Common Lab Research Infrastructure for the Arts and Humanities (CLARIAH), we need to provide more ‘generous’ access to the data than can be provided with generalised search and visualisation tools alone. Our approach is to use Jupyter Notebooks in combination with the existing archive APIs (Application Programming Interface). This gives access to both the archive metadata and a wide range of analysis and visualisation techniques. We have created notebooks and modules of supporting functions that enable the overview, investigation and analysis of the archive. We demonstrate the value of our approach in preliminary tests of its use in scholarly research, and give our observations of the potential value for archivists. Finally, we show that good archive knowledge is essential to create correct and meaningful visualisations and statistics.

KW - Digital Humanities

KW - Audiovisual archives

KW - multimedia access

KW - Big Data

KW - Visualisation

KW - jupyter notebooks

U2 - 10.1109/BigData.2018.8622203

DO - 10.1109/BigData.2018.8622203

M3 - Conference contribution

SP - 2766

EP - 2774

BT - 2018 IEEE International Conference on Big Data (Big Data)

A2 - Song, Yang

A2 - Liu, Bing

A2 - Lee, Kisung

A2 - Abe, Naoki

A2 - Pu, Calton

A2 - Qiao, Mu

A2 - Ahmed, Nesreen

A2 - Kossmann, Donald

A2 - Saltz, Jeffrey

A2 - Tang, Jiliang

A2 - He, Jingrui

A2 - Liu, Huan

A2 - Hu, Xiaohua

T2 - IEEE International Conference on BIG DATA 2018

Y2 - 10 December 2018 through 13 December 2018

ER -

Jupyter Notebooks for Generous Archive Interfaces

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