TY - GEN
T1 - CensusIRL
T2 - 2022 IEEE International Conference on Big Data, Big Data 2022
AU - Doherty, Adam J.
AU - Murphy, Rachel A.
AU - Schieweck, Alexander
AU - Clancy, Stuart
AU - Breathnach, Ciara
AU - Margaria, Tiziana
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Census returns are a critical source of information for governments globally. They underpin a wide spectrum of public planning including health, housing, work and education. Historically, census forms have captured names, places, dates, age, occupation, family structure, and religion. In more recent times, sexual orientation and ethnicity, queries that can be intrusive to vulnerable communities, have been added to the criteria, and for such reasons data security is of paramount importance. Most governments restrict access to individual census returns, presenting the data in aggregate report format. The Irish government is particularly strict, enforcing a statutory closure period of 100 years. An exception was made for the Irish 1911 census which were digitised and released for free online consultation in 2009 [1]. They are an excellent source for genealogists and historians alike but exist as separate digital siloes. This project uses an eXtreme Model-Driven Development (XMDD) environment to create linkages between both datasets. It will discuss the development process of the CensusIrl application and the process used in developing the matching algorithm used. We will discuss the census records and the data cleansing process used in creating the initial proof of concept application. We detail the different approaches to the development life-cycle of the application and describe the different utilises used in the sanitation of data points in the records and the match-making process.
AB - Census returns are a critical source of information for governments globally. They underpin a wide spectrum of public planning including health, housing, work and education. Historically, census forms have captured names, places, dates, age, occupation, family structure, and religion. In more recent times, sexual orientation and ethnicity, queries that can be intrusive to vulnerable communities, have been added to the criteria, and for such reasons data security is of paramount importance. Most governments restrict access to individual census returns, presenting the data in aggregate report format. The Irish government is particularly strict, enforcing a statutory closure period of 100 years. An exception was made for the Irish 1911 census which were digitised and released for free online consultation in 2009 [1]. They are an excellent source for genealogists and historians alike but exist as separate digital siloes. This project uses an eXtreme Model-Driven Development (XMDD) environment to create linkages between both datasets. It will discuss the development process of the CensusIrl application and the process used in developing the matching algorithm used. We will discuss the census records and the data cleansing process used in creating the initial proof of concept application. We detail the different approaches to the development life-cycle of the application and describe the different utilises used in the sanitation of data points in the records and the match-making process.
KW - Census Data
KW - Digital Humanities
KW - Low-code Application Development
KW - Model-Driven Development
KW - Optimization
KW - PBL
UR - http://www.scopus.com/inward/record.url?scp=85147906466&partnerID=8YFLogxK
U2 - 10.1109/BigData55660.2022.10021106
DO - 10.1109/BigData55660.2022.10021106
M3 - Conference contribution
AN - SCOPUS:85147906466
T3 - Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022
SP - 2507
EP - 2514
BT - Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022
A2 - Tsumoto, Shusaku
A2 - Ohsawa, Yukio
A2 - Chen, Lei
A2 - Van den Poel, Dirk
A2 - Hu, Xiaohua
A2 - Motomura, Yoichi
A2 - Takagi, Takuya
A2 - Wu, Lingfei
A2 - Xie, Ying
A2 - Abe, Akihiro
A2 - Raghavan, Vijay
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 17 December 2022 through 20 December 2022
ER -