Understanding computational web archives research methods using research objects. Maemura, E., Becker, C., & Milligan, I. In 2016 IEEE International Conference on Big Data (Big Data), pages 3250–3259, December, 2016.
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Use of computational methods for exploration and analysis of web archives sources is emerging in new disciplines such as digital humanities. This raises urgent questions about how such research projects process web archival material using computational methods to construct their findings. This paper aims to enable web archives scholars to document their practices systematically to improve the transparency of their methods. We adopt the Research Object framework to characterize three case studies that use computational methods to analyze web archives within digital history research. We then discuss how the framework can support the characterization of research methods and serve as a basis for discussions of methods and issues such as reuse and provenance. The results suggest that the framework provides an effective conceptual perspective to describe and analyze the computational methods used in web archive research on a high level and make transparent the choices made in the process. The documentation of the research process contributes to a better understanding of the findings and their provenance, and the possible reuse of data, methods, and workflows.
@inproceedings{maemura_understanding_2016,
	title = {Understanding computational web archives research methods using research objects},
	doi = {10.1109/BigData.2016.7840982},
	abstract = {Use of computational methods for exploration and analysis of web archives sources is emerging in new disciplines such as digital humanities. This raises urgent questions about how such research projects process web archival material using computational methods to construct their findings. This paper aims to enable web archives scholars to document their practices systematically to improve the transparency of their methods. We adopt the Research Object framework to characterize three case studies that use computational methods to analyze web archives within digital history research. We then discuss how the framework can support the characterization of research methods and serve as a basis for discussions of methods and issues such as reuse and provenance. The results suggest that the framework provides an effective conceptual perspective to describe and analyze the computational methods used in web archive research on a high level and make transparent the choices made in the process. The documentation of the research process contributes to a better understanding of the findings and their provenance, and the possible reuse of data, methods, and workflows.},
	booktitle = {2016 {IEEE} {International} {Conference} on {Big} {Data} ({Big} {Data})},
	author = {Maemura, E. and Becker, C. and Milligan, I.},
	month = dec,
	year = {2016},
	keywords = {Big data, Computational modeling, Cultural differences, Digital curation, Documentation, Internet, Web archival material, Web archives sources analysis, Web archives sources exploration, computational Web archives research methods, computational archival science, computational methods, context, digital history research, digital humanities, history, information retrieval, libraries, research object framework, research objects, research projects, web archives},
	pages = {3250--3259}
}
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