{"id":2875,"date":"2026-06-03T09:53:12","date_gmt":"2026-06-03T09:53:12","guid":{"rendered":"https:\/\/interactivehpc.dk\/?p=2875"},"modified":"2026-06-03T09:53:12","modified_gmt":"2026-06-03T09:53:12","slug":"use-case-how-ucloud-supported-large-scale-research-combining-time-use-and-consumption-data-to-understand-socio-economic-differences","status":"publish","type":"post","link":"https:\/\/interactivehpc.dk\/?p=2875","title":{"rendered":"\u00a0Use case: How UCloud supported large-scale research combining time-use and consumption data to understand socio-economic differences\u00a0"},"content":{"rendered":"\n

\u00a0UCloud played an important role in Sofia Topcu Madsen\u2019s research by helping her analyse large-scale time-use and consumption data across seven countries faster and more efficiently, supporting her work to gain insights into how people spend their time and money in everyday life.\u00a0<\/em><\/p>\n\n\n\n

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Sofia Topcu Madsen is a former PhD fellow at Aalborg University, Department of Sustainability and Planning. As part of her PhD project, Getting the Data Right, she investigates how people across seven countries in low- and middle-income countries spend time and money on different everyday activities \u2014 and how socio-economic factors shape what people are able to do.\u00a0<\/p>\n\n\n\n

The project looks at countries including Uganda, Kenya, Tanzania, India, Sri Lanka, Argentina and Mongolia. Based on large-scale time-use and consumption data, Sofia analyses activities such as transport and household work and explores how time and money spent on everyday activities vary across different socio-economic groups. <\/p>\n\n\n\n

Working with large datasets <\/strong><\/h2>\n\n\n\n

Sofia\u2019s analyses are based on different types of detailed data. One example is time-use diaries, where participants report what they do throughout the day in 10-minute intervals. For some countries, the datasets are very large. In the Indian dataset alone, Sofia works with around half a million observations. <\/p>\n\n\n\n

This makes the computational work demanding. At first, Sofia tried running the analyses on her own computer, but the datasets were too large and the analyses too time-consuming. <\/p>\n\n\n\n

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\u201cOn my own computer, the analyses could take several days to run. With UCloud, it became much faster and more manageable,\u201d Sofia explains. <\/p>\n<\/blockquote>\n\n\n\n

UCloud gave her access to more computing power, making it possible to run large analyses more efficiently and rerun them when corrections or adjustments were needed. This became important throughout the project, as even small changes in the data setup or model specification could require the analyses to be run again. <\/p>\n\n\n\n

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\u201cUCloud has been a huge help. I do not think I would have been able to complete this part of the project in the same way without access to it,\u201d Sofia says. <\/p>\n<\/blockquote>\n\n\n\n

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Using Stata and R on UCloud <\/strong><\/h2>\n\n\n\n

To conduct the analysis, Sofia used Stata and R on UCloud. Stata and R are tools that researchers use to work with data and carry out statistical analyses. <\/p>\n\n\n\n

In Sofia\u2019s project, the tools were used to run regression analyses, where she examines how different factors may be connected \u2014 for example how education, income or gender may relate to the amount of time and money people spend on transport, household work or other everyday activities. <\/p>\n\n\n\n

She used SUR methods, which make it possible to run several related analyses at the same time. This was relevant because the project looks at activities across a full 24-hour day, where time spent on one activity can be connected to time spent on another. Similarly, money spent on products supporting one activity limits money for other products. <\/p>\n\n\n\n

Running several analyses at the same time with large datasets requires a lot of computing power and would have been very time-consuming to do on a normal computer. By using UCloud, Sofia could run the analyses faster and more efficiently, saving her a lot of time. <\/p>\n\n\n\n

Contributing to research on sustainable development <\/strong><\/h2>\n\n\n\n

Sofia\u2019s research is connected to the UN Sustainable Development Goals by exploring how everyday activities can be used as indicators of broader social and economic conditions. <\/p>\n\n\n\n

How people spend their time can tell us something important about everyday life, inequality and opportunities. For example, a joint perspective on time and money spent on transport, household work, or leisure can reveal how resources, responsibilities, and opportunities are distributed across different population groups. <\/p>\n\n\n\n

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\u201cTime can also be understood as a resource. Looking at how people spend their time gives us another way to understand poverty, inequality and sustainable development,\u201d Sofia explains. <\/p>\n<\/blockquote>\n\n\n\n

A platform that was easy to get started with <\/strong><\/h2>\n\n\n\n

Sofia describes UCloud as easy to access and use, especially once the workflow was in place. She also highlights the support as an important part of the experience. <\/p>\n\n\n\n

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\u201cThe support has been very effective. I have received quick answers to my questions, and that has been a big help,\u201d she says. <\/p>\n<\/blockquote>\n\n\n\n

Sofia received support from Aalborg University\u2019s local Front Office. Each Danish university has its own Front Office, where researchers can get help with access, use and questions related to UCloud. <\/p>\n\n\n\n

Would use UCloud again <\/strong><\/h2>\n\n\n\n

Sofia is now employed at the University of Copenhagen, Department of Food and Resource Economics, and she can see herself using UCloud again in future research. <\/p>\n\n\n\n

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\u201cI would definitely use UCloud again,\u201d she says. <\/p>\n<\/blockquote>\n\n\n\n

Because UCloud is available to researchers affiliated with Danish universities, Sofia can also continue to use the platform in future research projects at the University of Copenhagen.\u00a0<\/p>\n","protected":false},"excerpt":{"rendered":"

\u00a0UCloud played an important role in Sofia Topcu Madsen\u2019s research by helping her analyse large-scale time-use and consumption data across seven countries faster and more efficiently, supporting her work to gain insights into how people spend their time and money in everyday life.\u00a0 Sofia Topcu Madsen is a former PhD fellow at Aalborg University, Department […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"gtp_columnspro_styling":"{}","gtp_paragraph_styling":"{\"39a15257-ce4f-4e2b-8de6-7bb822d54721\":\" .gp-gutenbergpro-39a15 { background-position-x: 50%;\\nbackground-position-y: 50%;\\nbackground-size: cover;\\nheight: px; }\",\"83ead5dd-1893-41ad-be03-52e51e9ee04d\":\" .gp-gutenbergpro-83ead { background-position-x: 50%;\\nbackground-position-y: 50%;\\nbackground-size: cover;\\nheight: px; }\",\"f329969e-08ed-4d19-b4eb-47b8d94427ba\":\" .gp-gutenbergpro-f3299 { background-position-x: 50%;\\nbackground-position-y: 50%;\\nbackground-size: cover;\\nheight: px; 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