This week read about a new collaborative open data initiative for developing countries, the importance of data literacy and open data projects in China. There is also news on the potential for those with little data footprint to be excluded from Big Data informed decisions. The necessity of understanding the value you want from Big Data before embarking on Big Data projects is also emphasised.
At the Open Knowledge Foundation Conference held in Geneva last week, The World Bank announced a three year open data initiative. Partnering with The Open Data Institute and the Open Knowledge Foundation it aims to help developing countries start open data initiatives, increase open data use and show the impact of open data on development which a $1.25 million dollar budget for the first year.
In this UNDP (Central and Eastern Asia) post the need to increase data literacy among all citizens to ensure open data is used for accountable governance is discussed. Some projects that help to support this are highlighted. The way that open data is presented to the public is viewed as key to success. Standardised data across government departments in machine readable format is essential. The media’s role in turning complicated data into more comprehensive and insightful news articles, graphics and maps is also important. However, it is stressed that data literacy should not be confined to journalists as citizens that are non experts should be educated so they too can read and interpret data as data literacy may become the new computer literacy.
In this TechPresident post Cui Anyong, a recent graduate of City University of Hong Kong explains how he and other young techies are finding and using open data despite user challenges and political risks. He says that open data exists in China even if it is limited. For instance, the government publishes water-air quality and earthquake data in real time and its primary open data sites are Beijing Data, Data Shanghai and the National Bureau of Statistics. Cui is using data from the Chinese government’s websites to see if he can detect patterns between water quality and health including in so coined ‘cancer villages’. Data is also scraped from Weibo and news websites. This open data agenda is not at all government-driven as in some other countries and a lot of the data is not in a readable format.
Recent research by Wikibon has found that enterprises are investing in Big Data before understanding how they will get value from it and as a result are not making returns on their investment. Wikibon found that 46% of Big Data practitioners have had only partial success from their projects, and 2% have had to write off their investments. Specific and measurable business applications must be a core part of Big Data projects and Big Data becomes useless Data when an organisation hoards data without knowing why it is needed. This results in collecting data that creates noise and obscures the signal in the data. According to Wikibon, the best Big Data projects, "are generally not initiated by IT but driven by line-of-business departments, often marketing, and focus on small but strategic use cases."
This Co.Exist post by Jessica Leber questions what happens when those that are not digitally connected are left behind in decisions that utilise big data analysis. If Big Data tools are designed for the “electronically harvestable” person, those that are less digitally connected may actually face the problem of not being tracked enough. Those that provide no data will be excluded from opportunities and from democratic participation and so she says that policymakers must supplement a big data approach with considerations for those with less of a digital footprint.