Material intensity database for the Dutch building stock: Towards Big Data in material stock analysis

Re-use and recycling in the construction sector is essential to keep resource use check. Data availability about material contents of buildings significant challenge for planning future re-use potentials. Compiling intensity (MI) data time intensive. Often studies end up with only a handful datapoints. In order adequately cover diversity materials found cities, accurately assess stocks at detailed spatial scopes, many more MI datapoints are needed. this work, we present database on Dutch building stock, containing 61 large-scale demolition projects total 781 datapoints, representing than 306,000 square meters built floor space. This dataset representative types being demolished Netherlands. Our were empirically sourced collaboration company that explicitly focuses re-using components. The includes both structural component materials, covers wide range types, sizes, years. Compared existing literature, paper adds significantly detail different streams. increase volume necessary step toward enabling big methods, such as mining machine learning. These methods could be used uncover previously unrecognized patters stocks, or estimate locations have sparse available. article met requirements Gold-Gold JIE openness badge described http://jie.click/badges.