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

中文翻译：

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荷兰建筑库存的材料强度数据库：材料库存分析中的大数据

建筑行业的再利用和回收对于控制资源使用至关重要。关于建筑物材料内容的数据可用性是规划未来再利用潜力的重大挑战。编译材料强度 ​​(MI) 数据是时间和资源密集型的。通常研究最终只有少数数据点。为了充分覆盖城市中发现的建筑物和材料的多样性，并在详细的空间范围内准确评估材料库存，需要更多的 MI 数据点。在这项工作中，我们提供了一个关于荷兰建筑存量材料强度的数据库，其中包含 61 个大型拆除项目，共有 781 个数据点，代表超过 306,000 平方米的建筑面积。该数据集代表了荷兰被拆除的建筑物类型。我们的数据是与一家明确专注于重复使用和回收材料和组件的拆迁公司合作获得的。该数据集包括结构建筑材料和组件材料，涵盖了广泛的建筑类型、尺寸和建造年限。与现有文献相比，本文增加了明显更多的数据点，并且更详细地介绍了拆除流中发现的不同类型的材料。数据量的增加是实现大数据方法的必要步骤，例如数据挖掘和机器学习。这些方法可用于发现材料库存中以前无法识别的模式，或者更准确地估计只有稀疏数据可用的位置的材料库存。这篇文章符合Gold-Gold的要求JIE数据开放徽章在 http://jie.click/badges 中描述。