EconBiz Images for Text Extraction from Scholarly Figures

Scholarly figures are data visualizations like bar charts, pie charts, line graphs, maps, scatter plots or similar figures. Text extraction from scholarly figures is useful in many application scenarios, since text in scholarly figures often contains information that is not present in the surrounding text. This dataset is a corpus of 121 scholarly figures from the economics domain evaluating text extraction tools. We randomly extracted these figures from a corpus of 288,000 open access publications from EconBiz. The dataset resembles a wide variety of scholarly figures from bar charts to maps. We manually labeled the figures to create the gold standard. We adjusted the provided gold standard to have a uniform format for all datasets. Each figure is accompanied by a TSV file (tab-separated values) where each entry corresponds to a text line which has the following structure: X-coordinate of the center of the bounding box in pixel Y-coordinate of the center of the bounding box in pixel Width of the bounding box in pixel Height of the bounding box in pixel Rotation angle around its center in degree Text inside the bounding box In addition we provide the ground truth in JSON format. A schema file is included in each dataset as well. The dataset is accompanied with a ReadMe file with further information about the figures and their origin. If you use this dataset in your own work, please cite one of the papers in the references.学术图表（scholarly figures）是一类数据可视化形式，涵盖柱状图、饼图、折线图、地图、散点图及其他同类可视化作品。从学术图表中提取文本在诸多应用场景中均具有重要价值，因为学术图表内嵌的文本往往包含正文周边未涵盖的关键信息。 本数据集为面向经济学领域的121份学术图表语料库，用于评测文本提取工具。我们从EconBiz的28.8万篇开放获取出版物语料中随机抽取上述图表。该数据集涵盖从柱状图到地图等丰富多样的学术图表类型。我们通过人工标注的方式构建了金标准（gold standard）标注集。 我们对提供的金标准标注集进行了格式统一调整，以适配所有数据集的标准化要求。每份图表均附带一个TSV文件（制表符分隔值，tab-separated values），其中每一行对应一条文本条目，其结构如下： 边界框（bounding box）中心点的X轴像素坐标 边界框中心点的Y轴像素坐标 边界框的像素宽度 边界框的像素高度 以中心点为基准的旋转角度（单位：度） 边界框内的文本内容 此外，我们还提供了JSON格式的真值标注（ground truth）文件。每份数据集均附带一份Schema文件。本数据集同时包含README文件，用于说明图表的详细信息与来源背景。 若您在研究工作中使用本数据集，请引用参考文献中的任意一篇相关论文。