FabLab SUPSI DACD - Machine and Training Usage Dataset

The Digital Fabrication and Open Innovation Laboratory (FabLab) - SUPSI located on the DACD campus of SUPSI is a facility that supports students and staff of the university in the physical production of digital projects in the fields of architecture, interior design, engineering, design, conservation and restoration, and microbiology. The laboratory offers various machines for rapid prototyping, including: laser cutting machines, small and large format 3D printers, numerically controlled milling machines, vinyl cutters and an electronics workstation. In order to use the machines, it is necessary to take a vertical training course on the machine and the safety practices to be followed for its use. Authorised users can then book the equipment in 20-minute slots, either free of charge or for a fee, depending on the equipment. The booking of training courses and machine slots is managed through an open source platform called FabManager. The local instance can be accessed at fabmanager.supsi.ch. After registering via SSO, SUPSI users can log in to their management profile. On the platform, it is possible to view the details of each machine, finding technical data sheets and information about courses and available slots. As the platform administrator, it is possible to access a user management panel and a set of APIs for analysing data related to the laboratory. From the backend, statistics can be easily viewed through an intuitive user interface, with the ability to filter data by user, date, gender, age, type and cost. Dataset content and retrevial Direct database interrogation via platform-provided Application Programming Interfaces (APIs) is employed.Data are retrieved utilising a custom Python package, that is released via GitHub, resulting in clean tabular data formatted as JSON and comprising the following entries: users (number not public), machinery bookings (n=10639), course registrations (n=1477), a list of machines (n=34), and a list of courses (n=29). Due to the absence of publicly available APIs for projects retrieval, these records are excluded from this dataset. The specific field definitions applicable to each data category are comprehensively documented within the FabLab_DACD_SUPSI_UsageData_Schema.json document. Data cleaning process The raw data exported from the APIs is analysed and minimised to guarantee anonymisation. The analysis of the actual type of data is carried out below. Machine data The dataset pertaining to the machines within the digital fabrication laboratory of DACD contains information regarding all machinery, both operational and disabled. As some records relate to equipment not publicly visible, identified by ‘disabled’: true, these are removed from the published dataset to prevent sharing details concerning machinery unavailable to lab users. The dataset also includes a slug referencing each machine’s public-facing webpage; this is completed with the domain name to facilitate Linked Open Data connectivity. Creation dates of machines may serve as useful provenance information, indicating when equipment was added to the laboratory's inventory, only the date component is retained. Update dates are deemed unnecessary for potential analyses. Machine descriptions and specifications currently utilise HTML formatting, which hinders readability; therefore, a cleaning process eliminates superfluous tags while preserving external links to maintain connections with relevant sources. Metadata appended at the end of each file includes: data and time of cleaning, Data Owner (the dataset’s owner), Data Steward (responsible for data cleansing), Data Curator (responsible for initial data collection), source system from which the data are extracted ("Data Exported from"), date and time of export (“Data Exported at”), and licensing terms. Training data The dataset pertaining to the training courses offered at the digital fabrication laboratory of DACD contains data relating to all available courses. These records include course names, slugs linking to corresponding webpages, a flag indicating public visibility, creation and modification dates, the number of places available per session, and descriptions formatted in HTML. Following similar principles as previously described, this dataset undergoes cleaning according to established procedures; the maximum participant capacity is retained due to its potential utility for analytical purposes without compromising data integrity. The metadata remain consistent with those detailed earlier. Machine reservation data This dataset compiles all machinery bookings made at the laboratory, including user and machine details. To protect privacy, only the following data elements are retained: creation date of the booking, user group (course of study), identifier and link to the booked machine, an indicator denoting cancellation status, and duration of the reservation in hours. The metadata adhere to the conventions established for previous datasets. Training reservation data This dataset mirrors the structure of its predecessor, incorporating various details pertaining to booked training courses. The following data elements are retained within this recordset: booking creation date, user group affiliation, course identification and URL link, and an indicator denoting cancellation status. Folder structure The directory comprises three files at the primary level. FabLab_DACD_SUPSI_UsageData_Schema.json contains the dataset schema formulated according to JSON Schema Draft 7, incorporating supplementary details such as version information, authorial attribution, affiliation, creation and update dates, alongside requisite schema elements. A descriptive account of each field is included, accompanied by data type specifications and formatting particulars where applicable. FabLab_DACD_SUPSI_UsageData_Metadata_Export_02_12_2025.json exclusively houses metadata—also incorporated within the dataset itself—providing specific information pertaining to dates of data merging, data ownership, stewardship details (including ORCID identifiers), curation responsibilities (with corresponding ORCID identifier), source system for exported data, licensing terms, DOI assignment, and machine-specific export/cleaning timestamps for both machinery and training data. Finally, FabLab_DACD_SUPSI_UsageData_Export_02_12_2025.json represents the dataset itself, incorporating metadata as previously described alongside the substantive data arranged into categories: machines, trainings, reservations_machine, and reservations_training; structural details for each category are delineated within the schema document. Ethics risks It is possible to distinguish between the use of the machines by groups of students, which could limit the sample of users who may have used the machine at that time to around 40 people. This could inadvertently facilitate correlation between specific users and the equipment use on particular days; however, this association is not deemed inherently detrimental given the complexity involved in definitively identifying individual user identities and the actual information obtained, thus precluding any required remedial action. Sharing machine usage data allows for assessment of laboratory presence rates, a form of monitoring information that holds potential for misuse. However, as the facility operates within a public setting, no mitigating actions are considered necessary; furthermore, this information is crucial for dataset analysis. Within the training course descriptions, teaching staff names and surnames frequently appear. No specific measures are implemented in response to this occurrence, given their existing availability on the laboratory’s publicly accessible website. Technical risks Due to its considerable size, manual assessment of this dataset proves challenging; therefore, minimisation and anonymisation were wholly executed via Python scripting. While there remains a theoretical possibility of inadvertently sharing non-public data through this automated process, the robust JSON schema structure significantly mitigates such risk. The entire dataset has been restructured according to a defined logic, simplified within the accompanying scheme file; however, unfamiliarity with this new architecture may impede analytical efforts. Contacts Matteo Subet - Institute of Design (Interaction Design Research Group) [e-mail] - Department of Environment Constructions and Design [e-mail]瑞士南部应用科学与艺术大学（SUPSI）DACD校区的数字制造与开放创新实验室（FabLab）是为该校师生提供支持的实体制作设施，可助力其完成建筑、室内设计、工程、设计、保护与修复以及微生物学领域的数字项目实体化生产。 该实验室配备多款用于快速原型（rapid prototyping）制作的设备，包括激光切割机、大幅面与小幅面3D打印机、数控铣床、刻字机以及电子工作站。若要使用设备，需参加对应设备的专项培训课程，并掌握设备使用需遵循的安全规范。获得授权的用户可按20分钟为单位预约设备，预约费用依设备类型而定，可免费或付费使用。 培训课程与设备预约均通过名为FabManager的开源平台进行管理。该平台的本地实例可通过fabmanager.supsi.ch访问。SUPSI师生通过单点登录（Single Sign-On，SSO）完成注册后，即可登录个人管理面板。在平台上，用户可查看每台设备的详细信息，包括技术数据表、课程信息以及可预约时段。 平台管理员可访问用户管理面板，以及一套用于分析实验室相关数据的应用程序编程接口（Application Programming Interface，API）。通过后端直观的用户界面，管理员可便捷查看统计数据，并支持按用户、日期、性别、年龄、设备类型及费用进行数据筛选。 ## 数据集内容与获取方式 本数据集通过平台提供的应用程序编程接口（Application Programming Interface，API）直接查询数据库获取数据。数据通过GitHub发布的定制化Python工具包进行采集，最终得到格式为JSON的标准化表格数据，包含以下数据集条目：用户信息（具体数量未公开）、设备预约记录（n=10639）、课程报名记录（n=1477）、设备清单（n=34）以及课程清单（n=29）。由于项目获取暂无公开可用的API，相关记录未纳入本数据集。各数据类别的具体字段定义已在FabLab_DACD_SUPSI_UsageData_Schema.json文件中进行了全面说明。 ## 数据清洗流程 从API导出的原始数据将经过分析与精简，以确保数据匿名化。下文将对实际数据类型的分析过程进行说明。 ### 设备数据 DACD校区数字制造实验室的设备数据集涵盖所有设备的信息，包括正常运行与停用的设备。部分设备记录标记为`disabled: true`，代表该设备未对实验室用户公开，此类记录将从公开数据集中移除，避免泄露实验室用户无法使用的设备细节。数据集还包含指向各设备公开网页的短标识符（slug），补全域名后可支持关联开放数据（Linked Open Data）的互联互通。设备创建日期可作为有效的溯源信息，用于标识设备加入实验室库存的时间，因此仅保留日期部分，而更新日期对后续分析无必要，予以剔除。 当前设备描述与规格参数采用HTML格式，不利于阅读，因此清洗流程将移除冗余标签，但保留外部链接以维持与相关来源的关联。每个文件末尾附加的元数据包括：清洗日期与时间、数据集所有者（Data Owner）、数据管理员（Data Steward，负责数据清洗）、数据策展人（Data Curator，负责初始数据采集）、数据提取来源系统（标注为"Data Exported from"）、数据导出日期与时间（标注为"Data Exported at"）以及许可协议条款。 ### 培训数据 DACD校区数字制造实验室的培训数据集涵盖所有开设课程的相关信息。此类记录包含课程名称、指向对应网页的短标识符、公开可见性标记、创建与修改日期、单场课程可容纳的名额，以及HTML格式的课程描述。遵循前文所述的相同原则，该数据集将按照既定流程进行清洗：由于最大参与人数对分析具有实用价值且不会损害数据完整性，因此予以保留。元数据格式与前文所述一致。 ### 设备预约数据 本数据集汇总了实验室所有设备预约记录，包含用户与设备的相关信息。为保护用户隐私，仅保留以下数据字段：预约创建日期、用户群体（就读专业）、被预约设备的标识符与链接、预约取消状态标记，以及以小时为单位的预约时长。元数据格式遵循此前数据集的约定。 ### 培训预约数据 本数据集的结构与设备预约数据集一致，涵盖已预约培训课程的各类详情。本数据集仅保留以下数据字段：预约创建日期、用户群体所属关系、课程标识符与URL链接，以及预约取消状态标记。 ## 文件夹结构 该数据集目录的根层级包含三个文件。 FabLab_DACD_SUPSI_UsageData_Schema.json文件包含遵循JSON Schema Draft 7标准制定的数据集架构，其中补充了版本信息、作者归属、所属机构、创建与更新日期等内容，并包含必要的架构元素。该文件对每个字段进行了详细说明，并在适用时提供了数据类型规范与格式细节。 FabLab_DACD_SUPSI_UsageData_Metadata_Export_02_12_2025.json文件仅包含元数据（元数据也会嵌入数据集本身），提供以下具体信息：数据合并日期、数据所有者信息、数据管理员详情（包含开放研究者与贡献者身份（Open Researcher and Contributor ID，ORCID）标识符）、数据策展职责（包含对应的ORCID标识符）、导出数据的来源系统、许可协议条款、数字对象唯一标识符（Digital Object Identifier，DOI）分配情况，以及设备与培训数据各自的导出/清洗时间戳。 最后，FabLab_DACD_SUPSI_UsageData_Export_02_12_2025.json文件即为数据集本体，嵌入了前文所述的元数据，并将实体数据划分为以下类别：设备、培训课程、设备预约、培训预约；各类别的结构细节已在架构文件中进行了说明。 ## 伦理风险 可通过学生群体区分设备使用情况，这可能将特定时段使用设备的用户样本缩小至约40人，从而可能无意间建立特定用户与特定日期设备使用行为之间的关联。但由于明确识别单个用户身份的流程复杂，且实际获取的信息有限，此类关联本身并不会造成危害，因此无需采取任何补救措施。 共享设备使用数据可用于评估实验室的到场率，此类监控信息存在被滥用的潜在可能。但由于该实验室面向公众开放，因此无需采取缓解措施；此外，此类信息对数据集分析至关重要。 培训课程描述中经常出现授课教师的姓名。由于教师姓名已在实验室的公开网站上对外展示，因此未针对此情况采取额外的保护措施。 ## 技术风险 由于本数据集规模较大，人工审核存在难度，因此数据精简与匿名化流程完全通过Python脚本自动化执行。尽管理论上仍存在自动化流程意外泄露非公开数据的可能性，但严谨的JSON架构可大幅降低此类风险。 整个数据集已按照既定逻辑进行重构，并在配套的架构文件中进行了简化，但由于用户可能不熟悉该新架构，可能会对数据分析造成阻碍。 ## 联系方式 马特奥·苏贝蒂（Matteo Subet）——瑞士南部应用科学与艺术大学设计学院（交互设计研究组） 邮箱：[e-mail] 数字制造实验室——瑞士南部应用科学与艺术大学环境、建造与设计系 邮箱：[e-mail]