温州智慧城市书房书房运营数据

通过书房自助设备以及智慧城市书房治理端和驾驶舱等应用平台获取温州地区各个城市书房开放情况、读者行为数据、书房使用数据等，并通过大数据分析得出各地区书房分布情况、运营情况和数据趋势，了解读者到访频率等。用于同行业以及相关的图书资料产业的优化布局、活动营销等，也可用为当地文化产业数字化管理系统做评价指标数据，该书房运营数据模型还可用于其它城市书房大数据管理系统的构建。通过智慧城市书房治理端和驾驶舱等应用平台获取到城市书房的书房归属地信息行政编号、书房地图坐标经纬度、书房座位数、书房面积、书房开放时间、上一年星级评定等信息，然后分别按照一定规则进行计算，其中通过书房归属地信息行政编号进行分类求和得出本区书房数量，再结合书房地图坐标经纬度于百度地图上形成书房的具体分布，另外sum(书房座位数)=所有书房总座位数,sum(书房面积)=所有书房总面积,根据书房开放时间中day:1至day:7的数据和该日是周几分别求和得出今日书房开放数量，根据公式：上一年度五星级书房比例=去重计算（count(上一年星级评定=5的书房名称 )/count(所有数据的书房名称)），得出上一年度五星级书房比例。再通过书房自助设备获取书房当日刷卡次数，分别按月按年求和得出书房本月刷卡次数和书房今年刷卡次数，最后再求和计算出所有书房今年总刷卡次数，同时根据当前日期count(书房当日刷卡次数>0)/书房总数量=今日书房刷卡开门率。

This dataset is collected via self-service study room devices, Smart City Study Room Governance Terminal, Command Cockpit and other application platforms, encompassing the opening status, reader behavior data and usage data of all urban study rooms in Wenzhou. Big data analytics are applied to derive regional study room distribution, operational conditions, data trends and reader visit frequency.

The dataset supports optimized layout planning and event marketing for the industry and related book and information industries, and can serve as evaluation index data for local digital management systems of cultural industries. Furthermore, this urban study room operation data model can be utilized to construct big data management systems for other urban study rooms.

The specific data acquisition and calculation procedures are as follows:
1. Basic information collection: Obtain the administrative code of the affiliated locality, geographic coordinates (longitude and latitude), number of seats, area, opening hours and previous year's star rating of each urban study room through the Smart City Study Room Governance Terminal and Command Cockpit platforms.
2. Regional quantity and spatial distribution: Sum the number of study rooms by their affiliated administrative code to obtain the count of study rooms in each local district, and generate the precise spatial distribution of study rooms on Baidu Maps by combining the longitude and latitude data.
3. Aggregate resource statistics: Calculate the total seats of all study rooms as the sum of individual study room seat counts, and the total area of all study rooms as the sum of individual study room areas.
4. Daily open study room count: Sum the opening hours data corresponding to day:1 to day:7 and match with the current day of the week to obtain the number of study rooms open today.
5. Previous year five-star study room proportion: Calculate via deduplicated counting of study room names: (number of unique study room names with a previous year star rating of 5) / (total number of unique study room records).
6. Swipe count statistics: Obtain the daily card swipe count of each study room through self-service study room devices, aggregate the data monthly and yearly to get the monthly and annual swipe counts for each study room, then sum all annual swipe counts to get the total annual swipe count across all study rooms.
7. Today's swipe entry rate: Calculate today's study room swipe entry rate as (number of study rooms with daily swipe count > 0) / total number of study rooms.

AI搜集汇总

数据集介绍

特点

温州智慧城市书房书房运营数据由温州市图书馆提供，包含158个城市书房的详细运营信息，如座位数、面积、开放时间和刷卡次数等，共1312条数据，每日更新。该数据集用于分析书房分布、运营情况和读者行为，支持文化产业数字化管理和优化布局。