Non-profit geographically constrained locator
| Autor: | James W. McGuffee |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Computer science
business.industry media_common.quotation_subject Social Welfare Crawling Python (programming language) World Wide Web Undergraduate research General Earth and Planetary Sciences Web application Web crawler business Location Citizenship computer General Environmental Science media_common computer.programming_language |
| Zdroj: | ACM SIGCAS Computers and Society. 45:41-41 |
| ISSN: | 0095-2737 |
| DOI: | 10.1145/2809957.2809971 |
| Popis: | There exist numerous non-profit entities and organizations that provide social services to those in need. These organizations may be governmental, secular, parochial, or religious. The services provided may be long term institutionalized support, seasonal or limited time benefits. Beneficiaries of social services may be restricted by age, sex, family status, citizenship, and/or income level. Given this variability, we envisioned the need to create an interactive geographically constrained web based social services client matching system. In this system, a client would enter basic demographic information and the system would return a set of available social services within a specific geographic area. As a first step in trying to create this system, undergraduate student Dan Myers investigated the viability of using Scrapy to crawl and scrape data from the web based on geographic location. Scrapy is an open-source web crawling framework written in Python. Scrapy was chosen because it is open source, widely used, and provides tools for both scraping and crawling [2]. The main focus of Dan Myers' project was to write a web crawler that utilizes regular expressions to extract relevant data from geographically targeted websites. Specifically, Dan's project used Scrapy to find all web mentions of physical addresses in the zip codes of the three most northern counties in Kentucky. The two main tasks for this project were (1) to use Scrapy's spider class to extract street addresses from the chosen zip codes and (2) to create a Scrapy item object to manage the data. This project demonstrated that by using the open source tool Scrapy, the problem of extracting geographically relevant information is faster and easier to manage than previously proposed systems such as the gazetteer approach used in the web-a-where project [1]. The next phase of the project will be undertaken by a team of UR-STEM students in the summer of 2015. At NKU, UR-STEM (which stands for undergraduate research in STEM) is a paid summer research opportunity for students early in their college careers. A goal for this summer's research will be the creation of a fully working prototype of a web based non-profit geographically constrained locator. Depending on the quality of the code produced, the project may be released as the first version of an ongoing open source software project which could, potentially, lead to the creation of an HFOSS (Humanitarian Free and Open Source Software) project whose original programmers are all students [3]. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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