دانلود رایگان مقاله انگلیسی روش های هوشمند برای مدیریت داده های جغرافیایی در دولت فدرال ایالات متحده - IEEE 2017

Abstract

in many operations, the US government depends on geospatial data to obtain insights and drive policy making. Federal data are usually pulled from multiple sources, aggregated differently, and formatted in an assortment of standards. Analysts have been overwhelmed by the ample amounts of inconsistent and unstructured data available to them; the main quandary is that they are unable to draw clear conclusions from that data without proper analytics. Moreover, when dealing with geospatial data, the challenge of data management can exacerbate. Geospatial data (including longitudes, latitudes, country codes, addresses and many other forms) are applied at many governmental use-cases such as: census, military operations, natural disasters, economical research, agricultural commodities' production, US trade, and many others. To address such dire needs, this paper introduces a novel method (called G-Fed) for geospatial data management at the federal government. G-Fed provides tools for streaming, validating, aggregating, and presenting data. Furthermore, GFed utilizes the power of big data analytics to drive its processes. Software engineering best practices are also applied within GFed; such as multithreading, security roles, on-demand data tools, standardization, and accessibility. The United States Government Accountability Office (GAO) published a report to point to the matter of federal data management. GAO's report identified fourteen issues that governmental agencies need to solve to overcome their data challenges. Efficiency pressures and federal budget constraints are pushing data implementations towards more automation, extra validation, and higher security. Additionally, the Open Data and the Big Data Initiatives (signed in 2012) have put more pressure on the backs of agencies to make their data (including geospatial) open and available to the public. However, without having state-of-the-art data repositories, it is not possible to address such demands. This paper addresses these issues by presenting a step-by-step set of guidelines. G-Fed aims to help agencies organize geospatial data in a manner that makes it possible to publish, and be provided online to the keen American public. A data repository of public government data is used for experimentation of G-Fed. Experimental results are recorded and presented.

IV. EXPERIMENT AND CONCLUSIONS

The technical sanity of the presented system was tested through being used at a federal agency. However, the most important challenge to its success is user satisfaction – i.e. the satisfaction level of the federal analyst. Due to issues with federal data privacy and confidentiality, data examples are not publishable. However, a detailed experimental survey was conducted to evaluate G-Fed. Although a small number, 32 analysts, filled out the survey; the questions introduced in the survey were comprehensive. The survey included: 1- Do you use maps in your daily tasks? 2- How many maps did you build using G-Fed? 3- How long (on average) did it take you to build one map? 4-What is your overall satisfaction level with unfolding maps? 5- What is your overall satisfaction level regarding G-Fed? Answers for question 1 were: 70% yes, and 30% no. The average answer for question 2 was 11; while it was 5 hours for question 3. Unfolding maps had an overall satisfaction of 62%. The results from question 5 of the survey are presented in Figure 8 below. At government, culture and bureaucracies are major challenges when it comes to adopting new technologies. Most agencies have contracts with software vendors that keeps them hostage to certain tools. The method presented in this paper is ‘the first step’ towards using free, open-source, and vendor-agnostic mapping at the government. The method presented requires much more evaluation and experimentation. However, initial results shown user satisfaction – which is very important in a federal setting.