Replication Data for: Group 2 | BARI (Harvard, Northeastern): Expanding Administrative Urban Knowledge with R and Big Data: “Boston Property Assessments FY2018”

I. INTRODUCTION, AND IMPACT OF FINDINGS FOR FUTURE IMPLEMENTATION Outcome: A quantitative ""data-story"" can be fully expressed in qualitative form as a means of expressing the interconnected nature of variables that contribute to a networked understanding to map the constantly evolving modern Urban Landscape. Enhanced allocative, fiscal, political, and social decision making lead to almost immediate positive externalities in terms of the connected urban landscape. Constant constraints of many different forms force decision-makers to make impulsive, rushed, and consequently uninformed decisions that are based merely on presuppositions. Constant construction of pathways between seamlessly unrelated sets of information derived from the existing, historic, and quantifiable data types will bring urban decision makers solution-based and preventative vs. reactive competitive advantage . These *NEW* ""Measures"" that we have calculated and defined only be achieved through the expansion of PUBLIC access to unit-level, which is one of the purposes of publishing reproducible findings for this dataset.II. PURPOSE AND GOAL IN TERMS OF THE CONTRIBUTION TO UNCOVER INSIGHTS THAT HIGHLIGHT THE HOLISTIC FUNCTIONS OF THE CITY AND IMPROVE KNOWLEDGE * Incorporate big data into the study and management of the City of Boston to develop new contextually rich value-added variables through integration of additional administrative records, GIS/geographic data (shape-file/JSON), demographic data etc. * Statistically analyze and explore output generated from the integrated data to uncover correlations that will provide increased confidence levels, understandability, and interpretability in relation to the economy, direct human behavior, government policies/decision making, and the environment. * Use Practical Aggregate Measures to accelerate assimilation of, and to leverage all facets of corresponding applicable data * Finally, meticulously record, interpolate, hypothesize, and upload findings for a continuation of development.-- Replication of Citation Metadata for "Group 2": Dataset Persistent ID: doi:10.7910/DVN/PZCZSF Title: Group 2 Author: Boston Area Research Initiative, BARI (Northeastern University / Harvard University) Charan Konanki, Sai (Northeastern University) Shah, Chaitya (Northeastern University) Jonah, Domenic (Northeastern University) - ORCID: 0000-0002-0212-158