Predictive tracking for augmented reality. Unpublished doctoral disrtation

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Schön, Donald A., Bish Sanyal, and William J. Mitchell, editors, High Technology and Low-Income Communities: Prospects for the Positive U of Advanced Information Technology. Cambridge MA: MIT Press (1998).
High Technology and Low-Income Communities:持有至到期投资
Prospects for the Positive U of
Advanced Information Technology
Not for circulation or quotation.
7
Information Technologies That Change Relationships between Low-Income Communities and the Public and NonProfit Agencies That Serve Them
Joph Ferreira, Jr.
What are the prospective benefits for rvice providers and rvice recipients of decentralized access t
o information about populations and their needs, rvice systems, and operations? Will growing access to such information be, on the whole, enfranchising for community members, or will it subject them to incread centralized control? This chapter examines particular ways in which information technologies (IT) can make land-u planning (and other aspects of metropolitan evolution) more transparent and understandable to individuals and communities. The point is not that such a u of IT is possible; rather, it is to better understand how it might empower or dinfranchi low-income communities, promote efficiency through improved lf-governance, or further centralize authority in the hands of government and other large-scale data providers.
会计从业资格证书申请表
I begin by focusing on a simple, emingly straightforward example of the u of IT: to computerize inquiries about land u and ownership of land and property in the city. This "simple" example of decentralized data access becomes complicated, however, as soon as the issues of maintenance and updating are addresd. Moreover, various IT strategies for addressing the issues have significantly different impacts on whether or not data access promotes effective decentralization and citizen empowerment. A careful examination of some of the issues and options involved in simple example improves our ability to draw inferences about how access to information can and should foster improved metropolitan governance and broader public participation in urban and regional plan
ning. The real potential for capitalizing on IT to improve governance is not simply a matter of automating government rvices, nor is it a question of whether or not to introduce IT. Shaping planning process, to capitalize on IT, are crucial in improving local governance through reduced bureaucracy and devolution of authority. My reasoning is consistent with recent obrvations in the management literature by Shoshana Zuboff, Tom Peters, and others about IT-driven restructuring of work in U.S. corporations (Peters 1992; Zuboff 1988).
Supporting urban revitalization with data and information systemsrootkit是什么
The role and relevance of information in urban planning is a broad, complex, and much-debated issue (Harris 1989; Innes 1995, Schön 1995). Here I focus on a few practices (of data gathering and analysis) that are common in urban revitalization, concentrating on how the design and implementation of a metropolitan area's information infrastructure can affect the ufulness of such practices to constituencies typically involved in urban revitalization.
Urban planning can be about the public investment, authorization, and support for improved infrastructure (roads, transit, water and wer, etc.), and for other public works and rvices (parks, buildings, public housing, garbage collection, job training, public safety, health care, etc.). It can also
be about the regulatory process that t, monitor, and enforce land-u and zoning regulations, environmental controls, economic development incentives, design guidelines, and the like. Land-u functions-the focus of this chapter-are typically undertaken by institutions that exist in different ctors (public, private, and nonprofit) and at different levels of government (federal, state, metropolitan, city, and neighborhood). In Boston, for example, the Boston Redevelopment Authority (BRA) plays a key role in land-u planning. It is usually responsible for planning studies of major real estate investment projects such as Government Center, the Prudential Center complex, and more recently, the controversial "megaplex" proposals to develop a convention center and related commercial and sports facilities in South B oston. But, the Boston Housing Authority (BHA), which owns and manages housing for more than 10 percent of the city's residents, is the lead agency for two Housing and Urban Development (HUD)-financed urban revitalization demonstration programs costing more than $80 million over a five-year period. Neither authority is completely under the mayor's control, nor are they the only citywide agencies with significant authority in land-u planning. Boston's Public Facilities Department (PFD) is responsible for l and and facilities owned by the city (including, for example, abandoned property); it is also heavily involved in Boston's "Empowerment Zone" planning.[1]  Other federal-, state-, and metropolitan-level agencies and authorities are also significant players in urban redevelopment. HUD and the Massachutts Housin
g Finance Agency (MHFA) are major underwriters of subsidized housing in the region; the Massachutts Water Resource Authority (MWRA) is in the midst of multi-billion dollar projects to upgrade the region's water and wer system; and the Central Artery Project is managing the $7 billion decade-long transportation improvement project to sink Boston's Central Artery and build a third harbor tunnel. Also, the Massachutts Bay Transit Authority (MBTA) and related transit and transportation planning agencies have a considerable impact (through their control of transit routes and transportation investment) on the accessibility of inner-city residents to jobs and rvices; and federal and state environmental protection agencies regulate the reu of the many "brownfields"[2] in inner- city areas that have questionable land-u history.
Private agencies are also important in land-u planning. The Metropolitan Boston Housing Partnership (MBHP), a regional nonprofit organization, manages the pass-through of state and federal housing subsidies for more than five thousand houholds. Along with large landlords, community development corporations, neighborhood and church associations, private developers, and the like, such groups reprent significant interests and planning/management capabilities that are vocal, more or less organized to reprent their interests, and likely to grow in size and/or number as federal efforts continue to decentralize control of prog rams for housing, economic development, and social rvices.
To develop new land-u plans and proposals (or to form opinions as new opportunities and proposals surface), all of the agencies typically spend considerable energy rearching and analyzing land u and ownership in the neighborhoods surrounding the sites that are targeted in the plans. This work (along with other related studies) is then ud to develop tables, charts, and maps that summarize patterns of land-u and ownership and that estimate the size and nature of changes in both the physical and socioeconomic environment that are likely to result from one or another of the propod changes in land u.[3] For large proposals with relatively formal review and approval process, the results of this work are typically included in an environmental impact asssment (EIA) report and/or in various related planning reports and documents that critique, amend, or expand upon the EIA. In the ca of large and controversial projects, the public review process can be long and complex; and public (or mandated private) funds are often ud for parate studies and technical reports, so different interest groups can be more evenly balanced as they debate relevant issues and expectations.
The land-u and ownership studies are only one part of a complex land-u planning process, and their effects on urban revitalization are indirect. Nevertheless, they help us explore the planning us of emerging computing technologies, becau they show how unexpected difficulties can ari in a s
eemingly simple data-processing tting. And, the difficulties highlight a generic issue. Much urban planning focus on understanding places and spatial relationships. Computing technologies have only recently had the horpower and computer graphics tools to track, digest, and visualize complex urban ttings. But to understand the plans and build connsus on action, we need to integrate and reinterpret many data sources now disperd among agencies and groups that are administratively isolated and focud on different issues and goals. Moreover, they often u different accounting systems to name, measure, and value urban activity.
Although I am optimistic about our learning to deal with the difficulties, the devil is in the details. In forecasting the impacts of computing technologies, it is often easy to take for granted elementary operations that bog down when they assume the scale and complexity needed to address real-world ttings. This is especially true if, as I believe, the important benefits of data-processing systems for urban planning are not so much in gaining access to detailed urban data, but in having decentralized access in a way that allows meaningful dialogue as part of an ongoing planning process of design, discussion, and connsus building across many diver and relatively autonomous groups. With this in mind, I examine how Boston's parcel databa is ud to identify and categorize land-u and ownership patterns. I then discuss how emerging information technologies might assist us in the development of improved planning for urban revitalization.
倒立怎么练
Rearching land-u and ownership patterns
As suggested earlier, many neighborhood planning activities-from economic development studies and urban revitalization projects to community organizing, community development corporations (CDC) development, and site planning-begin with a study of patterns of land u and ownership. In the old days this meant spending considerable time in the Asssor's Office and at the Registry of Deeds. Today, most parcel ownership and land-u records are computerized, so that information can be obtained by arching digital databas for a parcel's address, owner name, and the like. A sample of such parcel data for one-to-three family residential housing in East Boston is shown in table 7.1.[4] The address and owner names are shown for veral dozen residential parcels, along with their lot sizes and the February 1, 1996, assd values for the land and buildings. In many U.S. cities and counties electronic access to such parcel data is provided from terminals in a limited number of
government offices through the u of databa applications. The allow the ur to lect from a limited t of text-bad inquiry "screens" in order to find and display information about a single parcel. Providing citizens with direct access to the terminals in government offices became relatively common during the 1980s. More recently, some cities and counties in the United States ha
ve begun to provide more flexible and widespread access to parcel data through u of the Internet or CD-ROM distribution and, in recent months, through map-bad interfaces that make it easy to identify relevant properties and compare the characteristics of neighboring properties.[5 ]
Table 7.1. Sample Parcel Data for Residential Housing in East Boston.
PARCEL_ID  OWNER                NO  STREET      USE  LANDVAL  BUILDVA  LOTSIZE
(dollars)(dollars)(sq. ft.)
---------- -------------------- ---- ------------- ---  -------  -------  -------
010******* PASCUCCI CARLO      105A PUTNAM ST    R3  39400    55500    1,150
010******* MASTRORILLO ANGELO P 197  LEXINGTON ST  R3  39400    59600    1,150
010******* HASELTON PETER      199  LEXINGTON ST  R3  39400    48400    1,150
010******* DILLON KELLEY A      201  LEXINGTON ST  R3  39400    73400    1,150
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010******* DIGIROLAMO JOHN F    203  LEXINGTON ST  R2  40900    73700    2,010
010******* BOTTE FRANK A        205  LEXINGTON ST  R3  41600    65100    2,500
010******* PORCELLA RACHELA    209  LEXINGTON ST  R3  41600    79700    2,500
010******* CIOTO ROBERT        245H LEXINGTON ST  R1  39200    37900    1,238
暮光之城4破晓下什么时候上映
010******* CAHILL STEPHEN F    245  LEXINGTON ST  R3  41200    72300    2,250
010******* MIANO MARIA ETAL    247  LEXINGTON ST  R3  39800    54300    1,838
010******* SHEA RAFFAELA        249  LEXINGTON ST  R3  40100    67800    1,835
010******* CARUSO SYLVIA HELEN  31  PRESCOTT ST  R1  39300    42700    1,263
010******* PATTI RALPH ETAL      33  PRESCOTT ST  R1  39700    70000    1,650
010******* MELE ANTHONY          35  PRESCOTT ST  R2  39700    68400    1,650
010******* STEWART ROBERT        37  PRESCOTT ST  R3  39600    87900    1,700
010******* SLOWEY JAMES J      252  PRINCETON ST  R3  41600    95300    2,500
010******* BOSSI MICHAEL ETAL  250  PRINCETON ST  R3  41600    99200    2,500
010******* TONTODONATO SANDRA M 248  PRINCETON ST  R1  41600    61900    2,500
010******* MARSIGLIA MARILYN G  246  PRINCETON ST  R1  41600    43100    2,500
010******* CAPO JOHN A & MARY B 244  PRINCETON ST  R2  41600    61200    2,500
Source: Boston Asssing Office data from February 1, 1996.
Parcel Records for Boston, Massachutts.
Compared with poring over printed records of parcel information, electronic access speeds up rearch into land u and ownership. This is especially true now that Internet or CD-ROM access can run queries from a desktop compu ter (rather than a customized dial-up terminal) so that the results can be "cut-and-pasted" into the neighborhood planner's spreadsheet or report. The latest databa technologies and mapping software enable urs to construct spatial and textual queries; find, map, and aggregate significant amounts of digested parcel data; and download the data to the desktop in ur-determined formats that become local tables, maps, and spreadsheets.
Using IT to accelerate the process of rearching land u and ownership is a typical example of enhanced efficiency through IT automation. But, this "speed-up" effect is only the most obvious of the possible impacts we might imagine; and, as it turns out, it may not make much of a dent in the considerable amount of time th at our prototypical neighborhood planner must spend studying land u and ownership.[6] We shall e why in the following two ctions. In subquent ctions, I shall suggest how computerizing parcel records might result in a deeper restructuring of neighborhood planning activities.
Exploring Land Ownership Patterns
A typical land- u and ownership study might examine in detail the records for a few hundred to perhaps a thousand parcels. Boston has approximately 138,000 parcels distributed among 16 primary neighborhoods, 22 political wards, 64 sub-neighborhoods, and about 4,500 city blocks.[7] Hence, a typical land-u and ownership study might focus on an area smaller than a BRA sub-neighborhood, one that ranges from a few dozen to a hundred blocks. To explore the characteristics of computerized parcel records, however, we need not limit ourlves to a sub-neighborhood. Since we have access to a "snapshot" of 1996 Boston parcel records stored on a fast network rver with relational databa management tools, we can explore land ownership patterns by sorting, aggregati
ng, and summarizing the parcel data for all of Boston.[8] By doing so, it will be easier to spot data ambiguities and problems that might have an impact on the accuracy and generality of a small area study.
For example, table 7.2 lists the owners of the largest amounts of residential property throughout Boston. The listing is the output of a query written in Structured Query Language (SQL), which has become the lingua franca of databa interoperability.[9] For each unique owner name in the official records, the query counts the number of parcels owned and sums the total lot size and the total assd value.[10] Since we have been discussing neighborhood planning, we focus only on tho 80,842 parcels zoned for residential u (that is, tho with a land-u classification code beginning with "R").[11] Of the 80,842 residential parcels, 3,213 were owned by the top-20 owners shown in table 7.2.that girl什么意思
Table 7.2. Residential Holdings of the Largest Boston Property Owners (using "official" owner names as of February 1, 1996).
文胸的英文
OWNER                          PARCELS  TOTVAL_K  ACRES
($ x 1000)
------------------------------ -------- ---------- ---------
CITY OF BOSTON                1,589      506      271.9
CITY OF BOSTON BY FCL            944      168      81.2
考研英语参考书102    7,664        8.3
BOSTON REDEVELOPMENTAUTH          83        0      11.9
CITY OF BOSTON FCL                71        0        4.5
WEST ROX CRUSHED STONE CO        46      883        8.6
BOSTON HOUSING AUTHORITY          37        0        4.5
laundry是什么意思
CITY OF BOSTON MUNICIPAL CP      35        0        3.3
UNITED STATES OF AMERICA          35        95      12.1
SAMIA LEONARD J                  34    7,135        3.3
MERCURI ANTHONY C                30      547        5.3
ABBEY ST GERMAIN LP              28    9,554        0.8
W ROX CRUSHED STONE CO            27    1,500      41.7
OBRIEN PATRICK                    24    4,012        4.1
HYDE SQUARE CO OP                22    1,929        1.6
RAND MORRIS TRST                  22        91        0.5
FEDERAL HOME LOAN MGT CP          21    2,398        2.2
JONES JOHN C                      21    1,189        1.7
SECRETARY OF HOUSING              21    1,651        2.5
TODESCA CHARLES ETAL              21      456        2.5
A look at the owners' names in table 7.2 suggests that a problem must be solved in order to make go
od u of this computerized listing of the official parcel records. It is not surprising to find that the city of Boston owns most of the parcels. But the city is also cond, fourth, fifth, venth, and eighth in this top-20 listing. The BY FCL in CITY OF BOSTON BY FCL stands for "by foreclosure" and reprents
foreclosures for nonpayment of taxes. Seven hundred forty-four such parcels are listed, but another venty-one parcels list "CITY OF BOSTON BY FCL" as the owner and are presumably more of the same. The BRA, the BHA, and the CITY OF BOSTON MUNICIPAL CP are also among the top-20 residential landowners and should probably be treated as municipal ownership in any land ownership study. Note also that one hundred and two residential parcels have the owner name missing and that the UNITED STATES OF AMERICA, the FEDERAL HOME LOAN MGT CP, and the SECRETARY OF HOUSING make the top-20 owner list. Almost all of the U.S.-owned parcels are on the Stony Brook Rervation in Hyde Park, whereas th e Federal Home Loan and Secretary of Housing parcels are spread around town and probably reprent foreclod residential property owned (as of February 1996) by the Federal Home Loan Mortgage Corporation and HUD. In all likelihood, the properties should also be treated as "municipal ownership" in a land ownership study aimed, say, at understanding property ownership for the purpo of designing a program of urban revitalization.  Difficulties in Categorizing Owner Names
If the parcel data recorded ownership in a way that matched the needs of such a study, then access to the computerized records through powerful data query tools such as SQL would be especially uful. But variations in spelling and the need to group official names into broader categ ories of ownership complicate our efforts to capitalize on the speed and cross-referencing capabilities of tools for processing digital parcel records. Of cour, spelling errors could be corrected, and we could take steps to categorize ownership. But there are veral ways of making such corrections and categories, and the choice can make more difference for planning and policy analysis purpos than we might at first think.
If the only issue were an occasional spelling error in owner names, then almost any solution would be effective. Occasional errors would not have a big impact on our totals and summary statistics, and we could still save a lot of the legwork involved in chasing down owner names for the bulk of the parcels recorded correctly in the databa. But a clor look at the 1996 parcel databa reveals more than an occasional spelling error or omitted name. The West Roxbury Crushed Stone Company shows up twice in the top-20 list with a total of venty-three parcels of (mostly unusable) residential land. The owner name, WEST ROX CRUSHED STONE CO, is associated with forty-six of the parcels, and the other twenty-ven parcels are recorded under the owner name W ROX CRU
SHED STONE CO. The two spellings might result from different choices about how to abbreviate the long name in order to fit it within the thirty characters allowed in the parcel databa. The databa comes from official "owner of record" information generated when the deed of ownership is recorded. Hence, standardizing the owner names ud to record land ownership would not be an easy task-especially since the "owner" might include multiple individuals, corporations, trusts, and the like.

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