MASA Project - Phase 1

8/16/2019 MASA Project - Phase 1

1/31

MASA Project

Phase 1 - The Crime Stats

1 of 30

MASA Multi-Family Anti-Crime Plan

HPD UCR Crime Stats

Phase 1

October 2015, rev1

Ben Munguia


2/31

MASA Project


2 of 30

“Law enforcement is a public service, and citizens expect a fullaccounting from the police commissioner, police chief, orsheriff concerning the administration of the agency and thestatus of public safety within their jurisdiction.”

FBI Uniform Crime Reporting Handbook 2004


3/31

MASA Project


3 of 30

Contents Summary ...................................................................................................................................... 4

Part I ........................................................................................................................................... 5

I. Quantitative Review of Crime................................................................................................ 7

Table and Image Section ......................................................................................................... 9

Table 1 – Quantity of UCR Part 1 by Offense Type ................................................................ 9

Table 2 – Listing of UCR Part 2 Offense Types ...................................................................... 9

Table 3 - Yearly Rates of UCR Part1 Incidents .................................................................... 10

Chart 1 & Pie 1 - Yearly Rates ............................................................................................ 10

Table 4 – Quantity of Incidents by Premise ......................................................................... 11

Table 5 – Remedial Properties ............................................................................................ 13

Table 6 – Blue Star Certified Properties .............................................................................. 14

Part II ........................................................................................................................................ 15

II. Qualitative Review of Crime Stats ...................................................................................... 16

Table and Image Section ....................................................................................................... 18

Table 7 – Overview of Downloaded Records ....................................................................... 18

Pie 2 – UCR Part 1 vs Part 2 ................................................................................................ 18

Table 8 – Samples of Data Errors ........................................................................................ 19

Diagram 1 - MSExcel Only Model ....................................................................................... 20

Diagram 2 - MSAccess Only Model ..................................................................................... 20

Diagram 3 - Effecient Model .............................................................................................. 20

Diagram 4 – User Friendly Models ...................................................................................... 21

Screen Print 1 - Standard XLS Dataset in MSExcel .............................................................. 22

Screen Print 2 - Standard XLS Dataset in MSAccess ............................................................ 23

Screen Print 3 - User Friendly XLS Dataset in MSExcel ........................................................ 24

Screen Print 4 - User Friendly XLS Dataset in MSAccess ..................................................... 25

Screen Print 5 - User Friendly XLS Dataset in Excel Viewer ................................................. 26

Screen Print 6 - User Friendly XLS Dataset in Libre Office .................................................. 27

Screen Print 7 - User Friendly XLS Dataset in Google Docs ................................................. 28

Screen Print 8 - User Friendly XLS Dataset in Excel Online ................................................. 29

End of Presentation .............................................................................. Error Bookmark not defined.


4/31

MASA Project


4 of 30

Summary

Background: From the perspective of a citizen, the crime stats provide vital information that helps usdetermine what the levels of crime are and where.

For example, the stats play a vital role as to how much a tenant is willing to tolerate or risk on amulti-family property they are considering moving to. The stats also have an impact on theapartment business, per se, because they are one of the methods that rate the quality of itsenvironment.

Some of the issues I discovered during my research, as described in Phase 0, is that there is avariances between the law enforcement agencies as to how much and what kind of data is provided tothe public.

For example, I discovered that “transparency” varied between the law enforcement agencies. Clearly,it is a determinant that can hinder or empower the citizen with vital information in becoming a victimand or a statistic or avoiding that fate.

While federal law dictates the provisioning of UCR crime stats, the law does not dictate the provisioning of the crime stats to the general public. And when the crime stats are provided to the public, there is no federal law that mandates what data will be released or not.

Additionally there is a variance as to how this data is provided and its format which also affects theusability and accessiability of the data.

Lastly, citizens may request additional or specific crime stat data via Open Records. However, theLEA’s can continue to utilize discretionary authority and limit what they will release – their rationale

being a need to protect the privacy of either the victim or the criminals.

Questions: Are HPD’s Crime Stats provided as a convenience or for informational purposes or arethey a valid anti-crime methodology? Why are citizens and business’s not utilizing the HPD crimestats?

Solution : A critical analysis was executed on HPD’s Crime Stats and I have provided the resultsherein, as a two-part report.

Part 1 – The Quantitative Review of the HPD Crime Stats

Part 2 – The Qaultitative Review of the HPD Crime Stats, This section pertains to the qualityof the data that was utilized for Part 1.


5/31

MASA Project


5 of 30

Conclusion :

It was very disappointed with HPD crime stats, in part because I had to use advance database

technology to ascertain the information I needed from the data. As such, while the provision ofcrime stats to the public may be a noble effort, it would be fair to say that 99.9 % of Houstonianscannot do anything with the data as provided at this time.

Therefore, HPD’s claims that citizens are not meeting them halfway, is not exactly true. The crimestats need to evolve and become a anti-crime methodology. Like with Blue Star, citizens should beable to know which properties are safer than other and to invest their earning and livelihood in those

businesses.Part I


6/31

MASA Project


6 of 30


7/31

MASA Project


7 of 30

I. Quantitative Review of Crime

A. This analysis examines the level and scope of the incidents of crime in Houston, withemphasis of those occurrences on the multi-family properties, and to justify theimplementation of the MASA guide, a make-safe multi-family anti-crime guide

B. The scope of this report:1. Is limited to HPD statistical data between January 01, 2012 and Jun 30, 2015.2. Is limited to specific crimes as defined as UCR Part 1, (see Table 1).3. Does not contain data for individual properties.4. Will contain an acceptable margin of error.

C. The results from the HPD statistical data are as follows:1. Within the 40 month period, 401,590 incidents occurred in Houston, (see Table

1).2. Within the 40 month period, 98,316 incidents occurred among the 4,620 multi-

family properties 1 , (see Table 4).3. An average of 21.3 incidents occurred per month per multifamily property.

D. The above results show that as the yearly “amount” of crime in Houston varies, theyearly “rate” of crime for multi-family properties is consistent (see Table 3).Therefore there is a positive correlation between the amount of crime and multi-family properties. It might appear that there is a causal link between crime andproperties of high density populations.

E. However, not all properties have similar rates of criminal activities. As indicated inTable 5 there are 45 properties flagged as Remedial because their levels of crime arehigher than the thousands of other properties. But properties as those in Table 6should have criminal activities lower than the thousands of other properties.

F. What the above proves is that while the rate of crime is consistent for multi-familyproperties as a whole, the amount of crime varies for multi-family propertiesindividually. Therefore, there is a negative correlation between crime and the multi-

family property because it appears that there is a causal link between crime and theenvironment of the multifamily property.

G. Environments are multi dimensional and can be characterized by elements such asphysical, economic, technical, structured, natural, social, etc..,. Environments thatlack integrity are commodious to the criminal element of "Opportunity" which is

1 HCAD. "Open Records Request Wo#15-3678." Message to the author. 08 Sept. 2015. E-mail. Number of activeaccounts coded to the CoH (J/C 061) and that are listed as B1 (Apts) is 4,509 and B4 (Condos) is 111.


8/31

MASA Project


8 of 30

conducive to crime; accordingly, multi-family properties are characterized by theireconomic, physical and social environments, and unfortunately by their levels ofcrime as well.

H. A strategy known as CPTED is an approach to eliminate criminal activities byeliminating “Opportunity” from the physical environment. This anti-crime strategy istaught by HPD via its Blue Star Certification Program for multi-family properties.

I. However, the CPTED and the Blue Star program have limitations such as:1. Only .028% of the 4,620 multifamily properties are Blue Star certified, (see

Table5).2. CPTED is not a 100% crime preventative because crime adapts and evolves to

changes in the environment.3. Blue Star is not provided to Remedial’s although these properties are most in

need of knowledge and not the certification.4. CPTED concepts are limited to the physical environments.

J. The MASA Guide 1 is a multi-dimensional approach to reduce the elements of“Opportunity” and “Offender” of the Crime Triangle, from both the physical andsocial environments of multi-family properties, respectively.

K. In conclusion, HPD Chief McClelland believes in Robert Peel’s seventh principle,which states, “ The police are the public, and the public are the police 2 .Subsequently, until more is done to engage and guide the people with the advantageof knowledge and the understandings of crime, communications and community, thepublic is at a disadvantage.

2 Chief McClelland, City of Houston Police Department. Chief of Police Discusses HPD’s Role in Working with Media,Community . UHCLTheSignal.com . The Signal Newspaper, 2 Mar. 2015. Web. 1 Sept. 2015.


9/31

MASA Project


9 of 30

Table and Image Section

The UCR Program collects data about Part I offenses in order to measure the level and scope of crimeoccurring throughout the Nation. The Program’s founders chose these offenses because they areserious crimes, they occur with regularity in all areas of the country, and they are likely to be reported

to police.

Table 1 – Quantity of UCR Part 1 by Offense Typefor Houston Texas

Year: 2012 2013 2014- 3 2015 -4

No of Months: 12 % 12 % 10 % 6 %

Offense Type:

Aggravated Assault 10,108 8.1 9,131 7.1 6,460 7.1 4,316 7.6

Auto Theft 12,449 10 12,990 10.1 9,937 10.9 6,386 11.2

Arson 0 0 0 0 0 0 0 0

Burglary 26,169 20.9 23,550 18.3 17,616 19.3 9,465 16.6

Murder 198 .2 206 .2 140 .2 124 .2

Rape 599 .5 574 .4 506 .6 367 .6

Robbery 9,278 7.4 9,839 7.7 8,276 9.1 4,706 8.3

Theft 66,152 52.9 72,142 56.2 48,313 52.9 31,593 55.5

Sub Totals 124,953 100 128,432 100 91,248 56,957 100

Grand Total 401,590Average per Month 10,413 10,703 9,125 9,493

3

Table 2 – Listing of UCR Part 2 Offense Types

Other assaults (simple) Gambling

Forgery and counterfeiting Offenses against the family and children

Fraud Driving under the influence

Embezzlement Liquor laws

Stolen property; buying, receiving, possessing Drunkenness

Vandalism Disorderly conduct

Weapons; carrying, possessing, etc. Suspicion

Prostitution and commercialized vice Curfew and loitering laws (persons under age 18)

Drug abuse violations Runaways (persons under age 18)Sex offenses (except forcible rape, prostitution,and commercialized vice)

Vagrancy

All other offenses ―All violations of state or local laws not specifically identified as Part I or Part IIoffenses, except traffic violations.

3 2014 –June 2014 & July 2014 HPD Crime Stats are excluded due to insufficient data4 2015 – At the time of this analysis, the YTD ended on June 30, 2015


10/31

MASA Project


10 of 30

Chart 1 & Pie 1 - Yearly Rate of Incidents

Table 3 - Yearly Rates of UCR Part1 Incidents

Source: HPD Crime Stats January 2012 - June 2015

YearMths

Total Quantityof Incidents

RatioQuantity onMulti-Family

RatioQuantity

forAll Else

Ratio

2012 12 124,953 100% 32,435 25.9% 92,518 74.0%

2013 12 128,432 100% 31,383 24.4% 97,049 75.5%

2014 -4 10 91,248 100% 21,958 24.0% 69,290 75.9%

2015 -5 6 56,957 100% 12,540 22.0% 44,417 77.9%

G Total 40 401,590 98,316 303,274

Average 100% 24.5% 75.5%

4 Chart 1 & Pie 1 - Yearly Rates

4 2014 – Premise Codes not found in the June 2014 & July 2014 HPD Crime Stats due to RMS transition/upgrade5 2015 – At the time of this report, the YTD ended on June 30, 2015

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

2012 2013 2014 2015

Multi-Family

All Else

2012 2013 2014 -4 2015 -5


11/31

MASA Project


11 of 30

* Multi-Family:ApartmentApartment LaundryApartment Parking LotApartment Rental OfficeCondominiums

Table 4 – Quantity of Incidents by Premise

Incidents Ranked High to LowSource: HPD Crime Stats January 2012 - June 2015

Premise Incidents Rate Premise Incidents Rate

MULTI-FAMILY * 98,316 24.482% AIRPORT TERMINAL 1,576 0.392%RESIDENCE/HOUSE 53,645 13.358% RENTAL STORAGE FACILITY 1,524 0.379%

ROAD/STREET/SIDEWALK 31,445 7.830% VEHICLE/AUTO SALES/LEASE/A 1,511 0.376%

DRIVEWAY 23,360 5.817% BANK/SAVING INSTITUTION * 1,427 0.355%

OTHER PARKING LOT 20,411 5.083% CONSTRUCTION SITE 1,421 0.354%

RESTAURANT/CAFETERIA ** 19,419 4.835% ELECTRONICS STORE, ELECTRIC 1,323 0.329%

GROCERY/SUPERMARKET ** 15,122 3.766% GYM,RECREAT,CLUB HSE,INDR 1,279 0.318%

DEPARTMENT/DISCOUNT STOR 14,772 3.678% AUTO REPAIR 1,189 0.296%

COMMERCIAL PARKING LOT/G 9,125 2.272% LAUNDRY/DRY CLEANERS ** 1,058 0.263%

HOTEL/MOTEL ** 8,782 2.187% WAREHOUSE 1,046 0.260%

OTHER/UNKNOWN 8,380 2.087% BARBER AND BEAUTY SHOPS 987 0.246%

BAR/NIGHT CLUB ** 7,928 1.974% BUS STOP 968 0.241%STRIP BUSINESS CENTER PARKI 7,742 1.928% HIGH SCHOOL 955 0.238%

CONVENIENCE STORE ** 7,657 1.907% VACANT SINGLE OCCUPANCY R 900 0.224%

SERVICE/GAS STATION 7,326 1.824% SEXUALLY ORIENTED ** 650 0.162%

MISC. BUSINESS (NON-SPECIFIC 5,403 1.345% PAWN/RESALE SHOP/FLEA MAR 598 0.149%

MALL ** 4,332 1.079% HIGHWAY/FREEWAY 596 0.148%

SPECIALTY STORE (NON-SPECIF 4,245 1.057% MIDDLE SCHOOL 563 0.140%

COMMERCIAL BUILDING 3,423 0.852% PHYSICIAN'S OFFICE 551 0.137%

CHURCH/SYNAGO/TEMPLE ** 2,767 0.689% FACTORY/MANUFACTURING/I 543 0.135%

GARAGE/CARPORT 2,703 0.673% FIELD/WOODS 541 0.135%

PARKS & RECREATION, ZOO, S 2,672 0.665% ELEMENTARY SCHOOL 530 0.132%

CLOTHING STORE 2,596 0.646% MOBILE HOME 518 0.129%

HOSPITAL ** 2,387 0.594% CAR WASH 502 0.125%

OFFICE BUILDING 2,223 0.554% BUS STATION 454 0.113%

DRUG STORE/MEDICAL SUPPLY 2,176 0.542% LIQUOR STORE ** 454 0.113%

MULTI-PLEX HME(DUPLEX,TRIP 1,973 0.491% SPORTING GOODS/GUN SHOPS 421 0.105%

5

* The Multi-Family premise code is the aggregate of HPD’s Apartment’s & Condo’s premise codes.


12/31

MASA Project


12 of 30

Premise Incidents Rate Premise Incidents Rate

FREEWAY SERVICE ROAD 396 0.099% REHABILITATION CENTER 91 0.023%

VACANT BUILDING (COMMERCI 359 0.089% COMMERCIAL OR TRAINING SCH 85 0.021%

GOVERNMENT/PUBLIC BUILDING 349 0.087% HIGH RISE 85 0.021%

NURSING HOME 338 0.084% VACANT OTHER STRUCTURE (O 76 0.019%

STADIUM/SPRTS ARENA/RACE T 336 0.084% VACANT GROCERY/SUPERMARK 66 0.016%

DAYCARE/CHILD CARE/KINDER 306 0.076% VACANT RESTAURANT 66 0.016%

THEATRES,DINNER THEATERS,A 284 0.071% FIRE STATION 62 0.015%

CHECK CASHING PLACES 278 0.069% BOOK,RECORD,STATIONARY,OF 61 0.015%

LIBRARIES, MUSEUMS 258 0.064% JAIL/PRISON 61 0.015%

MAINTENANCE/BUILDING SERVI 241 0.060% SAVINGS AND LOAN INSTITUTIO 60 0.015%

POOL HALL/GAME ROOM 228 0.057% VIDEO RENTAL & SALES 53 0.013%

PRIVATE SCHOOL 227 0.057% VACANT CHURCH/SYNAGOGUE 41 0.010%

JEWELRY STORES 213 0.053% VACANT INDUSTRIAL/MANUFA 40 0.010%

FURNITURE, APPLIANCES, RADIO 201 0.050% RAILROAD TRACK/RIGHT OF W 38 0.009%

PARK & RIDE TERMINAL 199 0.050% TRAIN TERMINAL 35 0.009%

ALLEY 197 0.049% LIGHT RAIL PLATFORM 34 0.008%

UNIVERSITY/COLLEGE 188 0.047% CREDIT UNION 33 0.008%

VACANT OTHER RESIDENTIAL (A 182 0.045% LAKE/WATERWAY/BAYOU 33 0.008%

BODY SHOP 174 0.043% LIGHT RAIL VEHICLE 29 0.007%

AMUSE. PARK,BOWL. ALLEY,SKA 142 0.035% TOLLWAY 27 0.007%

CONVENTION CENTER/EXHIBIT 141 0.035% VACANT HOTEL/MOTEL/ETC. 25 0.006%

VACANT STORAGE FACILITY (BA 128 0.032% VACANT SCHOOL/COLLEGE 24 0.006%UTILITY COMPANY,ELECTRIC,GA 124 0.031% VACANT GOVERNMENT/PUBLIC 21 0.005%

POLICE STATION 113 0.028% VACANT HOSPITAL 10 0.002%

SOCIAL SERVICES/PUBLIC CHARI 107 0.027% MARINE VEH. SALES,BOATS,SAIL 8 0.002%

ADULT BOOK STORE/NEWSSTAN 102 0.025% CONTRA-FLOW/HOV 5 0.001%

GARDEN SUPPLY, NURSERY, FLO 101 0.025% VACANT BANK 1 0.000%

TOYS,ARTS & CRAFT,MUSICAL,BI 96 0.024% Grand Total 401,593 100%

Table 4 Continued:

** Premise code is an aggregate of the parent code and child code, such as store+store parking lot


13/31

MASA Project


13 of 30

Table 5 – Remedial PropertiesMay 1, 2012‐ April 30, 2013 6

1 Angle Ridge 8600 Sterlingshire 23 Lucy Apts 5203 Lucille2 Atlas Broadway 8400 Broadway St 24 Pecan Villa 4725 N. Main

3 Belarbor 6060 Belarbor 25 Pine Lake Village 1325 Greens

4 Biscayne @ City View 17050 Imperial Valley 26 Plum Creek Apartments 4904 Plum Creek

5 Broadway Square Sec 2 7900 Morley 27 Regency Square 7222 Bellerive

6 Broadway Square Sec 4 8750 Broadway 28 Sedona Square I&II 9755 Court Glen Dr

7 Casa Miranda 12261 Fondren 29 Somerset 8000 Tidwell

8 Chez Orleans 7065 Bellfort 30 South Lawn Palms 7006 Scott

9 Clasa Azul 12600 Brookglade Cir 31 Springfield@City View I&II 17435 Imperial Valley Dr

10 Colonial Arms 3201 Laura Koppe 32 Sunset Valley 6705 Fairway

11 Community Apartments 4001 Yellowstone Blvd 33 The Carlisle 9898 Forum Park Dr

12 Crescent at City View 1100 Langwick 34 The Leader Friendly 5410 Wilmington

13 Crescent City Apartment Home 8501 Broadway St 35 The Thicket 13011 Northborough

14 Crofton Place 9555 Crofton 36 Tierra Del Sol 8000 Cook Rd

15 Emerson House 201 Emerson 37 Tronewood 9222 Lockwood

16 Fairway Apartments 6739 Fairway 38 Villa Americana 5901 Selinsky

17 Green River 9211 Green River 39 Villa De Cancun 9450 Woodfair

18 Gulf Palms 6514 Sloan 40 Villa la jolla 10101 Forum Park Dr

19 Huntington Place 2110 Melbourne 41 Villa Monteray 9445 Concourse Dr

20 Legacy 3905 Lockwood 42 Westwood Two 9560 Deering Dr

21 Leonora Square 7611 Glenview 43 Woodlen Glen 8405 Broadway St

22 Live Oak Bend 1351 Greens 44 Yorkshire Apartments 520 Yorkshire

45 Yorkshire Village 12221 Fleming

6 "Remedial Properties." Apartment Enforcement Unit . HPD, May 2013. Web. Sept. 2015..


14/31

MASA Project


14 of 30

Table 6 – Blue Star Certified PropertiesAs of 2015- 7

1 2125 Yale 34 Holly View 67 Reserve White Oak

2 7 Seventy 35 Huntington Glen 68 Retreat City Park3 Abbey (Briargrove) 36 Idlewood Park 69 Retreat Eldridge

4 Abbey (Eldridge) 37 IMT (Medical Center) 70 Retreat Westchase

5 Aberdeen 38 Jane Cizik Garden Place 71 Retreat Westpark

6 Archstone Toscano 39 Kempwood Hollow 72 Richmond Green

7 Ashford Stancliff Park 40 Kempwood Place 73 Richmond Townehomes

8 Ashford Westchase 41 Kingswood Village 74 Royal Oaks Westchase

9 Ashford Willows Falls 42 Kirby Place 75 Savoy Manor

10 Barcelona 43 Legacy Westchase 76 Spring Shadows

11 Belmont Place / LaFontaine 44 Lodge Spring Shadows 77 Stone Crossing Westchase

12 Belvedere Westchase 45 Lofts Ballpark 78 Stoney Brook

13 Braeburn Village 46 Marquis Downtown Lofts 79 Summer Creek

14 Braeswood Place 47 Marquis Westchase 80 Summerstone

15 Brays Oaks Park 48 Meadowchase 81 Sunset Shadows

16 Brighton Oaks 49 Memorial City 82 Takara So

17 Cambridge Place 50 Memorial Heights 83 Tiffany Square Apartments

18 Camden Holly Springs 51 Meyer Grove 84 Tradewinds (Willowbrook)

19 Camden Oak Crest 52 Midtown Arbor Place 85 Turtle Point

20 Camden Park 53 Midtown Grove 86 Vanderbilt Lodge

21 Camden Stonebridge 54 Mirabella Galleria 87 Ventura Lofts

22 Camden Vanderbilt 55 North Park 88 Villa del Prado

23 Carrington Court 56 Northline 89 Villas Coronado

24 Catalina 57 Oaks Moritz 90 Wallingford

25 Central Park 58 Parkway & Parkgreen 91 Walnut Terrace

26 Chestnut Hill 59 Pathway 92 Water Mill

27 City View Lofts 60 Pine Arbor 93 West End Boutique

28 Edison 61 Plaza Westchase 94 Westchase Creek

29 Enclave Cypress Park 62 Portico West 8 95 Westchase Forest

30 Fox Hall 63 Premier on Woodfair 96 Westward Square

31 Foxboro 64 Reserve Braesforest 97 Woodtrail

32 Gramercy Park 65 Reserve Creekbend

33 Hidden Park 66 Reserve Garden Oaks

7 "Blue Certified Properties." Apartment Enforcement Unit . HPD, May 2015. Web. Sept. 2015..


15/31

MASA Project


15 of 30

Part II


16/31

MASA Project


16 of 30

II. Qualitative Review of Crime Stats

A. Introduction: This is a review on the quality of the information that is provided by

the HPD Crime Stats Webpage8

. Specific issues and suggestions are provided belowin order to improve the integrity of the information and for the creation of a userfriendly and quality experience to the public.

B. Respectively, 40 months of crime stats were downloaded that contained 448,319records from HPD’s RMS. However, only 401,590 of those records were suitable foruse for the Quantitative Analysis in Part 1 of this presentation.

C. Issue 1 - Of the 448,319 records, 46,729 were disqualified due to missing andinaccurate data. Table 7 summarizes these types of records and Table 8 provides a

sampling of the unacceptable data. The industry refers to these occurrences as“Computer Glitches” or “Garbage in, Garbage out”. Suggestion: The datasets shouldbe cleaned up before making them available for public inspection,

D. Issue 2 - The webpage provides no information regarding the particulars of thecrime stats, such as what will we see, where they came from, how to handle orinterpret records that are incomplete or out of place. Suggestion: Webpage shouldbe more informative.

E. Issue 3 - The webpage cites the following: “You must have Microsoft Access or

Microsoft Excel installed on your computer in order to view these files ”. However,the citation is inaccurate and raises questions as to why the statement was made inthe first place. Diagram 1 and Diagram 2 are visual representation the mandatedmodels inferred by the citation. However, the fact is that people “do not require” theproprietary and expensive software installed on their computers to view thesedatasets. As shown in Diagram 4 there is plenty of software available that canaccess the crime stats datasets in their Microsoft file formats. Suggestion: Webpageshould be more accurate and less restrictive and intimidating.

F. Issue 4 - The webpage provides duplicated datasets each as a .mdb and a .xls file

format. However, by providing datasets in 2 file formats only furthers the misguidedperceptions as referenced by Diagram 1 and Diagram 2. The fact is that only onefile type is necessary and can be used by both MSExcel and MSAccess, asrepresented in Diagram 3. Suggestion: The webpage should be “lean and mean”.

8 "UCR Data by Street." Houston Police Department - Crime Statistics . HPD Public Affairs, 2015. Web. Sept. 2015..


17/31

MASA Project


17 of 30

G. Issue 5 - All datasets should be formatted to ready them for quick use uponopening. Screen Print 1 shows a typical unformatted dataset as it appears whenviewed with the MSExcel spreadsheet program. However, as shown in Screen Print 3a formatted dataset with filtering pre-enabled, is a much improved version becausethey are ready to provide results to the user. As shown in Screen Prints 3 through 8,pre-formatted datasets are perfectly acceptable by other software. And the moreadvanced software is engineered to ignore formatting, as shown in Screen Print 2.Pre-formatting a dataset requires approximately 2 minutes (or 20 seconds viamacro). Suggestion: Clean up and format the datasets before releasing them to thepublic. By making the datasets smarter they will be user-friendly especially tothose persons of limited means and or computer experience.

H. Issue 6 - The webpage describes datasets as UCR data by “street” and providesstreet numbers in the form of “block ranges”. However, block ranges areambiguous, unless the incidents had occurred in the middle of a street, park, et al..There should be no reason as to why exact block numbers whenever possible shouldnot be provided in the datasets, especially since this information would otherwise beavailable via “Open Records”, TV news and newspapers. Suggestion: Include exactstreet numbers to improve the quality of information necessary for pin pointingcriminal activities.

I. Issue 7 - Crime stats do not contain data on UCR Part 2 offenses. Offenses shownin Table 1 are included in the crime stats but not the offenses in Table 2. Yetthousands of these offense occur with the frequency equally or greater than UCRPart 1 crimes. As shown in Pie 2, the public is not being provided with a completepicture of crime in Houston. Suggestion: There is no benefit with not providing afull account of criminal activities to the public. The inclusion of UCR Part 2 data inthe crime stats should be policy and not the exception. It should not require afederal mandate or agency recommendation to have HPD help its community and itscitizens with keeping us better informed about all crimes occurring in our city.Ambiguity and omission only benefits crime and not the citizens.

J. In conclusion, all that provided and done by HPD is a reflection of themselves. As

such there is room to do better via its Crime Stats Webpage.

K. To improve the quality of the information being disseminated by HPD is necessary inorder to achieve the objective of “Integrity through Integration”. Only then canRobert Peel’s seventh principle 3 be realized.


18/31

MASA Project


18 of 30

Table and Image Section

The information below is a summary overview of the errors discovered during the analysis

phase of the 40 datasets of stats downloaded. Column 1 describes the records. Column 2summarizes the quantity of the records found. And Column 3 provides the locations inTable 6 with examples of the errors.

Table 7 – Overview of Downloaded Records

Record TypeNumber of

RecordsCell References in Table 6

Records downloaded 448,319 C2 → C448320

Disqualified for improper dates - 1,977 C2 → C1976

Disqualified for improper premise codes -33,356 G5, G12

Disqualified for duplication -12,249 C3, C4

Disqualified for other improper data. - 853 C5, G5, G19

Records Qualified for the Qualitative Analysis 401,590 C401591 → C448320

Pie 2 – UCR Part 1 vs Part 2

27.58%

72.41%

UCR Part 1 Type CrimesSee Table 1

UCR Part 2 Type CrimesSee Table 2


19/31

MASA Project


19 of 30

A B C D E F G H I J

1 Year Month Date Hour OffenseType Beat Premise BlockRange StreetName StreetType

2 2014 9 9/8/1914 07 Burglary 24C60 Restaurant or Cafeteria 12700-12799 LAKE HOUSTON PKWY

3 2014 10 11/2/1914 03 Burglary 18F60 Miscellaneous Business (Non-Specific) 8800-8899 BELLAIRE BLVD

4 2014 10 11/2/1914 03 Burglary 18F60 Miscellaneous Business (Non-Specific) 8800-8899 BELLAIRE BLVD

5 2014 12 12/3/1914 19 Auto Theft 12D20 12800-12899 GULF FWY

6 2015 1 1/5/1915 22 Theft 3B10 Other Parking Lot 3200-3299 MANGUM RD 180 - 7 2015 1 1/14/1915 23 Auto Theft 5F10 Apartment Parking Lot 7000-7099 WESTVIEW DR

8 2015 4 4/24/1915 07 Burglary 1A20 Office Building 3100-3199 SMITH - 9 2015 1 12/15/1915 15 Burglary 9C30 Commercial Building 10200-10299 LOOP -

10 2015 2 12/25/1915 17 Theft 6B30 Apartment 6400-6499 ANTOINE DR

11 2015 6 6/24/1916 12 Theft 4F20 Road, Street, or Sidewalk 9800-9899 KNOBOAK DR

12 2014 6 6/28/1920 16 Theft 17E40 12100-12199 FAIRMEADOW DR

13 2014 12 12/9/1924 11 Theft UNK Strip Business Center Parking Lot 11000-11099 EASTEX FWY

14 2013 4 2/2/1963 13 Theft 10H40 09R 3800-3899 MAIN ST 15 2015 3 3/23/1964 19 Rape 13D20 Residence or House 6600-6699 SOUTHBROOK DR

16 2014 9 2/3/1971 06 Theft 1A10 Residence or House 1200-1299 TRAVIS -

17 2015 2 1/28/1972 19 Burglary 7C10 Apartment 1400-1499 SOLO -

18 2013 11 6/1/1972 00 Rape 12D50 20R 16400-16499 BROOKVILLA DR

19 2013 8 7/15/1972 20 Burglary 14D30 --- 5300-5399 NORTHRIDGE DR

20 2014 1 5/1/1973 23 Rape 8C60 20R 6500-6599 MOHAWK ST

21 2012 11 11/16/1973 13 Theft 1A30 210 2500-2599 RICHMOND AVE

22 2012 5 5/17/1975 15 Robbery 4F30 20A 1800-1899 BARKER CYPRESS RD

23 2015 6 1/8/1980 23 Burglary 5F30 Apartment 8000-8099 ELLINGER LN

24 2015 1 1/17/1980 14 Theft 3B10 Apartment Parking Lot 4900-4999 DACOMA ST

25 2015 2 4/29/1980 23 Burglary 15E20 Residence or House 5900-5999 BELROSE DR

Table 8 – Samples of Data Errors

Source: HPD Crime Stats January 01, 2012 – June 30, 2015

The table below contains a sample of 25 records of the 448,319 downloaded records. Columns A and B were added for normalization afterdownloading the initial Dataset. However, Data in Columns B-J (and column L, not shown) are from HPD’s Records Management System.Columns A-B contains the Year and Month for the source file of the record. Please refer to Table 5 Colum 3 for locations of examplesbelow .


20/31

MASA Project


20 of 30

Data Flow Models

The visual representations below are currently inferred on the Crime Stats webpage asrequirements for processing the downloadable datasets.

Diagram 1 - MSExcel Only Model Diagram 2 - MSAccess Only Model

Alternative Model

The representation below is a more efficient methodology and produces the exactoutput as the models above. Less-is-best and mdb’s are inessential.

Diagram 3 - Effecient Model

Also see Screen Print 1 Also see Screen Print 2

Same as Screen Print 2 Same as Screen Print 1


21/31

MASA Project


21 of 30

Diagram 4 – User Friendly Models

The representation below demonstrates the available methodologies for accessing thedata from the datasets.

At the center of the hub is the standard XLS dataset showing the additional methods foraccessing and processing the crime stats. Additionally by pre-formatting datasets foruser friendliness, a spreadsheet software is more than adequate to display desiredresults for the novice computer user.

Pre-formatted datasets are easily viewable on Microsoft and non-Microsoft software, asshown in Screen Prints 2 through 9.


22/31

MASA Project


22 of 30

Screen Print 1 - Standard XLS Dataset in MSExcel

The image is a screen printout of what a typical unformatted dataset in xls appears when viewing with the MS Excel Spreadsheet software.


23/31

MASA Project


23 of 30

Screen Print 2 - Standard XLS Dataset in MSAccess

The image is a screen printout of what a typical unformatted dataset in xls appears when viewing with the MS Access Database software.The first column “ID” is an option the software provides when importing or linking the xls dataset. Otherwise the table below is exactly thesame as the table in Screen Print 1 .


24/31

MASA Project


24 of 30

Screen Print 3 - User Friendly XLS Dataset in MSExcel

The image is a screen printout of what a pre-formatted crime stat dataset in xls appears when viewing with the MS Excel Spreadsheetsoftware. The table has user instructions at the top and the auto filtering has been pre-enabled and the gridlines are disabled. Filtering is asimplified way to quickly drill down to specific records from the thousands that are provided by datasets.


25/31

MASA Project


25 of 30

Screen Print 4 - User Friendly XLS Dataset in MSAccess

The image is a screen printout of what a pre-formatted crime stat dataset in xls appears when viewing with the MS Access Databasesoftware. As shown, pre-formatting is automatically ignored by the program and the presentation is exactly the same as Screen Print 2


26/31

MASA Project


26 of 30

Screen Print 5 - User Friendly XLS Dataset in Excel Viewer

The image is a screen printout of what a pre-formatted crime stat dataset in xls appears when viewing with the Free MS Excel Viewer(version 2003). The free viewer has no power, like a spreadsheet program. However, any dataset can be highly informative on a powerlessviewer, but only if it is pre-formatted and filtering is pre-enabled. Below, records are being selected by street name(s).


27/31

MASA Project


27 of 30

Screen Print 6 - User Friendly XLS Dataset in Libre Office

The image is a screen printout of what a pre-formatted crime stat dataset in xls appears when viewing with the spreadsheet module of theFree Libre Office. Below, records are being filtered. However, the user can remove all formatting and process the data with the powerprovided by the spreadsheet.


28/31

MASA Project


28 of 30

Screen Print 7 - User Friendly XLS Dataset in Google Docs

The image is a screen printout of what a pre-formatted crime stat dataset in xls appears when viewing with the Free Google Docs OnlineSpreadsheet. Below are records being filtered by street name(s)


29/31

MASA Project


29 of 30

Screen Print 8 - User Friendly XLS Dataset in Excel Online

The image is a screen printout of what a pre-formatted crime stat dataset in xls appears when viewing with the Free MS Excel OnlineSpreadsheet via the browser. Similarly viewed via the Free Excel App for tablets. After the menu option “create t able” is engaged, the filterrows that were set during pre-formatting, will engage. Below are records being filtered by block range(s).


30/31

MASA Project


30 of 30

It is with integrity through integration thatwe can engage and guide them .

Ben Munguia


31/31

MASA Project


Documents

MASA Project - Phase 1