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8 October 2015
Preliminary Results from a Survey of State DOT Website InfrastructureA.J. Million, Ph.D. candidate, School of Information Science & Learning Technologies, University of Missouri
A.J. Million, Doctoral CandidateUniversity of Missouri
School of Information Science & Learning Technologies
October 8, 2015
Preliminary Results from a Survey of State DOT Website Infrastructure
Organizations
Traditionally arranged by bureaucratic hierarchy
Government agenciesDebate about centralization and decentralization of service
provisionTied to politics
Organization can influence service quality
Studied in public administrationStudied by socio-technical researchers
E-government services are not typically examined in this way
Cloud Computing
Refers to a formal computational modelFive essential characteristics
Three service models Four deployment models
More than Google docsDescriptive parts also apply to many online
networksUnderlying concept not new
Rooted in networking of computer systems
Definition
Essential Cloud Computing characteristics are
On-demand serviceBroad network access
Resource poolingRapid elasticity
Measured service
Not all apply to every government websiteMost exhibit multiple traits
Definition Cont.
Cloud service models includeSoftware as a ServicePlatform as a Service
Infrastructure as a Service
Similar to contracting out, but granularVery flexible
May not see if something is Cloud-basedDecentralizes service provision from single
provider
Definition Cont.
Deployment models includePrivate
CommunityHybridPublic
Describes non-Cloud systems tooRefers to where systems are physically
deployed
Why It Matters
Cloud-based approaches tied to broadbandHigh-speed Internet 70%+
Likely to become more so in the futureDecouples government staff from online services they provide
Same can happen with other approaches
Research tends to focus on usability or security
Challenges and benefits of using virtual assetsManagement needed
Potential for greatly increased complexity and problems
Socio-technical Research
Overlap between organizations and technical systems
Think of roads like technologyRequires design and standards
Have to plan for users and people or they won’t work wellInvestment
Managers are responsible for implementation
Study the overlap between spheres
Technology
Social Factors
Possible Benefits
For public administratorsIdentify causes of Web infrastructure adoption to make more
purposefulRemove barriers to best practices
See how innovations spreadUse all of these lessons to build better websites
Value for most transportation librariansOften lack a say
Designed mostly for public communicationLeverage to shape infrastructure in way that helps librarians
Methodology
Online survey sent to three groupsAASHTO Subcommittee on Information Systems
SLA Transportation DivisionTRB Information Services Committee
Collected summer of 2015Used definitions from literature to frame
questionsFollow-up interviews nearly done
Summary of Demographics
Generalizable threshold (N=45) for responsesMore individuals (61) than states
Mean (13.9) is over decade of experience
Mid-sized (4,062) agencies mean by FTESmall (4.2) mean for Web staff
Average site built in 2010Mid-sized (6,366,683) state mean by total
populationMean ($107,116) lane mile spending
13
34
14
Job Titles by Classifi-cation
Execuitive ManagementStaff
0k < 1k 2k 3k 4k 5k 6k 7k 8k +0
1
2
3
4
5
6
7
8
9
10
Agency FTE Counts in Thousands
1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 20160
1
2
3
4
5
6
7
8
9
Sites Built by Year
0
1
2
3
4
5
6
7
8
State Population Counts in Millions0m <1m2m3m4m5m6m7m8m9m10m11m12m13m +
Summary of Infrastructure
Most (n=28) were built in-house Only two known states host their website in
the CloudOn-demand self-service (n=10) is rare
Vast majority reported having (n=40) broad network accessMany (n=23) pool resources
Most (n=23) infrastructure was not rapidly elasticMajority (n=33) measured
Most DOTs take a centralized approachState IT often involved
Summary of Infrastructure
Most infrastructure deployed (n=32) privatelyEven more administer infrastructure (n=37)
in-houseContent usually (n=42) in-house
Combanation In-House0
5
10
15
20
25
30
Site Built Location
Don't Know No Yes0
5
10
15
20
25
30
35
On-Demand Self-Service
Don't Know No Yes0
5
10
15
20
25
30
35
40
45
Broad Network Access
Don't Know No Yes0
5
10
15
20
25
Pooled Resources
Don't Know No Yes0
5
10
15
20
25
Rapid Elasticity
Don't Know No Yes0
5
10
15
20
25
30
35
Measured Service
0
5
10
15
20
25
30
35
Infrastructure Deployment
Don't Know Community Hybrid Private
Contracted-Out In-House Other0
5
10
15
20
25
30
35
40
Infrastructure Administration
In-House Other0
5
10
15
20
25
30
35
40
45
Content Administration
Statistical TestingRank
Trait X2 N Sig. Notes
1 Content Administration 73.20 45 Yes More in-house. No contracted-out.
2 Deployment 68.35 42 Yes Far more private. No public.
3 Broad Network Access 62.80 45 Yes Far more yes.
4Infrastructure Administration
48.53 45 Yes More in-house.
5 Measured Service 34.68 44 Yes Many more yes.
6 How Built 27.46 43 Yes More in-house. No contracted-out.
7 On-Demand Service 23.33 45 Yes Many more no.
8 Pooled Resources 9.73 45 Yes More yes. Many more don’t know.
9 Rapid Elasticity 7.14 44 Yes More no.
Implications for Librarians
Most DOTs are still managing Web systems in-house
Content management is localResource pooling with other agencies very common
Bureaucratic organization commonLimited staff
Designed to control and limit operationsSubject to authority
Software appears to be compartmentalized
Conclusions
Sites redesigned on average every five years
Uncertainty existsJoin Web committees
Encourage site redesigns to help the libraryMake friends with IT staff
Will follow-up with interviews over next month
Will examine barriers to best practices
A.J. Million, Doctoral CandidateUniversity of Missouri
School of Information Science & Learning Technologies
E-Mail: [email protected]
Thank You!
