| Name | Description and usage | Complexity | Specific Req |
| Field Data Collection List (FDCL) | This is a paper book produced annually that includes PMS segmentation and county mileposts, pavement type, percent predominant pavement type, and location references (NJct U54/K15 15.234 which comes from a manually maintained Reference table). It is used by field data collectors, PMS data users, and many people just for the references. | Medium | 9.1.1.1 and 9.1.1.2 |
| Projects (outstanding, submitted, future) | This is a dataset that is constantly maintained that sometimes takes the form of reports, interfaces, forms, and even workflows. The data represents tracking of pavement projects from the time they are candidates, to district selections, to 1R (or other program) selections, to "real" projects (have a number assigned), to let projects, to "open to unrestricted traffic" .... The formats of these reports vary by different users and uses. Note that the data behind these reports comes from many different sources (1R Candidates, District Selections, WinCPMS, Letting Lists, Completed Rehab Form submissions, .... They are used by the project selection processes (1R and 3R), CRF, many of the mapping reports, and Transportation Planning as they update their pavement histories. | High (lots of sources to get to this data) | 10.2 and 10.2.1 |
| Data Collection Maps | This set of GIS maps shows shows the inventory locations to be collected for LCMS/NOS, WHIPAVSAUR, FWD, SKID... vs what has been collected in the current cycle. Basically, this report is showing data collection progress. | Medium | 7.1.2 |
| Data Loaded Maps | This set of GIS maps shows where collected data has been loaded to the appropriate PMS data tables over the inventory as a back drop. Basically, this report is showing data loading progress. | Medium | 7.1.2.1 |
| Candidate Project Lists and Maps | This paper report or dataset (or workflow) which is the results of PMS analysis that indicates candidate project locations and scopes for each of the 6 districts for their consideration | High (lots of sources to get to this data) | 7.1.5 and 7.1.6 |
| District Selection | This (typically comes back as an email with a spreadsheet attachment and) is the district response to the candidate lists that indicates which projects and scopes they selected including the possibility of projects that were not on the candidate list | High (lots of sources to get to this data) | 7.1.5 and 7.1.6 |
| Approved for 402s | This is (typically an email with a spreadsheet attachment and is) the response to the district response that indicates approval by the Chief of Construction and Materials to projects and scopes for a district for a cycle | Low | 3.1 see also (7.1.5, 7.1.6, and 11.1) |
| Candidate Maps | This is a paper map based on the 1R process to show candidate project locations and scheduled projects in each district. They are used by District Staff to help them decide which 1R projects to do in their next cycle. | High (lots of sources to get to this data) | 7.1.5 |
| Action History Table and Maps | This is a paper report and a process that results in a database table that summarizes contiguous roadway segments annually with candidate information, planned project information, past project information, ... | Medium | 7.1.3 |
| Pavement Sandwiches | This can be a paper report or dataset (or interface) and represents a section of roadway and both its action history in the form of what was done when and in the form of what physical pavements exist there now | High (mostly due to aggregation rules and precision concerns) | 7.1.3 |
| Condition Reports (Annual, IKE, State PM dashboard, others?) | These may be paper reports or datasets (or workflows) that simply provide some aggregation of pavement condition data or predicted condition data or work types and amounts accomplished or scheduled to other parts of the Agency | Medium | 11.2 |
| Condition Maps (Roughness, Rutting, Faulting, Transverse Cracking, Joint Distress, Pavement Type, SKID, FWD, Surface Age, ...) | These typically are paper maps showing various pavement condition information | Low | 7.1.4 |
| DQMP Check | This is a paper report that follows the Kansas Pavement Condition Data Collection Quality Management Plan to produce an annual report documenting the quality of the collected data | Medium | 9.1.1.3 |
| KTA data | This can be a paper book or dataset (or interface) produced annually that provides pavement condition data collected by KDOT but for the KTA (and HPMS). It includes roughness, rutting, and faulting following KDOT methods and could include more PMS condition data (transverse cracking, structural data, SKID, ...) . It is used by KTA for input into their PMS and reports. | Low | 11.2 |
| SKID book | This is a paper book generated mostly to facilitate field data collection. The current process to generate this book also creates unique IDs and data record placeholders in existing tables. The book is used by field data collectors to determine where they need to gather friction data. | Medium | 9.1 and 9.1.1.2 |
| SKID map | This is a paper map based on the SKID book to show locations that need to be collected along with some additional details like where projects have just been completed and where there might be construction pending. | Low | 9.1.1.1 See also 7.x |
| FWD map | This is a paper map showing locations to collect FWD based on a list generated by Pavement Evaluation staff. | Low | 9.1.1.1 |
| HPMS report card | This is a paper report following FHWA guidance that uses the HPMS submittal data to check pavement data and summarize condition. The official version of this report will come back from FHWA software, but this version needs to use data in the PMS so that we know the answers before we go through the submittal process. | Medium | 4.1.1.2 |
| Mandli data reports to move from XML and profile to the PMS database | These datasets are the current means of taking the processed LCMS data and using Mandli's Road View Workstation tools to assemble it into attributes (roughness, rutting, faulting, (various forms of ) cracking, ...) at various aggregations (frame, tenths, segments, projects, ...) for import into data tables each year. | High | 9.1.1 |
| DS, CS, PL, report summaries for feeding GASB, TAMP, ACFR, PMs, Auditors, Annual Report) | These may be paper reports or datasets (or workflows) that provide pavement condition data in the forms of Distress State, Condition State, and Performance Level distributions to other parts of the Agency mostly as detail to the more aggregated summaries reported elsewhere | Low | 5.1 for TAMP and 11.2 for all others |
| Widows and Orphans | This can be a paper report or dataset (or interface or workflow) produced regularly (weekly?) that provides analysis of referential integrity (e.g. inventory record with no condition data or vice versa), internal checks (e.g. components of PMSID concat correctly into the PMSID), and logical checks (e.g. scheduled projects have future not past dates). It is used by PMS staff to check the database. | Medium | 21 |
| District Mileage Allotments | This can be a paper report or dataset (or interface or workflow) produced annually as part of the 1R process. It represents the number of miles allocated to each district to target as they select projects from the candidate project lists. Historically, rules have been applied to assign minimum proportions of the projects selected from different categories versus this district total. Those rules helped keep the PMS output and the implementation of projects somewhat in sync. The mileages are used by the Districts when selecting projects and by PMS to check proportions and totals for projects which get selected by each district. | High (lots of process to get to this data) | 3.1 |
| 1R Tour Supplemental Data | This is typically a dataset that summarizes pavement history, traffic, pavement width, NHS, ... for candidate project locations for the field reviews | Low | 11.1 |
| Additional Reports | Note that this list of reports is not exhaustive and that respondants should indicate if they have a limit to the numbers of reports included in their bid so that it does not become a point of contention during implementation. | Varies | 11.2 |