Wage, projection, skill, task, interest, and technology patterns across five library-related occupations, collected from the CareerOneStop API on 2026-07-28.
Where the roles are, what they pay, and what they require.
Geographic wage distribution and the top-paying states.
The credentials, skills, knowledge, and abilities workers in these roles typically bring.
The software O*NET associates with these jobs. Pick a single role above to also see its day-to-day tasks.
Benchmarks, salary banding, hiring forecasts, and tooling.
Wage distribution by occupation, with a state filter to drill into within-state percentile bands.
State wage paired with projected growth, plus the national outlook.
Credentials current workers hold and the tools you might budget for.
Where the data comes from, how it was cleaned, and what it can and cannot tell you.
What the dataset is, where it came from, and the time window.
Primary source. This data is delivered by an API from CareerOneStop, sponsored by U.S. Department of Labor, Employment and Training Administration
Upstream source. Competency, task, and tools data originate from O*NET OnLine, surfaced through the CareerOneStop API.
Collection date. 2026-07-28.
Occupations. Five O*NET-SOC codes: 25-4031.00, 43-4121.00, 25-4022.00, 25-1082.00, 25-9099.00.
Geographic scope. 54 states and territories.
Known problems in the source data, and how each one is handled.
| File | Rows | Used for |
|---|---|---|
| wages_by_state_2026-07-28.csv | 452 | Wages by state plus national benchmarks (incl. pct10/25/50/75/90) |
| projections_by_state_2026-07-28.csv | 492 | State projections plus repeated U.S. benchmark rows |
| lmi_by_state_2026-07-28.csv | 270 | All analytic columns empty - not used |
| tasks_2026-07-28.csv | 147 | Task scores (data_value); no separate importance field |
| skills_2026-07-28.csv | 140 | Skill importance and level values |
| knowledge_2026-07-28.csv | 132 | Knowledge importance and level values |
| abilities_2026-07-28.csv | 208 | Ability importance and level values |
| tools_and_technology_2026-07-28.csv | 305 | Tools, technologies, hot-tech and in-demand flags |
| interests_2026-07-28.csv | 9 | Occupational interest profiles |
| Issue | Observed | Action taken |
|---|---|---|
| LMI extract | All 270 rows had null avg_annual_wage, career_outlook, and typical_training values. | Excluded from plots; summarized as a data gap. |
| Projection U.S. benchmarks | 270 rows carried a repeated U.S. benchmark in state-scoped records. | Collapsed to 5 unique national rows; kept separate from state rows. |
| Task duplicates | 31 exact duplicate task descriptions in profiles. | Deduplicated on (onet_title, task_description) before ranking tasks. |
| Interest importance field | importance was null in all 9 interest rows. | Interests are collected but not shown anywhere in this dashboard: the importance scores that would rank them are empty for every row. Retained in the extract in case a future collection populates them. |
| Profile table coverage | Tasks, skills, knowledge, abilities, tools, and interests cover 4 of 5 occupations. | Profile sections exclude "Library Workers, All Other" and flag the gap. |
| Year horizon mismatch | State projection rows are 2022-2032; U.S. benchmark rows are 2024-2034. | Surfaced in a caveat callout near projection visuals; not normalized. |
| Data & AI tagging | No native flag in the raw tools-and-tech rows for "this is data or AI work". | Derived an is_data_ai boolean over 29 concepts, matched against each row's NAME (Python, SQL, MySQL, Tableau, Power BI, Stata, SPSS, SAS, Excel, spreadsheet, statistics, analytics, visualization, dashboard, quantitative, GIS, spatial, data mining/warehousing/visualization/analysis, AI, machine learning, deep learning, LLM, generative, neural network), plus three unambiguously analytic O*NET categories and two named exceptions (Microsoft Access, FileMaker Pro). Hardware rows are excluded. The category "Data base user interface and query software" is deliberately NOT whitelisted: it is library catalog and discovery software, and matching it swept in Blackboard, HTTrack, web-clipping utilities and bibliographic catalogs. Tagged 15 occupation-item pairs (15 distinct tools) across the four populated occupations. Counts are an O*NET baseline, not a demand signal. |
| Occupation | Annual wage states | Projection states | Joined states |
|---|---|---|---|
| Library Technicians | 52 | 50 | 50 |
| Library Assistants | 51 | 50 | 50 |
| Librarians and Media Specialists | 52 | 52 | 51 |
| Library Science Teachers | 29 | 30 | 25 |
| Library Workers, All Other | 52 | 40 | 40 |
| Occupation | State count | Min median | Median of medians | Max median | Mean median |
|---|---|---|---|---|---|
| Librarians and Media Specialists | 52 | $42,980 | $63,230 | $100,030 | $67,189 |
| Library Assistants | 51 | $23,110 | $36,130 | $59,390 | $36,272 |
| Library Science Teachers | 29 | $59,920 | $79,460 | $125,640 | $80,406 |
| Library Technicians | 52 | $26,850 | $40,335 | $62,570 | $42,092 |
| Library Workers, All Other | 52 | $24,780 | $50,215 | $83,130 | $50,761 |
O*NET's own markers for tools it considers in demand or newly prominent. These labels come with the source data.
| Occupation | Hot | In-demand | Items |
|---|---|---|---|
| Library Technicians | 11 | 2 | Hot: Adobe Acrobat, Adobe Illustrator, Adobe Photoshop, Microsoft Excel, Microsoft Office software, Microsoft PowerPoint, Microsoft Publisher, Microsoft Windows, Microsoft Word, National Library of Medicine Medline … and 1 more |
| Library Assistants | 10 | 2 | Hot: Adobe Acrobat, Adobe Photoshop, C++, Microsoft Excel, Microsoft Office software, Microsoft Outlook, Microsoft PowerPoint, Microsoft Windows, Recordkeeping software, Word processing software |
| Librarians and Media Specialists | 27 | 2 | Hot: Adobe Acrobat, Adobe Photoshop, Apple iMovie, Autodesk AutoCAD, Extensible hypertext markup language XHTML, Extensible markup language XML, Google Workspace software, Graphics software, Hypertext markup language HTML, JavaScript … and 17 more |
| Library Science Teachers | 15 | 0 | Hot: C++, Extensible markup language XML, Gale Cengage Learning Associations Unlimited, JavaScript, Microsoft Excel, Microsoft Office software, Microsoft Outlook, Microsoft PowerPoint, Microsoft SharePoint, Microsoft Word … and 5 more |
Every tool counted as data or AI work, listed in full. Unlike the flags above, this classification is not part of O*NET — the rule used is described in the cleaning table above.
| Occupation | Data & AI | Tools O*NET lists | % of listed tools | Tagged items |
|---|---|---|---|---|
| Library Technicians | 3 | 45 | 6.7% | FileMaker Pro, Microsoft Access, Microsoft Excel |
| Library Assistants | 2 | 49 | 4.1% | Microsoft Access, Microsoft Excel |
| Librarians and Media Specialists | 6 | 124 | 4.8% | Data visualization software, FileMaker Pro, Microsoft Access, Microsoft Excel, StataCorp Stata, Structured query language SQL |
| Library Science Teachers | 4 | 87 | 4.6% | Database management system software, Microsoft Excel, MySQL, Structured query language SQL |
Each collection adds a point. With several snapshots, this shows how the figures move.