Upgrade to Pro — share decks privately, control downloads, hide ads and more …

The Office Hours Data Conundrum

Avatar for Christina Koch Christina Koch
February 15, 2018
Research
0
170

The Office Hours Data Conundrum

Avatar for Christina Koch

Christina Koch

February 15, 2018
Tweet

More Decks by Christina Koch

See All by Christina Koch
Data Carpentry SQL Introduction
Avatar for Christina Koch christinalk
0
1.3k
A Different Kind of Carpentry
Avatar for Christina Koch christinalk
0
170
Best Practices For All
Avatar for Christina Koch christinalk
0
140
Query Live Database
Avatar for Christina Koch christinalk
0
640
Workshop Development en breve
Avatar for Christina Koch christinalk
0
88
Software Portability
Avatar for Christina Koch christinalk
0
290
Software Licenses and Interpreted Languages
Avatar for Christina Koch christinalk
0
110
Research Computing Taxonomy
Avatar for Christina Koch christinalk
0
210
HTCondor User Tutorial
Avatar for Christina Koch christinalk
0
300

Other Decks in Research

See All in Research
AWSで実現した大規模日本語VLM学習用データセット "MOMIJI" 構築パイプライン/buiding-momiji
Avatar for 開発室Graph studio_graph
2
810
EarthDial: Turning Multi-sensory Earth Observations to Interactive Dialogues
Avatar for SatAI.challenge satai
3
270
投資戦略202508
Avatar for Pragmaworks pw
0
570
まずはここから：Overleaf共同執筆・CopilotでAIコーディング入門・Codespacesで独立環境
Avatar for Yusuke Matsui matsui_528
2
660
[CV勉強会@関東 CVPR2025] VLM自動運転model S4-Driver
Avatar for Shin-kyoto shinkyoto
2
550
カスタマーサクセスの視点からAWS Summitの展示を考える～製品開発で活用できる勘所～
Avatar for モブエンジニア（Masaki Okuda） masakiokuda
2
210
Galileo: Learning Global & Local Features of Many Remote Sensing Modalities
Avatar for SatAI.challenge satai
3
390
アニメにおける宇宙猫ミームとその表現
Avatar for yttrium173340 yttrium173340
0
110
cvpaper.challenge 10年の軌跡 / cvpaper.challenge a decade-long journey
Avatar for gatheluck gatheluck
3
360
CoRL2025速報
Avatar for robotpaper.challenge rpc
1
2.5k
超高速データサイエンス
Avatar for Yusuke Matsui matsui_528
1
170
Mamba-in-Mamba: Centralized Mamba-Cross-Scan in Tokenized Mamba Model for Hyperspectral Image Classification
Avatar for SatAI.challenge satai
3
140

Featured

See All Featured
個人開発の失敗を避けるイケてる考え方 / tips for indie hackers
Avatar for panda_program panda_program
116
20k
GitHub's CSS Performance
Avatar for Jon Rohan jonrohan
1032
470k
Why Our Code Smells
Avatar for Brandon Keepers bkeepers
PRO
340
57k
The Pragmatic Product Professional
Avatar for Laura Van Doore lauravandoore
36
7k
The Straight Up "How To Draw Better" Workshop
Avatar for Dennis Kardys denniskardys
239
140k
Building Flexible Design Systems
Avatar for Yesenia Perez-Cruz yeseniaperezcruz
329
39k
Intergalactic Javascript Robots from Outer Space
Avatar for Vicent Martí tanoku
272
27k
Building Better People: How to give real-time feedback that sticks.
Avatar for Will Jessup wjessup
369
20k
How STYLIGHT went responsive
Avatar for nonsquared nonsquared
100
5.9k
How Fast Is Fast Enough? [PerfNow 2025]
Avatar for Tammy Everts tammyeverts
2
100
Thoughts on Productivity
Avatar for Jon Yablonski jonyablonski
71
4.9k
The Success of Rails: Ensuring Growth for the Next 100 Years
Avatar for Eileen M. Uchitelle eileencodes
46
7.7k

Transcript

  1. { The  Office  Hours   Conundrum Christina  Koch Data  Story

     Slam,  February  2018

  2. This  is  me   (Christina)

  3. My  colleague  Lauren  and  I  work  for  the   Center

     for  High  Throughput  Computing  (CHTC)   as  research  computing  facilitators

  4. { New  accounts,  ongoing  meetings,   and  weekly  office  hours.

    We  meet  with  a  lot   of  people.

  5. { Question How  many  people  do  Christina  and  Lauren  meet

      with  every  month?

  6. Version  1:  Calendar

  7. Version  2:  Form

  8. Version  3:  Sign  In

  9. Success!

  10. { Busiest  Month May:  77  people

  11. { Slowest  Month December:  27  people

  12. None

  13. { What  happened   in  July? Christina  and  Lauren  were

     out  of  the  office   (conferences,  summer  school,  workshops)

  14. { 312 Number  of  people  new  to  CHTC

  15. None

  16. Ñ  Everyone  has  to  deal  with  data Ñ  Sometimes  a

     simple  solution  is  the  best  solution Ñ  Structure  your  data Ñ  Once  you  have  data,  you  can  tell  a  story Lessons  Learned