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Semantic Challenges in Getting Work Done
Published on Dec 19, 20142442 Views
In the new millennium, work involves an increasing amount of tasks that are knowledge-rich and collaborative. We are investigating how semantics can help on both fronts. Our focus is scientific work,
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Chapter list
Semantic Challenges in Getting Work Done00:00
Outline - 103:44
Outline - 204:19
To Dos - 104:35
To Dos - 204:52
To Do Lists05:05
To Do List Management: Opportunities for Interpretation-based Assistance05:50
What Are To Do Items Like: FB app!06:34
What Are To Do Items Like: Office07:59
Opportunities09:03
Agents: Beamer for CALO and Radar - 109:26
Agents: Beamer for CALO and Radar - 210:06
Agents: Beamer for CALO and Radar - 310:29
The Need for Semantics11:22
Paraphrase Game [Chklovski 2005]11:30
Common (Sense) Knowledge11:49
VerbOcean12:28
Managing To Dos through Colleagues: Social Task Networks13:31
Managing To Dos through On-Line Resources14:47
Some Readings15:22
A Semantic Challenge: Managing Personal To Dos16:37
A Semantic Challenge: Coordinating To Dos of Different People16:44
Semantic Challenges in Getting Work Done16:55
Data-Intensive Computing in Science17:29
The Bottleneck is the Process, Not the Data!17:46
Text Extraction in Hanalyzer18:55
Robot Scientist19:42
Intelligent Science Assistants20:00
Timely Analysis of Environmental Data20:13
A Semantic Workflow21:42
Semantic Workflows in Wings22:44
Semantic Components in WINGS23:56
WINGS Specializes Workflow Based on Characteristics of Daily Data24:29
WINGS Dynamically Selects Appropriate Model Based on Daily Sensor Readings25:27
WINGS Workflow Reasoners25:52
Example (Step 1 of 5)27:30
Example (Step 2 of 5)27:53
Example (Step 3 of 5)28:01
Example (Step 4 of 5)28:08
Example (Step 5 of 5)28:19
WINGS Workflow Reasoners: Result28:26
WINGS Automatic Workflow Generation Algorithm28:40
WINGS Automatic Workflow Generation Algorithm30:19
Semantic Process Models31:03
Semantic Descriptions of Software Components in Geosciences31:56
CSDMS Standard Names32:38
Turbosoft Portal33:21
Benefits of Semantic Workflows: 1) Automatic Workflow Elaboration33:53
Benefits of Semantic Workflows: 2) Access to Data Analytics Expertise34:28
Capturing Expertise through Workflows35:23
Capturing Expertise36:04
Benefits of Semantic Workflows: 3) Saving Time Through Reuse36:26
Saving Time through Reuse36:40
Measuring Time Savings with “Reproducibility Maps”37:35
Benefits of Semantic Workflows: 4) Interoperability in a Workflow Ecosystem - 138:09
Benefits of Semantic Workflows: 4) Interoperability in a Workflow Ecosystem - 238:26
Some Readings38:54
A Semantic Challenge: Automatic Paper Generator39:06
A Semantic Challenge: A Web of Semantic Workflows/Processes39:49
Semantic Challenges in Getting Work Done40:23
Collaboration to Develop Workflows40:41
Understanding the “Age of Water”41:27
A New Kind of Collaborative Platform42:52
Organic Data Science44:15
Self-Organization through Task Decomposition45:04
Social Principles for Online Communities45:43
Social Principles: Some Examples46:24
Opening Science: Polymath47:31
Organic Data Science48:15
Self-Organization through Dynamic Task Decomposition48:30
Organic Data Science: Contributors48:51
Data49:03
Models49:10
Workflows49:11
Training Newcomers49:14
What Features Are Used to Manage Tasks?49:23
How Do Users Find Relevant Tasks?49:45
Are Users Collaborating?49:53
What Does the Social Network of Collaborators Look Like?50:14
A Semantic Challenge: Email-less Coordination for Projects50:46
A Semantic Challenge: Open Science Processes51:11
Semantic Challenges in Getting Work Done51:39
“We need bigger glasses and more hands in the water”52:32
Discovery Informatics: Knowledge-Rich Science Infrastructure - 152:55
Discovery Informatics: Knowledge-Rich Science Infrastructure - 253:19
A View from Biomedical Research53:29
A View from Geoscieces53:54
What Might the Future Look Like?54:13
In the Future54:29
Thank you!54:37