eScience through the Integration of Data and Models: A Biodiversity - PowerPoint PPT Presentation

eScience through the Integration of Data and Models: A Biodiversity Scenario Natalia Villanueva-Rosales *, Luis Garnica Chavira * , Nicholas del Rio † , Deana Pennington * Experience Paper *Cyber-ShARE Center of Excellence, University of Texas at El Paso, El Paso, US † Air Force Research Lab, Information Directorate, Rome, US.

Overview ▪ Motivation ▪ The Earth Life and Semantic Web Project (ELSEWeb) ▪ Creating Species Distribution Models: A User’s Perspective ▪ ELSEWeb’s Service Oriented Architecture ▪ ELSEWeb’s User Interface ▪ User Study ▪ Lessons Learned ▪ Conclusions and Future Work ▪ Acknowledgements 2

Motivation ▪ Large amount of time invested in finding and preprocessing data to use specialized tools. ▪ Heterogeneity of data formats, programming, query languages, and lack of documentation, contribute to the challenges of interoperability between scientific tools. ▪ It is expected to have a wide array of tools and data available for the generation of biodiversity models, the challenge is to integrate them ▪ Cyberinfrastructure (CI) streamlining the integration of data and models would allow scientists to focus on the science. 3

The Earth Life and Semantic Web Project (ELSEWeb) ▪ Aims to develop and test generic scalable solutions to address integration of data and models . ▪ Initial use case: Integrating raster-based environmental data sets such as satellite imagery with species distribution models (SDMs). ▪ This presentation: ELSEWeb architecture (including GUI), usability study and lessons learned. 4

Species Distribution Models (SDMs) EDAC Environmental Data Agave Lecheguilla Output Lifemapper Model Agave Lecheguilla Occurrence Sets 5

User task without User task with ELSEWeb task ELSEWeb ELSEWeb Search for rainfall, terrain ● ● or vegetation data ● Download data Import to GIS or Image ● Processing System C OMPARISON MATRIX Obtain Lifemapper data ● ● requirements TASKS REQUIRED FOR THE GENERATION OF SDM S WITH AND WITHOUT THE USE ● ● Transform data OF ELSEW EB ● Export data ● Import data to QGIS ● Install Lifemapper Plugin Select Lifemapper ● ● experiment elements ● Assemble package Run Lifemapper 6 ● ● experiments

ELSEWeb’s Service Oriented Architecture ▪ Four principles of the Model Web: open access , minimal barriers to entry , service-driven and scalable . ▪ Service Oriented Architecture (SOA) using Web Services to achieve interoperability between third party service providers. ▪ Semantic capabilities. 7

ELSEWeb’s Service Oriented Architecture SOA View - Primary Representation

Semantic-Based Services Layered View – Primary Representation

ELSEWeb’s GUI Layered View – Primary Representation

ELSEWeb’s JavaScript Framework Layered View – Primary Representation

Step 1 Region Bounding Box Selection

Step 2 Species Occurrence Set Selection

Step 3 Environmental Dataset Filtering

Step 4 Modeling Algorithm Selection

Step 5 Experiment Submission and Dataset Selection

Step 6 Experiment Results and Provenance

User Study ▪ Guidelines and methodologies provided by the U.S. Department of Health & Human Services ( usability.gov ). ▪ Sample of 15 students from the University of Texas at El Paso. ▪ The session captured participant’s navigational choices , logger observations , task completion rates and post- test survey . ▪ Screen interaction and participant audio was recorded with BB Flash Back Express Recorder software. ▪ Each individual session lasted approximately 15 minutes. 18

User Study Evaluation Tasks ID ¡ Task ¡ T1 ¡ Login to the website. ¡ T2 ¡ Establish a boxed region for dataset availability. ¡ T3 ¡ Select species occurrence set. ¡ Set filtering parameters for corresponding T4 ¡ datasets ¡ T5 ¡ Select Model algorithm and parameter values. ¡ T6 ¡ Select datasets for experiment submission. ¡ T7 ¡ Submit experiment specification. ¡ T8 ¡ Consult experiment status. ¡ 19

Task # Task short description #of participants Non- Task completing the critical execution task errors avg. time (seconds) 1 Website login. 15 3 53 2 Establish boxed 15 11 94 Usability Study region for data Results availability. 3 Select species 15 7 47 Task Summary Table occurrence set. 4 Set filtering 15 9 73 parameters for datasets 5 Select model 14 0 19 algorithm and parameter values. 6 Select datasets. 15 0 21 7 Submit experiment 15 0 37 specification. 8 Consult experiment 13 6 34 status. 20

Survey Sample Results Overall GUI Score Ease of use 12 Excellent 10 Good 8 6 Average 4 Fair 2 Poor 0 Strongly Disagree Neutral Agree Strongly 0 2 4 6 8 10 Disagree Agree Responses Responses 21

User Issues Good… ▪ “Interface was very useful and friendly .” ▪ “Overall, the site worked perfectly fine, was straight forward , and easy to use .” Not so good… ▪ “It was frustrating not knowing that an option must be modified and reconfigured in order to prepare the Environmental Data Filters section.” ▪ “I had a hard time at the beginning to figure out where the tabs where , I had to scroll down to figure out there were at the bottom.” 22

Recommendations Overall Experiment Interface. ¡ Visual queues for the workflow been executed. ¡ 1 2 3 4 5 6 Region Species Datasets Algorithm Selection Submit What I’m I missing to General move to the Description next step? Parameters and Meanings 23

Related Work ▪ Model Web – aims for seamless interoperability between data and model providers. ELSEWeb focuses on environmental data into SDMs. (S. Nativi, et al., 2013) ▪ Research Objects (ROs), semantically rich aggregation of resources produced and consumed by services. RO features in ELSEWeb: aggregation, identity, metadata and lifecycle. (S. Bechhofer, et al., 2013) ▪ IPlant collaborative framework , real time services cover for construction and execution of scientific workflows. In addition, ELSEWeb offers service orchestration. These systems can achieve interoperability through ontology mapping. (D. D. Gessler , et al., 2013) 24

Discussion and Lessons Learned ▪ ELSEWeb architecture is extensible . ▪ Use of standards and best practices as a key element to enable interoperability with other systems. ▪ Notifications and synchronizations with third-party services is essential when reusing and linking resources. ▪ Use of conceptual models for communication across members of the collaborative, multidisciplinary team. ▪ Involvement of end-users facilitated development of framework but also validation of technically sound results. 25

Future Work ▪ Extending ELSEWeb to incorporate process models for water resource analysis – Model to model integration. ▪ URI naming conventions. ▪ Implementing the recommendations obtained in from the usability study. ▪ Further development of user-centered interfaces . ▪ Scientific evaluation . 26

Acknowledgements • ELSEWeb was funded by the NASA ACCESS grants NNX12AF49A (UTEP), NNX12AF52A (UNM), and NNX12AF45A (KU). • This work used resources from Cyber-ShARE Center of Excellence supported by NSF grant HRD-0734825. Linking knowledge across disciplines, Cyber-ShARE data and models 27

Useful Links ▪ ELSEWeb GUI: http://elseweb.cybershare.utep.edu/experimentgui ▪ Usability Study Report: http://elseweb.cybershare.utep.edu/publications ▪ Previous Papers: http://elseweb.cybershare.utep.edu/publications ▪ Usability.gov: http://www.usability.gov/ Looking for collaborators, contact us! 28

The Earth Life and Semantic Web Project http://elseweb.cybershare.utep.edu/ 29