NKN Presentations

NKN Tech Talk: Building with Jekyll


Presented by:  Evan Williamson and Devin Becker (UI Library Data and Digital Services)

Evan and Devin, Digital Infrastructure Librarians from the UI Library talk about how they are using Jekyll static site generator in redevelopment of the digital collections websites.  

Presentation: https://osf.io/amvs5/

NKN Tech Talk: The Docker System


Presented by:  Casey Blair (NKN Research Software Developer)

Docker provides a way to deploy flexible, minimal virtual containers around services and applications in order to build up scalable and manageable service-oriented architectures.   Casey has successfully dockerized various components of the NKN portal and new metadata editor and will be presenting on his preliminary findings today.

Learn more about Docker at: https://www.docker.com

NKN Tech Talk: From data portal to knowledge portal


Presented by: Marshall Ma (Assistant Professor, Computer Science Department, University of Idaho)

Full Title: "From data portal to knowledge portal: Leveraging semantic technologies to support interdisciplinary studies"

Abstract: Scientific research practices regularly adopt new technologies and platforms in an effort to increase information timeliness, sharing and discoverability. There are many initiatives related to open data, open code, open access, open collections, composing the topic of Open Science in academia. Being open has two levels of meanings. The first is to make the data, code, sample collections and publications, etc. freely accessible online. The other is the annotation and connection between those resources to establish the provenance information for reproducible scientific research. In this talk I will present our work on a web portal for the Deep Carbon Observatory (DCO) community. Experience on the use of a few technological platforms such as VIVO, CKAN, Drupal and the Handle System will be introduced. The DCO is a 10-year (2009-2019) initiative to intensify global attention and scientific effort in the burgeoning field of deep carbon science. Inspired by guiding questions such as “how much carbon does Earth contain?”, “where is it?” and “what can deep carbon tell us about origins?” more than 1000 scientists across the world are  actively participating in the DCO community. The DCO web portal is a research collaboration website developed to keep track of all researchers, organizations, instruments, field sites, and research outputs related to the DCO community. We intend for the DCO web portal to be a knowledge portal - adopting state-of-the-art semantic technologies to support various stages of the scientific process within and beyond the DCO community. 

NKN Tech Talk: Predicting climate hazard impacts in the pacific northwest


Presented by: Erich Seamon (REACCH, NKN)

As part of the Climate Impacts Research Consortium (CIRC – www.pnwcirc.org) NOAA funded effort, the following presentation will provide a preliminary overview of current data mining and machine learning work to explore climate hazard impact prediction in the Pacific Northwest. We are currently focusing on two predictive model areas and their relationships to climate hazards: 1) predicting agricultural crop loss. We are exploring ways to predict economic crop loss outcomes based on future climate model outputs, as well as more recent local forecast data. Using differing machine learning techniques, the goal is to effectively predict commodity loss at 4km cell level, using USDA agricultural insurance crop claims as data source. With a reliable predictive model, we can then explore predictive conditional relationships that may exist between crop loss and other inputs. 2) Landslide susceptibility. Using a similar structure, we are data mining observational landslide data from external sources, and using that data as a basis to create landslide zonation regions (Kanungo, et al, 2009) for economic loss prediction. In particular, we are exploring the use of artificial neural networks (ANN) to classify these landslide zones (Ercanglu, 2005; Arora et al., 2004; Gomez and Kavzoglu, 2005; Yesilnacar and Topal, 2005). 3) Application instantiation and API development. By integrating the aforementioned models into a dynamic application programming interface (API), we can build applications that visualize predictive probability model outcomes, as well as enable others to build their own API-compliant applications.

Dr. Jason Evans of Facebook


Dr. Evans is a Senior Software Engineer @ Facebook. He is also a UI Alum (B.S. Computer Science, Ph.D Bioinformatics). Dr. Evans was featured in this Wired article, “How Three Guys Rebuilt the Foundation of Facebook” (it's also an interesting perspective on the history and future of the PHP language!).

Between his B.S. in Computer Science and starting his PhD, Jason also worked at Apple, Inc. as a member of the Core operating systems team developing Mac OS X. Jason will lead an informal discussion of some of his large-scale programming projects (HHVM, jemalloc, others) that he contributed to at Facebook and elsewhere.

NKN Tech Talk: Deploying Predictive Models in the Cloud using Yhat

yhat-presentation.pdf

Yhat (yhat.com) is a commercial data science technology company that provides a cloud-based predictive analytics platform. Specifically, Yhat provides the ability to stand-up and publish statistical machine learning and prediction algorithms in the cloud and make these accessible via a simple REST API web service. NKN's Luke Sheneman presents on how to get started with using yhat.com and works through a practical demonstration of how to write your own models, train them on your data, and then deploy your trained statistical model on the Yhat cloud. Luke also demonstrates Yhat’s web interface for interacting with the REST API for the published prediction model, including details of the JSON input/output.

NKN Tech Talk: Implementation of an OAIS Repository

ed_nkn_techtalk_20151203.pdf

NKN's Ed Flathers discusses choices that led us to use the ESRI geoportal (for NKN's Data Repository), what we like and don't like about it, where we aim to be, and what progress we’ve made in that direction. The focus is on modular construction and the use of free, open-source software components to avoid either getting locked-in to a particular monolithic solution or finding ourselves reinventing the wheel over and over again.

NKN Tech Talk: Low-Level NKN Architecture

nkn_tech_talk_20150924.pdf , NKN_architecture_sheneman_july2014.pdf , NKN_architecture_sheneman_may2012.pdf

NKN's Luke Sheneman provides a brief presentation and moderates a discussion about the low-level components of the NKN Architecture, including brainstorming possible future directions with our low-level architecture.

NKN Tech Talk: VIVO


Jeremy Kenyon, UI Research Librarian, leads a technical discussion of the VIVO system which is jointly run by the UI Library and NKN. VIVO is a research-focused discovery tool that enables collaboration among scientists across all disciplines at the University of Idaho. Fed from institutional and publicly accessible data, VIVO includes a network of experts, web profiles, and an archive of publications.

Tighter integration between VIVO and the NKN Data Catalog is desirable and we discuss possible integration strategies.

NKN Tech Talk: An Overview of Database Models


Dr. Norm Pendegraft from the UI Department of Business provides a survey and discussion of the technical merits of different database models. We attempt to highlight where we currently use these different database models within the existing NKN infrastructure.

NKN Tech Talk: Data Observatories

INL_BigData_NKN_2015may.pdf

NKN's Technology and Data Services Manager, Luke Sheneman, presents on NKN as a Data Observatory. Also, as a group, we brainstorm/identify some NKN-hosted data (and some external data sources) that could be the basis of one or more compelling demonstrations to host on the NKN website.

NKN Tech Talk: Data Mining and Machine Learning

data_mining_presentation_erichs.pdf

Erich Seamon, Data Manager for the REACCH project, leads a discussion of data mining and machine learning as it applies to enabling data-intensive science.

NKN Tech Talk: Google Computing and the Development of ClimateEngine.org

NKN-TechTalk-ClimateEngine.pdf

Katherine Hegewisch presents on how Google Computing resources have aided the development of a web application that Katherine, Donny VanSant, and John Abatzoglou have been working on for the last 8 months with the Desert Research Institute and Google which they call Climate Engine.

NKN Students Present at AGU


UI graduate students Ed Flathers and Erich Seamon presented their research at the 2014 American Geophysical Union (AGU) Fall Meeting. The meeting was held in San Francisco, Dec 15-19. Erich and Ed were co-authors on two posters entitled, "Development of an interactive crop growth web service architecture to review and forecast agricultural sustainability" and "Service-Based Extensions to an OAIS Archive for Science Data Management".

NKN Director Presents at Purdue

20141208_gessler_flyer_purdue.pdf

NKN director Paul Gessler spoke at Purdue University's Agronomy seminar on Dec 8, 2014. His presentation    was entitled, "Soil-landscape Modeling: From Hillslopes to Landscapes and Big Data Analysis Opportunities".

NKN Poster & Brochure for GIS Day 2014

NKN_brochure_20141114.pdf , NKN_poster_GISday_jh.pdf

NKN staff Jennifer Hinds and Marisa Guarinello created a poster & brochure and staffed the NKN information table at GIS Day on the UI Campus in the Idaho Commons.