Cyberinfrastructure in practice

Slides:



Advertisements
Similar presentations
OMV Ontology Metadata Vocabulary April 10, 2008 Peter Haase.
Advertisements

The Documentum Team Lance Callaway, Brooke Durbin, Perry Koob, Lorie McMillin, Jennifer Song Missouri University of Science and Technology Rolla, Missouri.
A New Computing Paradigm. Overview of Web Services Over 66 percent of respondents to a 2001 InfoWorld magazine poll agreed that "Web services are likely.
©Ian Sommerville 2004Software Engineering, 7th edition. Chapter 17 Slide 1 Rapid software development.
INTRODUCTION TO CLOUD COMPUTING Cs 595 Lecture 5 2/11/2015.
These materials are prepared only for the students enrolled in the course Distributed Software Development (DSD) at the Department of Computer.
Open and Shared Information System OaSIS. SUNCOM’s Standard Business Process Centralized ordering for the enterprise Maintenance of an enterprise inventory.
The Internetworked E-Business Enterprise
Cloud computing is the use of computing resources (hardware and software) that are delivered as a service over the Internet. Cloud is the metaphor for.
EARTH SCIENCE MARKUP LANGUAGE “Define Once Use Anywhere” INFORMATION TECHNOLOGY AND SYSTEMS CENTER UNIVERSITY OF ALABAMA IN HUNTSVILLE.
Why We Create Metadata and How it is Useful Bruce Godfrey University of Idaho Library INSIDE Idaho
Integrating a Statewide Web Gateway With Digital Collections ______________________ Eric Weig and Beth Kraemer University of Kentucky and KCVL.
ASAM Standards International Perspective – A Report Author : Puran Parekh Board of Directors – ASAM e.V. 26th October 2011 Novi, USA.
© 2012 xtUML.org Bill Chown – Mentor Graphics Model Driven Engineering.
EPA Enterprise Data Architecture Metadata Framework Assessment Kevin J. Kirby, Enterprise Data Architect EPA Enterprise Architecture Team
NA-MIC National Alliance for Medical Image Computing UCSD: Engineering Core 2 Portal and Grid Infrastructure.
Frameworks CompSci 230 S Software Construction.
OAIS Rathachai Chawuthai Information Management CSIM / AIT Issued document 1.0.
Chapter 6 CASE Tools Software Engineering Chapter 6-- CASE TOOLS
PHS / Department of General Practice Royal College of Surgeons in Ireland Coláiste Ríoga na Máinleá in Éirinn Knowledge representation in TRANSFoRm AMIA.
Reduce Development and Testing Time on Embedded Space Programs With Auto- Generated Code Software Engineer Northrop Grumman Electronic Systems Matthew.
Lecture 21: Component-Based Software Engineering
1 Get All Answers Get All Answers. Contents History of Android Android Fragmentation The Role of Google Features and Architecture Android Software Development.
MasterCard Global Marketing Center An Alfresco Case Study Jay Mandel, MasterCard International Mike Vertal, Rivet Logic Corporation 15 November 2012.
Jeff Kern NRAO/ALMA.  Scaling and Complexity ◦ SKA is not just a bigger version of existing systems  Higher Expectations  End to End Systems  Archive.
Portlet Development Konrad Rokicki (SAIC) Manav Kher (SemanticBits) Joshua Phillips (SemanticBits) Arch/VCDE F2F November 28, 2008.
A Method for Improving Code Reuse System Prasanthi.S.
Client/Server Technology
Data Management Program Introduction
Computable Contracts as Functional Elements
Eclipse Vorto Alexander Edelmann.
Business System Development
GRASP – Designing Objects with Responsibilities
By: Raza Usmani SaaS, PaaS & TaaS By: Raza Usmani
Global Forest Information Service
COMPACT Web Design Approach:
Complexity Time: 2 Hours.
Lecture 6. Information systems
Web Engineering.
Design and Implementation
Software Product Lines
API Documentation Guidelines
C2CAMP (A Working Title)
Outline Pursue Interoperability: Digital Libraries
Community Information Toolkit
MANAGING KNOWLEDGE FOR THE DIGITAL FIRM
Tools of Software Development
Cloud Computing: IT Seminar
Distribuerte Systemer Viktigere enn vi tror, vanskeligere enn det høres Komponenttorget ‘99 Trondheim Trygve Reenskaug Numerica Taskon Distaribuerte.
Software Architecture
WIS Strategy – WIS 2.0 Submitted by: Matteo Dell’Acqua(CBS) (Doc 5b)
CESSDA Workplan: Metadata Harvesting Tool
Komponentbasert utvikling Den sanne objektorientering
Brian Kotek INDUS Corporation
Cost Estimation Van Vliet, chapter 7 Glenn D. Blank.
Middleware, Services, etc.
ARCHITECTURE OVERVIEW
Biodiversity Economy Tracking System
Intranets & Extranets Companies that do not have the resources to invest in enterprise applications can still achieve some measure of information integration.
Team 13 The Los Angeles Community Garden Inventory and Locator
Software Analysis.
Why IIIF? Shane Huddleston Jeff Mixter Dave Collins Product Manager
MSDI training courses feedback MSDIWG10 March 2019 Busan
Rapid software development
Knowledge Sharing Mechanism in Social Networking for Learning
Introduction to SOA Part II: SOA in the enterprise
Information Systems.
Web Based Tools for Research
SDMX IT Tools SDMX Registry
Chapter 10 – Component-Level Design
Presentation transcript:

Cyberinfrastructure in practice August 5, 2015 Cyberinfrastructure in practice Donald Sturgeon Harvard University sturgeon@fas.harvard.edu

Overview Infrastructure Application Programming Interfaces (APIs) What it is and why it matters Application Programming Interfaces (APIs) Simple examples in widespread use Current examples in Chinese studies Chinese Text Project (ctext.org) API Questions and challenges going forward What infrastructure do we need How are we going to maintain it

Infrastructure Is instrumental Not an end but a means to an end Makes the possible (but difficult) easier Makes the impractical practical Requires up-front investment Requires ongoing maintenance

Infrastructure in the humanities August 5, 2015 Infrastructure in the humanities Domain-specific tools, databases, etc. Humanities research tools Special-purpose research infrastructures ? ctext API CBDB API ? CTS General-purpose infrastructures Code Libraries Software Services Standards Low-level software infrastructure General-purpose operating systems “Real-world” infrastructure Electricity, hardware, etc.

Types of humanities infrastructure Data formats Text Encoding Initiative (TEI) Application Programming Interfaces (APIs) IIIF Image API Open source software and libraries Stanford CoreNLP Services University Library provision of IIIF-compliant data

Application Programming Interfaces What do they do? Predictable mechanisms for data exchange Increasingly: web APIs What are they useful for? Making materials/services available in consistent way Abstraction from implementation details Allowing the creation of “derived products” “Mashups” consisting of independently maintained parts Mining and analysis of data “Offloading” part of the development process

Google Maps Google Maps user interface Allows access to Google-defined services Google Maps API Allows building upon Google’s map services Create things Google alone would never create

Google Maps + Housing Rental Data Distribution of effort: Google: has no control over apartment data maintains map data and map interface Rental search company: has limited control over map data & interface maintains apartment rental information Resulting mashup is nevertheless a cohesive product Works as if created by a single group In fact maintained by two independent groups

Google Maps + Disease Data Economies of scale: Google: concentrates on one thing only: maps Other groups: concentrate on their own content benefit from centralization of map-related code & data Lower barriers to entry for subsequent projects Not a closed, one-off collaboration Instead: an open invitation to others to collaborate

APIs in practice: ctext API

APIs in practice: ctext API ctext, MARKUS, Text Tools, etc. all communicate via public API Everyone has access to the API and its documentation Lowers barriers to entry for subsequent projects Not a closed, one-off collaboration Instead: an open invitation to others to collaborate Anyone can create and distribute a new API client / plugin

APIs in the humanities How to create economies of scale What areas benefit from standardization What areas benefit from decentralization How to let projects concentrate on core work Digital projects increasingly complex No single team can expect to do everything well What infrastructure is most urgently needed Which components have greatest reuse potential

Cyberinfrastructure: challenges Components need to be maintained over time How will this be guaranteed institutionally Standardization is beneficial but not easy Humanities data is complex TEI is one example demonstrating this complexity Cyberinfrastructure needs coordination Not just a function of a single group Many stakeholders Data creators, disseminators, consumers, end users, etc.

Thank you!