This document discusses challenges and opportunities for developing sustainable software for science. It notes that software is increasingly important for science but current practices and incentives do not support long-term sustainability. The document summarizes discussions from the Working Towards Sustainable Software for Science conference, which identified key issues around developing sustainable software, best practices, policies around credit and careers, and building supportive communities. It proposes that better measuring contributions to software could help address incentives, career paths, and sustainability of software over the long term.
Collection Methodology for Key Performance Indicators for Smart Sustainable C...ITU
These indicators have been developed to provide cities with a consistent and standardised method to collect
data and measure performance and progress to:
achieving the Sustainable Development Goals (SDGs)
becoming a smarter city
becoming a more sustainable city
The indicators will enable cities to measure their progress over time, compare their performance to other
cities and through analysis and sharing allow for the dissemination of best practices and set standards for
progress in meeting the Sustainable Development Goals (SDGs) at the city level.
For more information visit: https://www.itu.int/en/ITU-T/ssc/united/Pages/default.aspx
Understanding Smart Cities as Social MachinesDirk Ahlers
Presentation at the 4th International Workshop on the Theory and Practice of Social Machines SOCM2016 at WWW2016.
Paper is here:
http://www2016.net/proceedings/companion/p759.pdf
More details: http://www.informatik.uni-oldenburg.de/~there/
Møte mellom NTNU Smart Sustainable Cities og Gjøvik kommune & eiendomsutviklere, 12.01.2018
Overview of ICT/Computer Science projects and large-scale approaches to understand and build Smart Cities.
Challenges in Replication and Scaling of PEDs – Technical and Organisational ...Dirk Ahlers
Presentation at: NordicEdge 2021 Smart City Research Symposium | Workshop: Positive Energy Districts as vehicle towards smart and sustainable cities | 22.09.2021
Dirk Ahlers, Annemie Wyckmans
NTNU – Smart Sustainable Cities Group
NTNU Climate-KIC Lessons: Learnings from project development with Climate-KICDirk Ahlers
17.11.2020 NTNU Horizon Europe and Erasmus+ Launch Week, Session: Experiences & Opportunities with EIT Climate-KIC. - European Institute of Innovation and Technology (EIT) in Horizon Europe.
Invited talk on Learnings from project development, participation, and management with Climate-KIC.
Collection Methodology for Key Performance Indicators for Smart Sustainable C...ITU
These indicators have been developed to provide cities with a consistent and standardised method to collect
data and measure performance and progress to:
achieving the Sustainable Development Goals (SDGs)
becoming a smarter city
becoming a more sustainable city
The indicators will enable cities to measure their progress over time, compare their performance to other
cities and through analysis and sharing allow for the dissemination of best practices and set standards for
progress in meeting the Sustainable Development Goals (SDGs) at the city level.
For more information visit: https://www.itu.int/en/ITU-T/ssc/united/Pages/default.aspx
Understanding Smart Cities as Social MachinesDirk Ahlers
Presentation at the 4th International Workshop on the Theory and Practice of Social Machines SOCM2016 at WWW2016.
Paper is here:
http://www2016.net/proceedings/companion/p759.pdf
More details: http://www.informatik.uni-oldenburg.de/~there/
Møte mellom NTNU Smart Sustainable Cities og Gjøvik kommune & eiendomsutviklere, 12.01.2018
Overview of ICT/Computer Science projects and large-scale approaches to understand and build Smart Cities.
Challenges in Replication and Scaling of PEDs – Technical and Organisational ...Dirk Ahlers
Presentation at: NordicEdge 2021 Smart City Research Symposium | Workshop: Positive Energy Districts as vehicle towards smart and sustainable cities | 22.09.2021
Dirk Ahlers, Annemie Wyckmans
NTNU – Smart Sustainable Cities Group
NTNU Climate-KIC Lessons: Learnings from project development with Climate-KICDirk Ahlers
17.11.2020 NTNU Horizon Europe and Erasmus+ Launch Week, Session: Experiences & Opportunities with EIT Climate-KIC. - European Institute of Innovation and Technology (EIT) in Horizon Europe.
Invited talk on Learnings from project development, participation, and management with Climate-KIC.
Data Technology and Smart Cities - Guest lecture Sustainable Facility ManagementDirk Ahlers
Introduction Guest lecture in the Sustainable Facility Management about use cases and options of using Smart City Data Technology in facility management
Urban nodes of soft infrastructure in Amsterdam and BerlinNico Janssen
A research study to the initiative, development, functioning, benefits and effects of vibrant social - urban places in Amsterdam and Berlin which stimulate the livability and vitality of neighborhoods, quarters and the city as a whole and are developed by local initiatives (artists, local entrepreneurs, local inhabitants)
Pauline Riordan Dublinked Smart Dublin Launch 8th March 16Mainard Gallagher
Pauline Riordan has worked for over 16 years in Irish local government in a number of roles including open data, strategic design, stakeholder engagement and urban planning. Since 2015 she is the manager of the Dublinked Open Data Platform and innovation network, dealing with data, smart city and research issues both regionally and internationally. Pauline has qualifications in urban planning, urban design and architecture and has a keen interest in sustainable living, future cities and new models of collaborative urbanism.
Conference at Tongi University - Shanghai: Smart City for developing and eme...Isam Shahrour
The conference of professor Isam Shahrour presented the urban challenges of emerging and developing countries, the concept of the Smart City and how this concept could help in facing the challenges of these countries. It also presents the implementation of the Smart City concept through the construction of the SunRise Smart City demonstrator.
Smart Cities that don't go "bump" in the night: delivering interoperable smar...Rick Robinson
I gave this presentation at the launch of the British Standards Institute's development of standards for interoperability between Smart Cities systems. It draws on my experience delivering large-scale, standards-based technology architectures. Whilst Open Standards will be absolutely crucial to the delivery and operation of interoperable, open Smart Cities systems, they are not a panacea, and it's vital that we're aware of their limitations as well as their value.
21c President and Founder, Dr Julia Glidden was invited by Google to be a key speaker at their TEDx event on Smart Cities. Speaking to over 200 members of Google Julia set out the concept of using a city as an innovation platform, using open data to harness the power of a cities greatest resource – its citizens.
Rob Kitchin Smart Cities 08th March 2016 (Smart Dublin)Mainard Gallagher
Rob Kitchin is a Professor and ERC Advanced Investigator in the National Institute of Regional and Spatial Analysis at Maynooth University, for which he was director between 2002 and 2013. He is one of Ireland's leading social scientists and was the 2013 recipient of the Royal Irish Academy's Gold Medal for the Social Sciences and received the Association of American Geographers ‘Meridian Book Award’ for the outstanding book in the discipline in 2011.
Metrics & Citation for Software (and Data)Daniel S. Katz
A talk about why metrics and citation for software (and data) are important to NSF and the science & engineering community, and what a number of projects are trying to do to improve the situation. Presented at "Workshop on Supporting Scientific Discovery through Norms and Practices for Software and Data Citation and Attribution", Washington, DC, 29 Jan 2015
A description of the idea of transitive credit, a potential way of quantifying the contribution of various people to scholarly products, where the contribution is direct or indirect (through additional levels of products)
Data Technology and Smart Cities - Guest lecture Sustainable Facility ManagementDirk Ahlers
Introduction Guest lecture in the Sustainable Facility Management about use cases and options of using Smart City Data Technology in facility management
Urban nodes of soft infrastructure in Amsterdam and BerlinNico Janssen
A research study to the initiative, development, functioning, benefits and effects of vibrant social - urban places in Amsterdam and Berlin which stimulate the livability and vitality of neighborhoods, quarters and the city as a whole and are developed by local initiatives (artists, local entrepreneurs, local inhabitants)
Pauline Riordan Dublinked Smart Dublin Launch 8th March 16Mainard Gallagher
Pauline Riordan has worked for over 16 years in Irish local government in a number of roles including open data, strategic design, stakeholder engagement and urban planning. Since 2015 she is the manager of the Dublinked Open Data Platform and innovation network, dealing with data, smart city and research issues both regionally and internationally. Pauline has qualifications in urban planning, urban design and architecture and has a keen interest in sustainable living, future cities and new models of collaborative urbanism.
Conference at Tongi University - Shanghai: Smart City for developing and eme...Isam Shahrour
The conference of professor Isam Shahrour presented the urban challenges of emerging and developing countries, the concept of the Smart City and how this concept could help in facing the challenges of these countries. It also presents the implementation of the Smart City concept through the construction of the SunRise Smart City demonstrator.
Smart Cities that don't go "bump" in the night: delivering interoperable smar...Rick Robinson
I gave this presentation at the launch of the British Standards Institute's development of standards for interoperability between Smart Cities systems. It draws on my experience delivering large-scale, standards-based technology architectures. Whilst Open Standards will be absolutely crucial to the delivery and operation of interoperable, open Smart Cities systems, they are not a panacea, and it's vital that we're aware of their limitations as well as their value.
21c President and Founder, Dr Julia Glidden was invited by Google to be a key speaker at their TEDx event on Smart Cities. Speaking to over 200 members of Google Julia set out the concept of using a city as an innovation platform, using open data to harness the power of a cities greatest resource – its citizens.
Rob Kitchin Smart Cities 08th March 2016 (Smart Dublin)Mainard Gallagher
Rob Kitchin is a Professor and ERC Advanced Investigator in the National Institute of Regional and Spatial Analysis at Maynooth University, for which he was director between 2002 and 2013. He is one of Ireland's leading social scientists and was the 2013 recipient of the Royal Irish Academy's Gold Medal for the Social Sciences and received the Association of American Geographers ‘Meridian Book Award’ for the outstanding book in the discipline in 2011.
Metrics & Citation for Software (and Data)Daniel S. Katz
A talk about why metrics and citation for software (and data) are important to NSF and the science & engineering community, and what a number of projects are trying to do to improve the situation. Presented at "Workshop on Supporting Scientific Discovery through Norms and Practices for Software and Data Citation and Attribution", Washington, DC, 29 Jan 2015
A description of the idea of transitive credit, a potential way of quantifying the contribution of various people to scholarly products, where the contribution is direct or indirect (through additional levels of products)
A talk about the "Working towards Sustainable Software for Science: Practice and Experience (WSSSPE)" community/theme/set of workshop, focused on WSSSPE3, the working groups that were formed there, how they have developed from activities in previous WSSSPE3 meetings, and their current status.
This talk was given as a Dagstuhl meeting on Engineering Academic Software (http://www.dagstuhl.de/en/program/calendar/semhp/?semnr=16252) 20 June 2016.
Discussing Software Citation and related topics at Workshop on Data and Software Citation (June 6-7 at Harvard Medical School, http://www.software4data.com/#!nsf-workshop/jghgb)
Swift Parallel Scripting for High-Performance WorkflowDaniel S. Katz
The Swift scripting language was created to provide a simple, compact way to write parallel scripts that run many copies of ordinary programs concurrently in various workflow patterns, reducing the need for complex parallel programming or arcane scripting to achieve this common high-level task. The result was a highly portable programming model based on implicitly parallel functional dataflow. The same Swift script runs on multi-core computers, clusters, grids, clouds, and supercomputers, and is thus a useful tool for moving workflow computations from laptop to distributed and/or high performance systems.
Swift has proven to be very general, and is in use in domains ranging from earth systems to bioinformatics to molecular modeling. It’s more recently been adapted to serve as a programming model for much finer-grain in-memory workflow on extreme scale systems, where it can perform task rates in the millions to billion-per-second.
In this talk, we describe the state of Swift’s implementation, present several Swift applications, and discuss ideas for of the future evolution of the programming model on which it’s based.
Advancing Science through Coordinated CyberinfrastructureDaniel S. Katz
How local, regional, and national cyberinfrastructure can be coordinated and linked to advance science and engineering, based on experiences and lessons from the Center for Computation & Technology at LSU (ideas, funding, implementation), plus some thoughts on what might be done differently if we were starting today. Presented at First Workshop - Center for Computational Engineering & Sciences, Unicamp, Campinas, Brazil 10 APR 2014
Using Application Skeletons to Improve eScience InfrastructureDaniel S. Katz
presentation of Zhao Zhang & Daniel S. Katz, "Using Application Skeletons to Improve eScience Infrastructure", Proceedings of 10th IEEE International Conference on eScience (eScience 2014), Guarujá, Brazil, October 23, 2014. DOI: 10.1109/eScience.2014.9
US University Research Funding, Peer Reviews, and MetricsDaniel S. Katz
My part of the "Digital Science Webinar: Articulating Research Impact – Strategies from Around the Globe" (http://www.digital-science.com/events/digital-science-webinar-articulating-research-impact-strategies-from-around-the-globe/)
Daniel S. Katz will discuss how reviewers at the National Science Foundation (USA) consider the “intellectual merit” and “broader impacts” criteria for funding and in particular how metrics might help applicants understand their impacts in these areas.Dan will also talk about how reviewers might use qualitative and quantitative altmetrics data to inform their peer reviews for grant applications. He will address many of the salient questions around this use of metrics, for example, do reviewers take metrics seriously and what types of metrics are of most value to them?
Some thoughts on how research and infrastructure software are supported by NSF (and possibly other agencies), for the "What can academia learn from open source?" Academia Town Hall - https://ti.to/github-events/academia-town-hall-
A description of software as infrastructure at NSF, and how Apache projects may be similar. What lessons can be shared from one organization to the other? How does science software compare with more general software?
Scientific Software Innovation Institutes (S2I2s) as part of NSF’s SI2 programDaniel S. Katz
This talk, presented at a computational chemistry institute conceptualization project (https://sites.google.com/site/s2i2biomolecular/), discusses a view Scientific Software Innovation Institutes, as part of NSF's Software Infrastructure for Sustained Innovation (SI2) program
Scientific Software Challenges and Community ResponsesDaniel S. Katz
a talk given at RTI International on 7 December 2015, discussing 12 scientific software challenges and how the scientific software community is responding to them
International Symposium NLHPC 2013: Innovation at the frontier of HPC
Title: XSEDE: an ecosystem of advanced digital services accelerating scientific discovery
Abstract:
The XSEDE program (Extreme Science and Engineering Discovery Environment) has recently entered its third year of operation. In this talk we will discuss the vision, mission and goals of this project and some of the distinguishing characteristics of the program. This will be accompanied by a review of current status and look ahead at where the program is headed over the next several years.
EarthCube Monthly Community Webinar- Nov. 22, 2013EarthCube
This webinar features project overviews of all EarthCube Awards (Building Blocks, Research Coordination Networks, Conceptual Designs, and Test Governance), followed by a call for involvement, and a Q&A session.
Agenda:
EarthCube Awards – Project Overviews
1.. EarthCube Web Services (Building Block)
2. EC3: Earth-Centered Community for Cyberinfrastructure (RCN)
3. GeoSoft (Building Block)
4. Specifying and Implementing ODSIP (Building Block)
5. A Broker Framework for Next Generation Geoscience (BCube) (Building Block)
6. Integrating Discrete and Continuous Data (Building Block)
7. EAGER: Collaborative Research (Building Block)
8. A Cognitive Computer Infrastructure for Geoscience (Building Block)
9. Earth System Bridge (Building Block)
10. CINERGI – Community Inventory of EC Resources for Geoscience Interoperability (BB)
11. Building a Sediment Experimentalist Network (RCN)
12. C4P: Collaboration and Cyberinfrastructure for Paleogeosciences (RCN)
13. Developing a Data-Oriented Human-centric Enterprise for Architecture (CD)
14. Enterprise Architecture for Transformative Research and Collaboration (CD)
15. EC Test Enterprise Governance: An Agile Approach (Test Governance)
A Call for Involvement!
Presenting the following paper “Science Gateways: The Long Road to the Birth of an Institute” by Sandra Gesing, Nancy Wilkins-Diehr, Maytal Dahan, Katherine Lawrence, Michael Zentner, Marlon Pierce, Linda Hayden, Suresh Marru at HICSS50 Conference.
Supporting Research Communities with XSEDEJohn Towns
XSEDE is a major research infrastructure in the United States with collaborations worldwide supporting thousands of researchers across a wide range of domains. XSEDE has taken an integrative and holistic approach to supporting researchers in the use of the varying resources and services available via XSEDE. This presentation will breifly review XSEDE and its vision and provide a discussion of the efforts within XSEDE targeted at supporting research communities.
SGCI - Science Gateways - Technology-Enhanced Research Under Consideration of...Sandra Gesing
Science gateways - also called virtual research environments or virtual labs - allow science and engineering communities to access shared data, software, computing services, instruments, and other resources specific to their disciplines and use them also in teaching environments. In the last decade mature complete science gateway frameworks have evolved such as HUBzero and Galaxy as well as Agave and Apache Airavata. Successful implementations have been adapted for several science gateways, for example, the technologies behind the science gateways CIPRES, which is used by over 20.000 users to date and serves the community in the area of large phylogenetic trees. Lessons learned from the last decade include that approaches should be technology agnostic, use standard web technologies or deliver a complete solution. Independent of the technology, the major driver for science gateways are the user communities and user engagement is key for successful science gateways. The US Science Gateways Community Institute (SGCI), opened in August 2016, provides free resources, services, experts, and ideas for creating and sustaining science gateways. It offers five areas of services to the science gateway developer and user communities: the Incubator, Extended Developer Support, the Scientific Software Collaborative, Community Engagement and Exchange, and Workforce Development. The talk will give an introduction to science gateways, examples for science gateways and an overview on the services offered by the SGCI to serve user communities and developers for creating successful science gateways.
SGCI Science Gateways Landscape in North AmericaSandra Gesing
Presentation at RDA
A) Approaches to interoperability among Science Gateways
B) Key ingredients for successful and vibrant virtual research communities
C) Sustainability of Science Gateways - what are the current models that work (and conversely have failed))
Overview of XSEDE and Introduction to XSEDE 2.0 and BeyondJohn Towns
This presentation will briefly review XSEDE, its past mission and accomplishments, and give insight into the direction and vision for the second round of XSEDE.
A talk presented to the US Networking and Information Technology Research and Development (NITRD) Program's High End Computing Interagency Working Group, 16 January 2020
(a slightly updated version of this talk is at https://doi.org/10.6084/m9.figshare.10301741.v1)
A talk on the role of software in research and how NCSA is responding in terms of people and roles - given at the 2019 Data Science Leadership Summit (https://sites.google.com/msdse.org/datascienceleadership2019/).
This is partially based on a previous paper: Daniel S. Katz, Kenton McHenry, Caleb Reinking, Robert Haines, "Research Software Development & Management in Universities: Case Studies from Manchester's RSDS Group, Illinois' NCSA, and Notre Dame's CRC", 2019 IEEE/ACM 14th International Workshop on Software Engineering for Science (SE4Science)
doi: https://doi.org/10.1109/SE4Science.2019.00009
preprint: https://arxiv.org/abs/1903.00732
Parsl: Pervasive Parallel Programming in PythonDaniel S. Katz
a seminar presented at the School of Computer Science at the University of St Andrews 18 October 2019 (see https://blogs.cs.st-andrews.ac.uk/csblog/2019/09/25/daniel-katz-parsl/)
Requiring Publicly-Funded Software, Algorithms, and Workflows to be Made Publ...Daniel S. Katz
A presentation made to OECD's Committee for Scientific and Technological Policy (CSTP) at the Workshop on the Revision of the Recommendation of the Council concerning Access to Research Data from Public Funding, 15 October 2019
How different groups think about software sustainability, what "equations" we might use to measure it, and how it really can't be measured looking forward but only predicted.
Slides for:
"Software Citation in Theory and Practice," by Daniel S. Katz and Neil P. Chue Hong (published paper - https://doi.org/10.1007/978-3-319-96418-8_34; preprint - https://arxiv.org/abs/1807.08149), presented at International Congress on Mathematical Software (ICMS 2018)
Abstract. In most fields, computational models and data analysis have become a significant part of how research is performed, in addition to the more traditional theory and experiment. Mathematics is no exception to this trend. While the system of publication and credit for theory and experiment (journals and books, often monographs) has developed and has become an expected part of the culture, how research is shared and how candidates for hiring, promotion are evaluated, software (and data) do not have the same history. A group working as part of the FORCE11 community developed a set of principles for software citation that fit software into the journal citation system, allow software to be published and then cited, and there are now over 50,000 DOIs that have been issued for software. However, some challenges remain, including: promoting the idea of software citation to developers and users; collaborating with publishers to ensure that systems collect and retain required metadata; ensuring that the rest of the scholarly infrastructure, particu- larly indexing sites, include software; working with communities so that software efforts count; and understanding how best to cite software that has not been published.
A talk about "Conceptualizing a US Research Software Sustainability Institute (URSSI)" presented at the Toward a New Computational Fluid Dynamics Software Infrastructure (CFDSI, https://www.colorado.edu/events/cfdsi/) workshop in Boulder, CO, 16 May 2018.
A brief status of software citation work presented at AAS splinter meeting on implementing the FORCE11 Software Citation Principles in Astronomy (2018-01-11)
A talk about citation and reproducibility in software, presented at the HSF (High Energy Physics Software Foundation) meeting at SDSC, San Diego, CA, USA, 23 January 2017
Based on citation work done by the FORCE11 Software Citation Working Group as well as recent reproducibility discussions, blogs, and papers
Software Citation: Principles, Implementation, and ImpactDaniel S. Katz
A talk about Software Citation Principles for the 3:am conference (Bucharest, Romania, 28 September 2016), as developed by Arfon M. Smith, Daniel S. Katz, Kyle E. Niemeyer, and the FORCE11 Software Citation Working Group
Working towards Sustainable Software for Science: Practice and Experience (WS...Daniel S. Katz
This was a short talk about the WSSSPE events, given at the Dagstuhl workshop on Engineering Academic Software, 20 June 2016. It mostly discusses the working groups that have formed gradually over the WSSSPE meetings, and specifically those that worked through WSSSPE3, and what that have done since then.
Looking at Software Sustainability and Productivity Challenges from NSFDaniel S. Katz
A lightning talk by Daniel S. Katz and Rajiv Ramnath (NSF) at CSESSP workshop - https://www.nitrd.gov/csessp/
Based on a white paper, at http://arxiv.org/abs/1508.03348
Scientific research: What Anna Karenina teaches us about useful negative resultsDaniel S. Katz
a panel talk for the 1st Workshop on E-science ReseaRch leading tO negative Results (ERROR), held in conjunction with the 11th eScience conference on 3 September 2015 in Munich, Germany
Panel: Our Scholarly Recognition System Doesn’t Still WorkDaniel S. Katz
A panel at the 2015 Science of Team Science (SciTS) Conference
Organizers: Daniel S. Katz (U. of Chicago & Argonne National Laboratory), Amy Brand (Digital Science), Melissa Haendel (Oregon Health & Science University), Holly J. Falk-Krzesinski (Elsevier)
Panelists: Robin Champieux (Oregon Health & Science University) Holly Falk-Krzesinski (Elsevier)Daniel S. Katz (U. of Chicago & Argonne National Laboratory)Philippa Saunders (University of Edinburgh)
Abstract: http://bit.ly/scholarly-recognition
A Method to Select e-Infrastructure Components to SustainDaniel S. Katz
This is a talk presented at International Symposium on Grids and Clouds (ISGC), Taipei, Taiwan, March 20, 2015.
Abstract:
Reusable infrastructure (systems created by one or more people and intended to be used by other people) has become essential for many types of research over the last century, from microscopes to telescopes, and from sequencers to colliders. Over the past few decades, much research infrastructure has become digital, and many new digital systems have been developed. Here we discuss e-Research infrastructure (also called cyberinfrastructure), which has been defined by Craig Stewart as consisting of “... computing systems, data storage systems, advanced instruments and data repositories, visualization environments, and people, all linked together by software and high performance networks to improve research productivity and enable breakthroughs not otherwise possible.” While the research infrastructure as a whole is important, it is useful to consider infrastructure elements as well, as they comprise the overall infrastructure. Each element has a technical context (which allows one to ask questions about its architecture, such as: How does it fit into the overall infrastructure? How does it interact with other infrastructure elements?), a social context (which allows one to ask questions about its developers, such as: Who has developed the element?, and it users, such as: Who uses the element?, and its purpose, such as: What is the intended use of the element?), and a political context (which allows one to ask questions about its funders, such as: Who funds the development and maintenance?, and about its political scope, such as: Is the element national? International?). Understanding how a particular infrastructure element can be created and sustained requires answering two pairs of questions: What resources are needed to create it, and how can those resources be assembled and applied? What resources are needed to sustain it, and how can those resources be assembled and applied? In this paper, we focus on the second half of the two questions, since the amount and type of needed resources vary with the specific element being discussed. We believe elements of e-Research infrastructure can be placed in a three-dimensional space, consisting of temporal duration, spatial extent, and purpose. Note that the number of users of a given element should be larger the farther the element is from the origin in any direction, as should the cost. These two elements (number of users and cost) can be generically called ‘scale’ in this context. Alternatively, we can attempt to map impact, rather than usage, as an element of scale. In either case, scale is thus a metric of the space, though it is not orthogonal to any of the three axes. This talk with discuss how placing potential elements in this space allows decisions to be made on which elements should be pursued.
Multi-component Modeling with Swift at Extreme ScaleDaniel S. Katz
Presentation given at Supercomputing Frontiers 2015 (http://supercomputingfrontiers2015.com), Singapore, March 17, 2015.
Abstract: As both computing systems and science and engineering applications both grow larger and more complex, new challenges arise in abstractly understanding the applications on the systems, productively programming them, and using them to solve real problems. We believe that a large portion of these challenges can be addressed through an appreciation of the hierarchies in such systems, exposed to the user by means of orchestration. The Swift language’s ability to implicitly include parallelism and its highly scalable runtime system allow us to define, express, and efficiently execute applications composed of large-scale parallel components with a variety of connective elements, such as concurrent computational simulations, mathematically oriented data analysis frameworks, and computational simulations with in-situ data analysis.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
DevOps and Testing slides at DASA ConnectKari Kakkonen
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Working towards Sustainable Software for Science (an NSF and community view)
1. Working towards Sustainable
Software for Science
(an NSF and community view)
Daniel S. Katz
dkatz@nsf.gov & d.katz@ieee.org
Program Director, Division of
Advanced Cyberinfrastructure
ESIP Summer Meeting 2014
Copper Mountain - July 9
2. Big Science and Infrastructure
• Hurricanes affect humans
• Multi-physics: atmosphere, ocean, coast, vegetation, soil
– Sensors and data as inputs
• Humans: what have they built, where are they, what will they do
– Data and models as inputs
• Infrastructure:
– Urgent/scheduled processing, workflows
– Software applications, workflows
– Networks
– Decision-support systems,
visualization
– Data storage,
interoperability
3. Long-tail Science and Infrastructure
• Exploding data volumes &
powerful simulation methods
mean that more researchers
need advanced infrastructure
• Such “long-tail” researchers
cannot afford expensive
expertise and unique
infrastructure
• Challenge: Outsource and/or
automate time-consuming
common processes
– Tools, e.g., Globus Online
for data management
– Gateways, e.g., nanoHUB,
CIPRES, access to scientific
simulation software
NSF grant size, 2007.
(“Dark data in the long tail
of science”, B. Heidorn)
4. Science Infrastructure Challenges
• Science
– Larger teams, more disciplines, more countries
• Data
– Size, complexity, rates all increasing rapidly
– Need for interoperability (systems and policies)
• Systems
– More cores, more architectures (GPUs), more memory hierarchy
– Changing balances (latency vs bandwidth)
– Changing limits (power, funds)
– System architecture and business models changing (clouds)
– Network capacity growing; increase networks -> increased security
• Software
– Multiphysics algorithms, frameworks
– Programing models and abstractions for science, data, and hardware
– V&V, reproducibility, fault tolerance
• People
– Education and training
– Career paths
– Credit and attribution
5. Cyberinfrastructure
“Cyberinfrastructure consists of
computing systems,
data storage systems,
advanced instruments and
data repositories,
visualization environments, and
people,
all linked together by
software and
high performance networks,
to improve research productivity and
enable breakthroughs not otherwise possible.”
-- Craig Stewart
6. Cyberinfrastructure Framework for 21st Century
Science and Engineering (CIF21)
• Cross-NSF portfolio of activities to provide integrated cyber resources
that will enable new multidisciplinary research opportunities in all
science and engineering fields by leveraging ongoing investments and
using common approaches and components (http://www.nsf.gov/cif21)
• ACCI task force reports (http://www.nsf.gov/od/oci/taskforces/index.jsp)
– Campus Bridging, Cyberlearning & Workforce Development, Data
& Visualization, Grand Challenges, HPC, Software for Science &
Engineering
• Vision and Strategy Reports
– ACI - http://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf12051
– Software - http://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf12113
– Data - http://www.nsf.gov/od/oci/cif21/DataVision2012.pdf
• Implementation
– Implementation of Software Vision
http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504817
7. Software as Infrastructure
Science
Software
Computing
Infrastructure
• Software (including services) essential for
the bulk of science
- About half the papers in recent issues of
Science were software-intensive projects
- Research becoming dependent upon
advances in software
- Significant software development being
conducted across NSF: NEON, OOI,
NEES, NCN, iPlant, etc
• Wide range of software types: system, applications, modeling,
gateways, analysis, algorithms, middleware, libraries
• Software is not a one-time effort, it must be sustained
• Development, production, and maintenance are people intensive
• Software life-times are long vs hardware
• Software has under-appreciated value
For software to be sustainable,
it must become infrastructure
8. Software Vision
NSF will take a leadership role in providing
software as enabling infrastructure for
science and engineering research and
education, and in promoting software as a
principal component of its comprehensive
CIF21 vision
• ...
• Reducing the complexity of software will be a
unifying theme across the CIF21 vision,
advancing both the use and development of
new software and promoting the ubiquitous
integration of scientific software across all
disciplines, in education, and in industry
– A Vision and Strategy for Software for Science,
Engineering, and Education – NSF 12-113
9. Create and maintain a
software ecosystem
providing new
capabilities that
advance and accelerate
scientific inquiry at
unprecedented
complexity and scale
Support the
foundational
research necessary
to continue to
efficiently advance
scientific software
Enable transformative,
interdisciplinary,
collaborative, science
and engineering
research and
education through the
use of advanced
software and services
Develop a next generation diverse
workforce of scientists and
engineers equipped with essential
skills to use and develop software,
with software and services used in
both the research and education
process
Infrastructure Role & Lifecycle
10. ACI Software Cluster Programs
• ACI co-funding (research -> infrastructure)
– Exploiting Parallelism and Scalability (XPS)
• CISE (including ACI) program for foundational research
– Computational and Data-Enabled Science &
Engineering (CDS&E)
• Virtual program for science-specific proofing of
algorithms and tools
– ENG, MPS, ACI now; BIO, GEO, IIS in FY15?
• ACI lead-funding (infrastructure)
– Software Infrastructure for Sustained Innovation (SI2)
• Transform innovations in research and education into
sustained software resources that are an integral part of
the cyberinfrastructure
– Includes all NSF directorates
11. 4 rounds of funding,
35 SSIs
2 rounds of funding,
14 S2I2
conceptualizations
Software Infrastructure Projects
See http://bit.ly/sw-ci for current projects
5 rounds of funding,
65 SSEs
12. SI2 Solicitation and Decision Process
• Cross-NSF software working group with
members from all directorates
• Determined how SI2 fits with other NSF
programs that support software
– See: Implementation of NSF Software Vision -
http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=5
04817
• Discusses solicitations, determines who will
participate in each
• Discusses and participates in review process
• Work together to fund worthy proposals
13. SI2 Solicitation and Decision Process
• Proposal reviews well -> my role becomes
matchmaking
– I want to find program officers with funds, and convince them
that they should spend their funds on the proposal
• Unidisciplinary project (e.g. bioinformatics app)
– Work with single program officer, either likes the proposal or
not
• Multidisciplinary project (e.g., molecular
dynamics)
– Work with multiple program officers, ...
• Omnidisciplinary project (e.g. http, math library)
– Try to work with all program officers, often am told “it’s your
responsibility”
To judge software, need to
understand/forecast impact
14. ACI Software Cluster Programs
• In these programs, ACI works with other NSF
units to support projects that lead to software
as an element of infrastructure
• Issue: amount of software that is
infrastructure grows over time, and grows
faster than NSF funding
Q: How can NSF ensure that software as
infrastructure continues to appear, without
funding all of it?
A: Incentives
• The devil is in the details
• We are exploring this now...
15. Create and maintain a
software ecosystem
providing new
capabilities that
advance and accelerate
scientific inquiry at
unprecedented
complexity and scale
Support the
foundational
research necessary
to continue to
efficiently advance
scientific software
Enable transformative,
interdisciplinary,
collaborative, science
and engineering
research and
education through the
use of advanced
software and services
Transform practice through new
policies for software, addressing
challenges of academic culture, open
dissemination and use, reproducibility
and trust, curation, sustainability,
governance, citation, stewardship, and
attribution of software authorship
Develop a next generation diverse
workforce of scientists and
engineers equipped with essential
skills to use and develop software,
with software and services used in
both the research and education
process
Infrastructure Role & Lifecycle
16. Working Towards Sustainable
Software for Science: Practice and
Experiences (WSSSPE)
• http://wssspe.researchcomputing.org.uk
• Mailing list:
http://lists.researchcomputing.org.uk/listinfo.cgi/wssspe-
researchcomputing.org.uk
• First Workshop on Sustainable Software for Science:
Practice and Experiences (WSSSPE1), @ SC13, 17
November 2013, Denver
– 2 keynotes, 54 accepted papers
– Discussion sessions: Developing software; Policy; Communities
– Cross-cutting (emergent) topics: Defining sustainability; Career paths
– Post-workshop paper: http://arxiv.org/abs/1404.7414
• Upcoming events:
– WSSSPE1.1, @ SciPy2014, tomorrow!, Austin
– WSSSPE2, @ SC14, 16 November 2014, New Orleans
17. WSSSPE1 Context
• Science is becoming more complex
• Software is becoming more important in science
• Software is becoming part of the scientific
infrastructure
– Should be preserved and reused (for
reproducibility and cost effectiveness)
• But funding, culture, practice, etc. haven’t
caught up
– What changes are needed?
• Bundled under the name “software
sustainability”
18. WSSSPE1 Motivation
• Arfon Smith (GitHub) keynote: Scientific Software and the Open
Collaborative Web
• Example from data reduction in astronomy, where he needed to
remove interfering effects from the device; work needed was
persistent, but there was no practice of sharing this, so many
researchers repeated the same calculations; ~13 person-years
were wasted
• Why don’t we do better?
– Because we are taught to focus on immediate research outcomes and not on
continuously improving and building on tools for research
• When we do know better, why we do not act any different?
– Due to incentives and their lack: only the immediate products of research, not
the software, are valued
• Open source community has excellent cultures of code reuse,
where there is effectively low-friction collaboration through the
use of repositories
– This has generally not happened in highly numerical, compiled language
scientific software
19. WSSSPE1: Developing Software
• Widespread agreement that developing and maintaining
software is hard, but best practices can help
• Difficulty: Making sustainable software means paying
attention to many facets of software design, like APIs,
security, user experience, testing ...
– A single project that requires one fulltime software engineer
may actually require fractions of different kinds of engineers
– But long-tail projects can’t even fund one FTE, let alone one
that can address all these facets
• Team science (the science of teams) is important
• Lack of career paths for developers is an issue
Many of the issues in developing
sustainable software are social, not
technical
20. WSSSPE1: Best Practices
• Communities been built around projects, with:
– Public source code hosting, mailing lists, documentation, wikis, bug
trackers, software downloads, continuous integration, software
quality dashboards, and a general web presence to tie all of these
things together
• Dominant common themes
– Open development and community support
– Tighter interactions among domain scientists and code developers,
and developers and their users (which are often domain scientists)
– Users prefer robust and simple to use codes and platforms
– Continuous integration is good
– Sustainability is challenging for many reasons, including: changing
science, changing platforms and technology, and funding
• General recommendations
– Use existing code/tools where possible
– Code well, be simple and transparent
– Use your code, nurture your community, promote, find support
– Be satisfied with less than perfection
– Keep the scientific goal in focus
21. WSSSPE1: Policy
• Credit, citation, impact
Software work is inadequately visible in ways that “count”
within the reputation system underlying science
– Recognition of work on scientific software, linked to
questions of reward and thus motivation for particular
kinds of work on scientific software
– How to fix: Software papers? DOIs for software?
Altmetrics?
• Implementing Policy
– Need strategies to implement the many facets of
sustainable software for scientific software, in a
spectrum, between 2 extremes:
• “Co-funding” - large, multi-year collaborations, with equal
emphasis on both the science and the software
development
• “Software carpentry” - the scientists themselves will write
and maintain their code, but need good tools to do this well
22. WSSSPE1: Communities
• Communities can form around science areas (developers
work together to maximize science) or technologies
(technical catalysts take developments in one area and
apply them to another)
• Companies or organizations can use well-tested practices
to help communities to form
– E.g. Hackathons, communication channels, conferences,
orientations, and documentation
• Need to educate developers to produce complex, agile,
and sustainable domain-specific software, through:
– Focused community workshops, summer schools, boot
camps; general software development training (and science
training for computer scientists)
– Widely available prototype codes
– Increased credit for software developments
– Career paths in science
23. WSSSPE1: Defining Sustainability
• Sustainability for software does not just mean more
money from the government
– Though it does need a committed effort over time
• Software Sustainability Maturity Model (OSS Watch,
similar to discussion in Katz & Proctor)
– “When choosing software for procurement or development
reuse ... you need to consider the future. While a software
product may satisfy today’s needs, will it satisfy tomorrow’s
needs?... In other words, is the software sustainable?”
• Sustainability not integrated into software engineering due
to lack of accepted definition (Venters et al.)
• What is the goal of sustainability?
– reproducible science, or persistence, or quality, or ?
• How is success in sustainability measured?
– How does a group of developers know when they have
actually achieved sustainable software?
Sustainability: the effort that happens to make the
essential things continue (@pebourne)
24. WSSSPE1: Career Paths
• People are essential elements of research infrastructure -
they need:
– Education and training to be productive
– Career paths to remain motivated
– Incentives to move along their career paths
• It's difficult to motivate researchers to create sustainable
software - why?
– Few research career paths available for supporting software
– No incentives for researchers to develop broad skill sets
outside of domains
– Substantial competition from private companies
• Is there a role (career path) for non-tenure-track
researchers who produce software, data, etc. in
universities?
– Assuming yes, do universities recognize and support this?
• If no, how to get them to?
25. WSSSPE1: Career Paths
• Educate software developers and researchers to produce
sustainable software by teaching them to collaborate more
effectively; diminish distinctions
– Caveat: academic communities aren’t taught how to
evaluate cross-disciplinary work
– Lots of skills needed, domain science, software
development, applied mathematics, computer science, etc.
– Teach general software development to researchers and
general domain knowledge to software developers
– Provide focused community workshops, summer schools,
and boot camps to both, and give them a chance to interact
and work together on problems
• Recognize and reward software development and the
creation of other digital products
• Experiment, e.g. Moore & Sloan data science centers
26. Moving Forward
• WSSSPE1: Multiple linked social issues – Sustainability,
Incentives, Career Paths, Communities
• Computational scientists “have a responsibility to convince their
institutions, reviewers, and communities that software is
scholarship, frequently more valuable than a research article”
(Bourne)
• Hypothesis: better measurement of contributions can lead to
rewards (incentives), leading to career paths, willingness to join
communities, leading to more sustainable software
• Recent CISE/ACI & SBE/SES Dear Colleague Letter: Supporting
Scientific Discovery through Norms and Practices for Software
and Data Citation and Attribution (NSF 14-059,
http://www.nsf.gov/pubs/2014/nsf14059/nsf14059.jsp)
– There is a lack of well-developed metrics with which to assess the
impact and quality of scientific software and data
– NSF seeks to explore new norms and practices for software and data
citation and attribution, so that data producers, software and tool
developers, and data curators are credited”
• 6 EAGERs and 3 collaborative workshops to be funded
• Other ideas welcome – in WSSSPE2? Or discussion? Or email?
27. Resources
• These slides, on: http://slideshare.net/danielskatz
• NSF Software as Infrastructure Vision:
http://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf12113
• Implementation of Software Vision:
http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504817
• Software Infrastructure for Sustained Innovation (SI2) Program
– Scientific Software Elements (SSE) & Scientific Software Integration (SSI) solicitation:
http://www.nsf.gov/publications/pub_summ.jsp?ods_key=nsf14520
– 2013 PI meeting: https://sites.google.com/site/si2pimeeting/
– 2014 PI meeting: https://sites.google.com/site/si2pimeeting2014/
– Awards: http://bit.ly/sw-ci
• Working towards Sustainable Software for Science: Practice and Experiences
(WSSSPE)
– Home: http://wssspe.researchcomputing.org.uk (includes links to all slides & papers)
– 1st workshop paper: http://arxiv.org/abs/1404.7414
– 2nd workshop site: http://wssspe.researchcomputing.org.uk/wssspe2/
• NSF 14-059: “Dear Colleague Letter - Supporting Scientific Discovery through
Norms and Practices for Software and Data Citation and Attribution”
– http://www.nsf.gov/pubs/2014/nsf14059/nsf14059.jsp
28. Credits:
• SI2 Program:
– Current program officers: Daniel S. Katz, Rudolf Eigenmann,
Sumanta Acharya, William Y. B. Chang, John C. Cherniavsky,
Almadena Y. Chtchelkanova, Cheryl L. Eavey, Evelyn Goldfield, Sol
Greenspan, Daryl W. Hess, Peter H. McCartney, Bogdan Mihaila,
Dimitrios V. Papavassiliou, Andrew D. Pollington, Barbara Ransom,
Thomas Russell, Nigel A. Sharp, Thomas Siegmund, Paul Werbos,
Eva Zanzerkia
– Formerly-involved program officers: Manish Parashar, Gabrielle
Allen, Eduardo Misawa, Jean Cottam-Allen
• WSSSPE:
– Organizers: Daniel S. Katz, Gabrielle Allen, Neil Chue Hong, Karen
Cranston, Manish Parashar, David Proctor, Matthew Turk, Colin C.
Venters, Nancy Wilkins-Diehr
– Summary paper authors: Daniel S. Katz, Sou-Cheng T. Choi, Hilmar
Lapp, Ketan Maheshwari, Frank Löffler, Matthew Turk, Marcus D.
Hanwell, Nancy Wilkins-Diehr, James Hetherington, James
Howison, Shel Swenson, Gabrielle D. Allen, Anne C. Elster, Bruce
Berriman, Colin Venters
– Keynote speakers: Phil Bourne, Arfon Smith