Integrating Free and Open Source Solutions into Geospatial Science Education

The Move to the Middle: Convergence of the Open-Source and Proprietary Software Industries

Open-source software abbreviated as OSS is computer software that is available with source code and is provided under a software license that permits users to study, change, and improve the software. For the commercial software the source code and certain other rights are normally reserved for copyright holders,i.e. the company who developes the software. A group of people in a collaborative manner often developes the Open source software, not under the roof of a large organization. This strategy makes open source software cheap, reliable and modifiable if needed. In this context we shall discuss mainly the features of Open Source Software, differences of open source and free software and open source software movement in Indian perspective.

This chapter discusses the nature of free and open source software from the perspective of business models that can be used to operate within this emerging industry. The focus in the chapter is on free and open source software in general rather than on the specific geospatial domain, however this area of activity is used in several places for reference and by example. The chapter also examines the closed and proprietary complements of the free and open source world and contrasts the rationale and behaviours of software developers and users within both market places. While it is not the intention to set one or the other markets up as a straw man, it is clear from the discussion that the free and open source alternatives have a number of advantages in terms of developing high quality outputs that are responsive to end user needs while embodying the principles of innovation and advancing knowledge.

Open source software (OSS) is computer software that has its underlying source code made available under a licence. This can allow developers and users to adapt and improve it (Raymond, 2001). Computer software can be broadly split into two development models: • Proprietary, or closed software, owned by a company or individual. Copies of the binary are made public; the source code is not usually made public. • Open-source software (OSS), where the source code is released with the binary. Users and developers can be licenced to use and modify the code, and to distribute any improvements they make. Both OSS and proprietary approaches allow companies to make a profit. Companies developing proprietary software make money by developing software and then selling licences to use the software. For example, Microsoft receives a payment for every copy of Windows sold with a personal computer. OSS companies make their money by providing services, such as advising clients on the GPL licence. The licencee can either charge a fee for this service or work free of charge. In practice, software companies often develop both types of software. OSS is developed by an ongoing, iterative process where people share the ideas expressed in the source code. The aim is that a large community of developers and users can contribute to the development of the code, check it for errors and bugs, and make the improved version available to others. Project management software is used to allow developers to keep track of the various versions. There are two main types of open-source licences (although there are many variants and subtypes developed by other companies): • Berkeley Software Distribution (BSD) Licence: This permits a licencee to “close” a version (by withholding the most recent modifications to the source code) and sell it as a proprietary product; • GNU General Public Licence (GNU, GPL, or GPL): Under this licence, licencees may not “close” versions. The licencee may modify, copy, and redistribute any derivative version, under the same GPL licence. The licencee can either charge a fee for this service or work free of charge. Free software first evolved during the 1970s but in the 1990s forked into two movements, namely free software and open source (Berry, 2004). Richard Stallman, an American software developer who believes that sharing source code and ideas is fundamental to freedom of speech, developed a free version of the widely used Unix operating system. The resulting GNU program was released under a specially created General Public Licence (GNU, GPL). This was designed to ensure that the source code would remain openly available to all. It was not intended to prevent commercial usage or distribution (Stallman, 2002). This approach was christened free software. In this context, free meant that anyone could modify the software. However, the term “free” was often misunderstood to mean no cost. Hence, during the 1990s, Eric Raymond and others proposed that open-source software was coined as a less contentious and more business-friendly term. This has become widely accepted within the software and business communities; however there are still arguments about the most appropriate term to use (Moody, 2002). The OSMs are usually organised into a network of individuals who work collaboratively on the Internet, developing major software projects that sometimes rival commercial software but are always committed to the production of quality alternatives to those produced by commercial companies (Raymond, 2001; Williams, 2002). Groups and individuals develop software to meet their own and others’ needs in a highly decentralised way, likened to a Bazaar (Raymond, 2001). These groups often make substantive value claims to support their projects and foster an ethic of community, collaboration, deliberation, and intellectual freedom. In addition, it is argued by Lessig (1999) that the FLOSS community can offer an inspiration in their commitment to transparency in their products and their ability to open up governmental regulation and control through free/libre and open source code.

How can we address the complexity and cost of applying science to societal challenges? Open science and collaborative R&D may help [1]–[3]. Open science has been described as “a research accelerator” [4]. Open science implies open access [5] but goes beyond it: “Imagine a connected online web of scientific knowledge that integrates and connects data, computer code, chains of scientific reasoning, descriptions of open problems, and beyond …. tightly integrated with a scientific social web that directs scientists' attention where it is most valuable, releasing enormous collaborative potential.” [1]. Open science and collaborative approaches are often described as open source, by analogy with open-source software such as the operating system Linux which powers Google and Amazon—collaboratively created software which is free to use and adapt, and popular for Internet infrastructure and scientific research [6], [7]. However, this use of “open source” is unclear. Some people use “open source” when a project's results are free to use, others when a project's process is highly collaborative [4]. It is clearer to classify open source and open science within a broader class of collaborative R&D, which can be defined as scalable collaboration (usually enabled by information technology) across organizational boundaries to solve R&D challenges [8]. Many approaches to open science and collaborative R&D have been tried [1], [9]. The Gene Wiki has created over 10,000 Wikipedia articles, and aims to provide one for every notable human gene [10]. The crowdsourcing platform InnoCentive has reportedly facilitated solutions to roughly half of the thousands of technical problems posed on the site, including many in life sciences such as the $1 million ALS Biomarker Prize [11]. Other examples include prizes (X-Prize [12]), scientific games (FoldIt [13]), and licensing schemes inspired by open-source software (BIOS [14]). Collaborative R&D approaches vary in openness [15]. In some approaches, the R&D process and outputs are open to all—for example, open-science projects like the Gene Wiki described above. In other approaches which demonstrate what might be called controlled collaboration, there are strong controls on who contributes and benefits—for example, computational platforms like Collaborative Drug Discovery or InnoCentive that support both commercial and nonprofit research [9], [11]. Collaborative approaches can unleash innovation from unforeseen sources, as with crowdsourcing health technologies [11]–[13], [16]. They may help in global challenges like drug development [17], as with India's OSDD (Open Source Drug Discovery) project that recruited over 7,000 volunteers [16] and an open-source drug synthesis project that improved an existing drug without increasing its cost [18]. If you want to apply open science and collaborative R&D, what principles are useful? We suggest Ten Simple Rules for Cultivating Open Science and Collaborative R&D. We also offer eight conversational interviews exploring life experiences that led to these rules (Box 1). Box 1. Conversations on Open Science and Collaborative R&D Many commentators have considered challenges in translating open science and collaborative methods to biomedical research [2]–[4], [9], [17], [20], [24], [26], [28], [29]. How can protecting intellectual property be balanced with freeing researchers to build on previous knowledge? If R&D results are collaboratively created and freely available, who will take responsibility for costly clinical trials and quality control? What will be the Linux of open-source R&D? To explore such challenges and convey life experiences in biomedical open science and collaborative R&D, we offer eight conversational interviews by the first author of this article as supplementary material. The conversations were done on behalf of the Results for Development Institute and are with: Alph Bingham, cofounder of InnoCentive (Text S1) Barry Bunin, CEO of Collaborative Drug Discovery (Text S2) Leslie Chan, open access pioneer and director of Bioline International (Text S3) Aled Edwards, director of the Structural Genomics Consortium (Text S4) Benjamin Good, coleader of the Gene Wiki initiative (Text S5) Bernard Munos, pharmaceutical innovation thought leader (Text S6) Zakir Thomas, director of India's Open Source Drug Discovery (OSDD) project (Text S7) Matt Todd, open science and drug development pioneer (Text S8)

The article examines existing models of free and open-source software licensing worldwide. In particular, software is classified according to the type of distribution licence, while the difference between the concepts of ‘free software’ and ‘open-source software’, their ideological foundations and key features are highlighted. Within the framework of the paper, all free and open-source licences are classified into two key groups – permissive and copyleft. The main features of these groups are defined, and the most widely used licences of each type are analysed. The basis for determining the prevalence of specific free and open-source licences was current statistical data. The state of free and open-source software licensing in the EU is outlined. Special attention is also paid to public domain agreements under the public domain doctrines of the USA and Ukraine, and their relation to free and open-source software. The current legislation of Ukraine regulating free and open-source software licences is analysed. In particular, the legal nature of free and open licenses and their varieties is examined in the context of the existing legal structures of ‘public licence’, ‘licence’, and ‘licence agreement’. Furthermore, attention is given to the Recommendations of the Ministry of Economy, Leisure, and Agriculture regarding the application of free public licences for the use of copyright and related rights, which, for the first time in Ukraine, provide a definition of free public licences. To study the practical application and recognition of free and open-source software licences, relevant judicial practice is analysed. The conclusions emphasise the need for further legislative consolidation and regulation of free and open-source software licences, particularly copyleft licences, which, although operating within the framework of classical copyright, due to their specific nature, do not fully fall under the traditional provisions on public licences.

Much work has been done in recent times to answer the question of why people contribute, and continue to contribute to open-source and free software, despite the lack of immediate financial gain in most cases. Lerner and Tirole (2002) hypothesize that open-source contributions act as a form of job-market signaling – they permit prospective employers to judge a person's ability directly. This paper tests the nature of this signaling using a complementarity framework. Do developers use open source software as a way to enhance the signal from a college education, or to substitute for it, in a form of learning by doing? I find evidence that they are complements, while conclusively rejecting the idea that they are substitutes.

A lot misinformation and mystery surrounds the topic of Open Source software. The conceptual misunderstanding of software is fostered, in some respects, by a lack of understanding within the professional ranks of the computer field. There are many different views of Open Source software today, based upon ones perspective. After about 20 years of evolution, the position of Open Source in our economy still has not coalesced. Few seems to understand whether Open Source is free software for running a computer (i.e., Linux) or just a way to obtain some software products without giving Microsoft ones money. “There is one thing stronger than all the armies in the world and that is an idea whose time has come” - Victor Hugo any view Open Source (OS) software as just a free alternative to proprietary software. The term does not mean that there is no cost associated with its procurement, although some vendors do provide free versions. The word “free” usually means the freedom to copy, modify, or distribute the software. One must be very careful when applying this broad, general meaning to Open Source software. There are many different Open Source licenses in use and it is imperative that users acquaint themselves with the legal ramifications of dealing with intellectual property rights. ` Open Source software should be viewed as a viable alternative in many software selection processes. Recently, the news has portrayed the report of India's Kerala state moving to Linux and OpenOffice for its 2,724 high schools. Likewise, OpenOffice is replacing Microsoft Office in many schools districts around the US. With tight school budgets, school superintendents are realizing significant cost savings by using the OpenOffice products for their campuses. Products such as OpenOffice may not be 100% compatible with their current proprietary counterpart, but for many applications, compatibility is not the issue. The price and the software license management of proprietary packages may be overwhelming.

Over the past decade, numerous computer-assisted retrosynthesis reaction prediction methods have been reported in the chemical literature, several of which are also shared as open-source code. Reports of integrating these modern open-source retrosynthetic prediction techniques into the chemical education classroom, however, is largely absent. This article describes our efforts to teach a computer-assisted retrosynthesis workshop series using open-source reaction prediction software and methods. In addition to three workshops on selected open-source reaction prediction methods, the series included workshops on Python programming and introductory cheminformatics using the RDKit cheminformatics toolkit. A pre and post survey was distributed to better understand participant familiarity and workshop outcomes. Participants indicated that they had minimal experience with cheminformatics, and open-source retrosynthesis software, however after the workshop series they indicated increased familiarity, interest, and desire to pursue additional training related to open-source retrosynthesis software and methods. We conclude this article with our experiences and ideas for future improvements. The workshop materials and code are available with an open source license, and educators are encouraged to adapt and improve the lessons (https://github.com/UA-Libraries-Research-Data-Services/retrosynthesis).

The use of free and open source software is gaining momentum due to the ever increasing availability and use of the Internet. Organizations are also now adopting open source software, despite some reservations in particular regarding the provision and availability of support. One of the greatest concerns about free and open source software is the availability of post release support and the handling of for support. A common belief is that there is no appropriate support available for this class of software, while an alternative argument is that due to the active involvement of Internet users in online forums, there is in fact a large resource available that communicates and manages the management of support requests. The research model of this empirical investigation establishes and studies the relationship between open source software support requests and online public forums. The results of this empirical study provide evidence about the realities of support that is present in open source software projects. We used a dataset consisting of 616 open source software projects covering a broad range of categories in this investigation. The results show that online forums play a significant role in managing support requests in open source software, thus becoming a major source of assistance in maintenance of the open source projects.

The use of free and open source software (OSS) is gaining momentum due to the ever increasing availability and use of the Internet. Organizations are also now adopting open source software, despite some reservations, in particular regarding the provision and availability of support. Some of the biggest concerns about free and open source software are post release software defects and their rectification, management of dynamic requirements and support to the users. A common belief is that there is no appropriate support available for this class of software. A contradictory argument is that due to the active involvement of Internet users in online forums, there is in fact a large resource available that communicates and manages the provision of support. The research model of this empirical investigation examines the evidence available to assess whether this commonly held belief is based on facts given the current developments in OSS or simply a myth, which has developed around OSS development. We analyzed a dataset consisting of 1880 open source software projects covering a broad range of categories in this investigation. The results show that online forums play a significant role in managing software defects, implementation of new requirements and providing support to the users in open source software and have become a major source of assistance in maintenance of the open source projects.

Open source software is becoming increasingly prominent, and the economic structure of open-source development is changing. In recent years, firms motivated by revenues from software services markets have become the primary contributors to open-source development. In this paper we study the role of services in open source software development and explore the choice between open source and proprietary software. Specifically, our economic model jointly analyzes the investment and pricing decisions of the originators of software and of subsequent open-source contributors. We find that if a contributor is efficient in software development, the originator should adopt an open-source strategy, allowing the contributor to offer higher total quality and capture the higher end of the market while the originator focuses on providing software services to lower end consumers. Conversely, if the contributor is not efficient in development, the originator should adopt a proprietary software development strategy, gaining revenue from software sales and squeezing the contributor out of the services market. In certain cases an increase in originator development efficiency can result in increased contributor profits. Finally, we find that, somewhat counterintuitively, an increase in contributor development efficiency can reduce overall social welfare.

The main goal of this document is to help the research community to understand the basic concepts of software distribution: Free software, Open source software, licenses. This document also includes a procedure for research software and data dissemination.

Dendrochronological techniques are paramount in forest research. The current climate change scenario and the central role of forests in biogeophysical cycles enforce the importance of novel techniques to get accurate data from trees and their relationship with the environment in faster ways. Recent technological advances and the place of open source software and hardware are making free, user-developed tools for forest research available to the research community. The aim of this Ph.D. thesis is the development of tools for image acquisition and data collection in dendrochronology based on open source software and hardware. Thus, four different tools for dendrochronological research are presented in five different chapters. The first chapter focuses on the development of a do-it-yourself tool based on open source hardware for image acquisition and wood sample digitization at high resolution. We used open hardware equipment from Arduino and Python programming to develop CaptuRING and published the entire free open source tool as: "CaptuRING: A Do-It-Yourself tool for wood sample digitization" in Methods in Ecology and Evolution, 2022; 13:1185-1191. Furthermore, the original software was registered in the Registro General de Propiedad Intelectual (00/2022/737) of Ministerio de Cultura y Deporte (Spain). The second chapter presents "How to build and install your own CaptuRING". This contribution presents a series of videos with a step-by-step guide to promote the use of CaptuRING in the research community. The manuscript and related videos have been submitted for publication. The third chapter describes ρ-MtreeRing. This free and open-source software, which is written in R, analyzes X-ray films from dendrochronological samples to get microdensity values automatically segmented through a graphical user interface. The open source tool and manuscript are published as: "ρ-MtreeRing. A graphical user interface for X-ray microdensity analysis" in Forests. 2021; 12(10):1405. The fourth chapter describes the potential of deep learning methods to automatically segment xylem vessels. We trained three different convolutional neural networks to segment vessels in stained wood microsections using the Keras framework in Python. Our results demonstrate the potential of these techniques to automatically segment xylem vessels and overcome derived problems from image illumination, which hamper segmentation using classical image segmentation methods. The manuscript is published as "Convolutional neural networks for segmenting xylem vessels in stained cross-sectional images" in: Neural Computing & Applications, 2020; 32:17927-17939. The fifth chapter develops an algorithm to delineate annual ring limits in stained wood microsections of a species with diffuse porous wood using convolutional neural networks. We used Python for image processing and the Keras framework for the algorithm training. The results show the ability of this techniques to obtain accurate tree ring segmentation for quantitative wood anatomy, reaching similar or even outperforming conventional manual delimitation in most of the evaluated cases. The results of this chapter will be presented in the manuscript "Deep Learning for ring bordering in stained cross-sectional images". This PhD Thesis presents four open source tools to get accurate information from wood features to unveil how trees respond to the environment. From digitization at macroscopic perspective, automatic data collection and the development of feature segmentation on microscopic samples. The presented four novel dendrochronological tools based on open source software facilitates forest research in the current climate change scenario.

Focuses on open science practices in suicide research. Specifically, the authors use examples from their own and others' work to demonstrate the opportunities for future-proofing research by implementing open science practices, and they discuss some of the challenges and their potential solutions. They cover implementing open science practices in new, ongoing, and concluded studies, and discuss practices in order of being 'low' to 'high' threshold to implement (based on Kathawalla et al., 2021). Space constraints preclude an extensive presentation of all open science practices although they briefly describe the strategies of providing preprints, sharing study materials and codes, preregistration of studies and registered reports, and sharing research data. To highlight the open science work of as many researchers as possible, examples are provided in Electronic Supplementary Material 1 (ESM 1) rather than in the text. The authors ask for readers' help in adding to these examples via their 'living' reading list (https://osf.io/v6y3t/).