How is this data organized and described?
This section explains more about the organization and description of the data, recording editorial decisions. This page is useful for those looking to understand or contribute to this dataset. Every manageable effort will be made to keep the practices consistent and transparent.
The UTSC Library Digital Scholarship Unit is very open to feedback about what does and does not work regarding the current site organization.
The dataset consists of Records with each record representing a Tool.
Individual records should not be authored for corporate entities or broad communities, except for when the corporate entity and/or community have the same name and entry point as the tool itself (for example, Drupal.)
Companies that make multiple pieces of software should usually be reflected in multiple records, with each record describing a single tool.
Individual records should not be authored for separate components of a tool, except for when these individual components have other independent reuse value, are not part of the “core” offering of the tool, and/or are developed by a different group.
Example: Zotero
Zotero is a tool that contains at least two components: the browser plug-in, the web portal, and the desktop tool. You can use the browser plug-in and web portal without the desktop application, but it would be very rare to use the desktop application without using the browser plug-in and web portal. In this case, one record explains the entity Zotero.
Metadata Fields
The metadata fields for each record are as follows:
Note: Contributor name and email are gathered as part of the submission process, but not made available in data export or index. Contributor names will appear under the Credits section of the About page.
Title
When creating the title field, identify the name as clearly and specifically as possible.
Description
When creating the description field, please provide a brief, plain-language, description of the tool, limiting promotional tone and language, and beginning with an imperative sentence (this means usually beginning with a base verb in the bare infinitive form) such as “visualize” and “discover.” The description should give users a sense of what they can do with this software.
Linked Agents
Linked agents are used to link together separate records with a relationship based on a corporate entity or the proper name of a community or tool ecosystem, where knowledge of the interrelationship could productively affect your ability to utilize related tools. This relationship can exist because the same corporate entity develops both tools, but more frequently, it will be because tools have dependencies or strong relationships with one another.
Example: The WordPress platform
If you are familiar with WordPress, you will likely be able to use Commons-in-a-Box, or PressBooks, both of which extend WordPress for special use cases. In this case, there is a “linked agent” provided (“Wordpress”) so that you can retrieve all things that are related to the WordPress Content Management System. The open-source WordPress platform is owned by the private company Automattic, Inc. but knowing this does not increase your ability to use the software, so it’s not referenced here.
Example: Zotero and Digital Scholar
Zotero is a tool built by the non-profit corporate entity Digital Scholar, who also develops Omeka. However, knowing that the same non-profit organization develops both does not increase your access to either tool, as they are totally separate communities. In this case, the linked-agent field does not specify that Digital Scholar is a common link between the two tools.
Note: Linked Agents are not available in the contribution form, but are identified and added before the record is published.
Type(s)
This vocabulary contains terms that are methodologies or approaches in digital scholarship. Each type has a definition that will define its scope and use. Terms vary in specificity and complexity, and are based on a vernacular sense of what an end-user would be looking for. This is close to a 'tags' vocabulary in that it is flat and somewhat informal, and likely to evolve based on observed patterns of use and the evolution of practice.
Example one: Visualizations
Mapping is, strictly speaking, a Visualization but is categorized separately as the Digital Scholarship Unit has gotten specific questions about Mapping.
Cost
This category does not specifically identify exact costs, but rather buckets things into categories of cost. In general, although things that are open-source are free, the dataset differentiates between the two because open-source software (particularly software with a server dependency) is often not free. Learn more about the costs of running open source software in this useful article from opensource.com.
Requirements
This field will answer the question: What do I need to run this software? Is this something you can run on a desktop, or something that requires a server? This field does not identify specific hardware requirements or software that may need to be installed in order to run a program.
For example: You may need to install Python on your laptop in order to use a python-based tool, but the dataset does not specify Python as a requirement. You may need a social media account to use software, but that social media account is not listed as a dependency.
Related Field
This field relates together tools that fill similar niches or that have a relationship that cannot be captured by the other metadata fields, but that may be useful to an end-user. This contrasts to the "Linked Agents" field because instead of grouping things together under publishers or concepts, the items in this field are usually (not always) competitors for similar functionality. Sometimes different versions of software are catalogued as separate records and then linked together.
Example: Website Development
Multiple items are categorized as website development, but a subset (perhaps Wix and WebFlow) would be browser-based website tools that use a Graphical User Interface (GUI) to let you build a site. In this case, the related field will show you that Wix is a similar tool when you are viewing the WebFlow record.
Complexity
Objects are categorized as Basic, Intermediate, and Advanced based on how approachable the tool or resource would be for a novice. A good question to ask is "How long would it take a novice user to get some value out of this resource."This is represented through the site using chilli peppers: Advanced tools are especially 'spicy'! This is assigned across all tools (and not within tool types). This means that all Qualitative research tools will be identified as inherently "spicier" than repositories of freely licensed multimedia that can be understood, downloaded, and used in a variety of contexts with relative ease. This is a very 'hunch-informed' vocabulary that may or may not be useful longer-term, as this is very subjective.