One of the advantages of altmetrics is the diversity and multitude of data sources they refer to. This allows for valuing different sorts of scientific output, be it data, code, or contribution in a blog. However, there are also risks of using such a wide range of data for scholarly evaluation or information seeking. Within OpenUp, we have developed a category of data sources in altmetrics This classification aims at supporting researchers about what kind of data are used in altmetrics and how they can inform scholarly information seeking or dissemination strategies.

 

Altmetrics providers, measure different sources to provide social outreach information for scholars and institutional customers. They do not only provide Altmetrics data, by utilizing various social media platforms but also bibliometric information by sourcing large scientific databases such as Web of Science (WoS)  and Scopus.

Data sources classification
Most data sources have millions of subscribers and users that allow for scientific information to travel beyond the typical audience of scholarly communication. But how the activities and data collection practices can be interpreted and classified?
Data sources used in Altmetrics can be assigned to the following categories: Social bookmarking; video, photo and slide sharing; Social networks; blogging; microblogging; recommendation and review systems; Q & A; Online Encyclopedias; Online digital libraries; Dataset repositories; Online publishers; Search engines and blog aggregators; others. The following table provides an overview of data sources and categories.

 


Categories

Data sources
Social bookmarking CiteULike, Mendeley, Delicious
Video, photo and slide sharing Youtube, Vimeo, Slideshare, Flickr, Daily Motion
Social networks Facebook, Google+, LinkedIn, Academia, ResearchGate
Blogging Nature blogs, PloS blogs, Scientific American blogs, Research Blogging, Nature
Microblogging Twitter, Sina Weibo, Tumblr
Recommendation and review systems F1000, F1000Prime, Reddit, Publons, Amazon reviews, Goodreads
Q & A Stack exchange, other
Online digital libraries and repositories PMC, Europe PMC, BioMed Central, PubMed, Scopus, Web of Science, CrossRef, Fighshare, arXiv, WorldCat, institutional repositories, RePec, EBSCO, SSRN, EPrints, dSpace, USPTO Patents, Lexis, CRIS
Dataset repositories Dryad, Datacite, ADSSource code repositories
Source code repositories Github, Sourceforge, Bitbucket
Online publishers PLoS, Open Edition, Copernicus
Search engines, blog aggregators Science seeker
Other ORCID, Google code, Google patents, WIPO, bit.ly, COUNTER

 

 

Altmetrics are closely linked to various innovative channels of dissemination. The OpenUP Altmetrics Taxonomy will help you to better understand the correlation between the two concepts. The taxonomy provides orientation for scholars who intend to make use of these channels and for those who aim to assess or reflect about their usage. Explore the different categories of scholarly services, based on the selected dimensions.

  •  

    Blogging

    • Attention: Medium
    • General scholarly appreciation: Medium
    • Scholarly relevance: Yes
    • Field specific appreciation: Yes
    • Metrics: Citations, Downloads, Views
    • Provider coverage: Altmetric.com, Plum
    • Technical Accessibility: Partly
    • Intergenerational differences in assessment: High

    Twitter

    • Attention: High
    • General scholarly appreciation: Low
    • Scholarly relevance: No
    • Field specific appreciation: No
    • Metrics: Mentions, Followers
    • Provider coverage: Altmetric.com, Plum, PloS, Impactstory
    • Technical Accessibility: Yes (but restricted)
    • Intergenerational differences in assessment: Medium

    Facebook

    • Attention: High
    • General scholarly appreciation: Very low
    • Scholarly relevance: No
    • Field specific appreciation: No
    • Metrics: Mentions, Views, Likes
    • Provider coverage: Altmetric.com, Plum
    • Technical Accessibility: Yes (but restricted)
    • Intergenerational differences in assessment: Low

    ResearchGate

    • Attention: Medium
    • General scholarly appreciation: Medium
    • Scholarly relevance: Yes
    • Field specific appreciation: Yes
    • Metrics: Activities within the network
    • Provider coverage: None
    • Technical Accessibility: No
    • Intergenerational differences in assessment: NA

     

  •  

    Youtube

    • Attention: High
    • General scholarly appreciation: Medium
    • Scholarly relevance: Yes
    • Field specific appreciation: Yes
    • Metrics: Followers, Mentions, Views
    • Provider coverage: Altmetric.com, Plum
    • Technical Accessibility: Yes
    • Intergenerational differences in assessment: Medium

    Vimeo

    • Attention: Medium
    • General scholarly appreciation: Low
    • Scholarly relevance: No
    • Field specific appreciation: No
    • Metrics: Followers, Mentions
    • Provider coverage: Altmetric.com, Plum
    • Technical Accessibility: No
    • Intergenerational differences in assessment: Low

    Pinterest

    • Attention: Low
    • General scholarly appreciation: Very low
    • Scholarly relevance: No
    • Field specific appreciation: No
    • Metrics: Mentions, Views, Likes
    • Provider coverage: Altmetric.com, Plum
    • Technical Accessibility: Yes (but restricted)
    • Intergenerational differences in assessment: Low

  • Mendeley

    • Attention: Medium
    • General scholarly appreciation: Medium
    • Scholarly relevance: Yes
    • Field specific appreciation: Yes
    • Metrics: Reads, Views
    • Provider coverage: Altmetric.com, Plum, PLOS
    • Technical Accessibility: Yes
    • Intergenerational differences in assessment: Medium

    CiteUlike

    • Attention: Medium
    • General scholarly appreciation: Medium
    • Scholarly relevance: Yes
    • Field specific appreciation: No
    • Metrics: Reads, Mentions
    • Provider coverage: Altmetric.com, Plum
    • Technical Accessibility: Yes
    • Intergenerational differences in assessment: Low

    Reddit

    • Attention: Medium
    • General scholarly appreciation: Very low
    • Scholarly relevance: No
    • Field specific appreciation: No
    • Metrics: Mentions
    • Provider coverage: Altmetric.com, Plum
    • Technical Accessibility: Yes (but restricted)
    • Intergenerational differences in assessment: Low

  • Github

    • Attention: Low
    • General scholarly appreciation: Low
    • Scholarly relevance: Some
    • Field specific appreciation: Yes
    • Metrics: Shares
    • Provider coverage: Altmetric.com, Plum, PLOS
    • Technical Accessibility: Yes
    • Intergenerational differences in assessment: Low

    Figshare

    • Attention: Low
    • General scholarly appreciation: Low
    • Scholarly relevance: Some
    • Field specific appreciation: Yes
    • Metrics: Shares
    • Provider coverage: Altmetric.com, Plum
    • Technical Accessibility: Yes
    • Intergenerational differences in assessment: Low

  • Wikipedia

    • Attention: Medium
    • General scholarly appreciation: Medium
    • Scholarly relevance: Yes
    • Field specific appreciation: No
    • Metrics: Contributions
    • Provider coverage: Altmetric.com, Plum, PLOS
    • Technical Accessibility: Yes
    • Intergenerational differences in assessment: Medium

  • Wikipedia

    • Attention: Medium
    • General scholarly appreciation: Medium
    • Scholarly relevance: NA
    • Field specific appreciation: Yes
    • Metrics: Citations, Contributions
    • Provider coverage: Altmetric.com
    • Technical Accessibility: No
    • Intergenerational differences in assessment: High

 

Dimensions of analysis:

A taxonomy is an attempt to classify entities according to their properties and to certain dimensions. In this case, we have developed certain dimensions that allow for ordering of dissemination channels. Here are the selected dimensions:

Attention

Attention

This category contains information about how channels of dissemination have the potential to increase attention for different types scientific output. The data for this category have been derived from the interviews conducted as well as desk research. It has to be noted that the assessment of attention can under the current situation not be fully disentangled according to target groups. Yet, in a further activity the findings that went into constructing the taxonomy will be harmonized with the findings from WP4 and WP6.

General scholarly appreciation

General scholarly appreciation

This category informs about how a specific communication channel is appreciated across various scholarly audiences. The data for this category have been derived from the survey which was conducted within OpenUp. It contains information about whether scholars find a specific communication channel valuable for their scholarly communication. Note: these perceptions are based on individual assessments of researchers in a survey, not on expert opinions. Again, it must be mentioned that dissemination channels beyond established scholarly communication formats such as conference presentations and publications only rarely receive reward and are only to a lesser extent appreciated in general.

Scholarly relevance

Scholarly relevance

This category contains information as to whether a specific channel of communication has been attributed to be scholarly relevant. We use the term ‘scholarly relevant’ as a general term for denoting as to whether a specific channel or service is of importance for either supporting scholarly workflows or is considered to be useful for addressing specific audiences with scholarly information. The assessment is based on an analysis of the scholarly expert literature in scientometrics, bibliometrics and information science conducted in activity D 5.2. and does not provide a representative perception across all sciences. To give an example, blogs are considered as ‘scholarly relevant’ because a number of scholarly articles in this specific literature have treated them as relevant for communicating scholarly arguments to nonscientific audiences. Recommendations in f1000prime may be considered as scholarly relevant as they can provide important information about the quality of a research article. At the contrary, Twitter mentions may direct attention to a specific research output but they themselves rarely contain or provide any scholarly argument.

Field specific appreciation

Field specific appreciation

This category contains information as to whether the appreciation of a specific communication channel is field specific or not. Some channels of communication are particularly appreciated and used in specific disciplines or scientific fields. There are, for instance, differences in how twitter is assessed among the scholarly communities. The information is based on results from the survey, analysis of scholarly literature as well as expert opinions

Provider coverage

Provider coverage

This category contains information about which channel of communication is tracked by which provider of altmetrics data. As D 5.1. indicated, there are different data providers in altmetrics which fulfil needs for different scholarly communities. The coverage of a specific communication may indicate as to whether the use of a communication channel relates to the needs and practices of specific scholarly communities.

Technical Accessibility

Technical Accessibility

Technical accessibility is meant to denote that a specific communication channel can be freely accessed through its users or by third party persons. Most usage studies in altmetrics have indicated technical accessibility through the existence of APIs (Automated Programming Interface). Some of the data relevant for studies in altmetrics, however, cannot be directly accessed but are provided by commercial services.

Intergenerational assessment

Intergenerational assessment

The survey data have indicated that there are differences in appreciation and usage of specific communication channels. These differences may be even stronger because of a user bias towards senior scholars. This category therefore denotes as to whether the survey indicated differences.

Since the coining of the term, altmetrics has evolved into a hot topic in science, science policy, and the wider public. There are, however, some discussions on how altmetrics will develop in the future. What are the challenges of designing, implementing, and using altmetrics which need to be addressed in the coming years? How can these new metrics provide benefit for different user groups? On the basis of an extensive landscaping effort, we have compelled a list of strengths, weaknesses, risks and opportunities for altmetrics.

 

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