Details
| Original language | English |
|---|---|
| Title of host publication | WebSci '18 |
| Subtitle of host publication | Proceedings of the 10th ACM Conference on Web Science |
| Pages | 353-357 |
| Number of pages | 5 |
| ISBN (electronic) | 978-1-4503-5563-6 |
| Publication status | Published - 15 May 2018 |
| Event | 10th ACM Conference on Web Science, WebSci 2018 - Amsterdam, Netherlands Duration: 27 May 2018 → 30 May 2018 |
Abstract
Digital objects as well as real-world entities are commonly referred to in literature or on the Web by mentioning their name, linking to their website or citing unique identifiers, such as DOI and OR-CID, which are backed by a set of meta information. All of these methods have severe disadvantages and are not always suitable though: They are not very precise, not guaranteed to be persistent or mean a big additional effort for the author, who needs to collect the metadata to describe the reference accurately. Especially for complex, evolving entities and objects like software, pre-defined metadata schemas are often not expressive enough to capture its temporal state comprehensively. We found in previous work that a lot of meaningful information about software, such as a description, rich metadata, its documentation and source code, is usually available online. However, all of this needs to be preserved coherently in order to constitute a rich digital representation of the entity. We show that this is currently not the case, as only 10% of the studied blog posts and roughly 30% of the analyzed software websites are archived completely, i.e., all linked resources are captured as well. Therefore, we propose Micro Archives as rich digital object representations, which semantically and logically connect archived resources and ensure a coherent state. With Micrawler we present a modular solution to create, cite and analyze such Micro Archives. In this paper, we show the need for this approach as well as discuss opportunities and implications for various applications also beyond scholarly writing.
Keywords
- Crawling, Data representation, Scientific workflow, Web archives
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
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WebSci '18: Proceedings of the 10th ACM Conference on Web Science. 2018. p. 353-357.
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Micro Archives as Rich Digital Object Representations
AU - Holzmann, Helge
AU - Runnwerth, Mila
N1 - Publisher Copyright: © 2018 Association for Computing Machinery.
PY - 2018/5/15
Y1 - 2018/5/15
N2 - Digital objects as well as real-world entities are commonly referred to in literature or on the Web by mentioning their name, linking to their website or citing unique identifiers, such as DOI and OR-CID, which are backed by a set of meta information. All of these methods have severe disadvantages and are not always suitable though: They are not very precise, not guaranteed to be persistent or mean a big additional effort for the author, who needs to collect the metadata to describe the reference accurately. Especially for complex, evolving entities and objects like software, pre-defined metadata schemas are often not expressive enough to capture its temporal state comprehensively. We found in previous work that a lot of meaningful information about software, such as a description, rich metadata, its documentation and source code, is usually available online. However, all of this needs to be preserved coherently in order to constitute a rich digital representation of the entity. We show that this is currently not the case, as only 10% of the studied blog posts and roughly 30% of the analyzed software websites are archived completely, i.e., all linked resources are captured as well. Therefore, we propose Micro Archives as rich digital object representations, which semantically and logically connect archived resources and ensure a coherent state. With Micrawler we present a modular solution to create, cite and analyze such Micro Archives. In this paper, we show the need for this approach as well as discuss opportunities and implications for various applications also beyond scholarly writing.
AB - Digital objects as well as real-world entities are commonly referred to in literature or on the Web by mentioning their name, linking to their website or citing unique identifiers, such as DOI and OR-CID, which are backed by a set of meta information. All of these methods have severe disadvantages and are not always suitable though: They are not very precise, not guaranteed to be persistent or mean a big additional effort for the author, who needs to collect the metadata to describe the reference accurately. Especially for complex, evolving entities and objects like software, pre-defined metadata schemas are often not expressive enough to capture its temporal state comprehensively. We found in previous work that a lot of meaningful information about software, such as a description, rich metadata, its documentation and source code, is usually available online. However, all of this needs to be preserved coherently in order to constitute a rich digital representation of the entity. We show that this is currently not the case, as only 10% of the studied blog posts and roughly 30% of the analyzed software websites are archived completely, i.e., all linked resources are captured as well. Therefore, we propose Micro Archives as rich digital object representations, which semantically and logically connect archived resources and ensure a coherent state. With Micrawler we present a modular solution to create, cite and analyze such Micro Archives. In this paper, we show the need for this approach as well as discuss opportunities and implications for various applications also beyond scholarly writing.
KW - Crawling
KW - Data representation
KW - Scientific workflow
KW - Web archives
UR - http://www.scopus.com/inward/record.url?scp=85049394671&partnerID=8YFLogxK
U2 - 10.1145/3201064.3201110
DO - 10.1145/3201064.3201110
M3 - Conference contribution
AN - SCOPUS:85049394671
SP - 353
EP - 357
BT - WebSci '18
T2 - 10th ACM Conference on Web Science, WebSci 2018
Y2 - 27 May 2018 through 30 May 2018
ER -