Heather Morrison

Global OA APCs (APC) 2010-2017: Major Trends

Introduction

Sustainable OA (OA) scholarly journal publishing requires a shift from demand to supply side economics. There are many approaches to supply-side funding, including sponsorship, library journal hosting, cooperatives, and transitioning library subscriptions funds to OA support (offsetting in interim phase). The APC model is used by a minority of fully OA journals. APC is important to study as a model that is working well for some journals, as a model some advocate as the basis for systemic change, and as one surrogate for necessary average cost per article, useful to assess the cost-efficiency of diverse approaches. This is the 2017 edition of a longitudinal study [START_REF] Morrison | OA APC dataverse[END_REF][START_REF] Morrison | Open Access Article Processing Charges: DOAJ Survey May 2014[END_REF][START_REF] Morrison | OA APCs (OA APC) Longitudinal Study 2016 Dataset[END_REF] to observe trends in OA journal publishing over time with a focus on APCs and fully-OA journals, to provide evidence on which to base decisions on support for supply-side economics. Will the APC market continue existing market trends in subscriptions of consolidation and price rises beyond inflation? If so, this would be a reason to consider other models. Or perhaps APCs will introduce competition into the marketplace by making the cost of publication transparent to authors and payers. If so, this would be a reason to support APCs.

The literature in the field is extensive. This section is limited to recent exemplars of major research approaches in order to provide context for this paper.

One approach involves payers monitoring their APC payments. Universities UK (2017) recently released a major report, Monitoring the transition to Open Access: December 2017. This is an exceptionally comprehensive report on activity in a country that has pioneered a systemic approach to OA transition. Two findings of key relevance to this study:

1. "mean average APC payment rose from £1,699 in 2013 to £1,969 in 2016, a rise of 16% (as compared with a rise of 5% in the CPI)." (P. 39), (hybrid journals: £2,095; fully-OA journals £1,640). These figures are reported as being in line with other UK and German-based APC payers; and 2. more than half of APC expenditures went to the 3 largest publishers, Elsevier, Springer Nature, and Wiley. OpenAPC (n.d.) is a project in which participating institutions submit data on their APC payments in standard format permitting for re-combining of the results.

There is significant overlap as 51 of the 117 participants are from the UK. The average APC paid for the 44,373 articles published in fully and hybrid OA journals was €1,936 and the median was €1,756.

Other researchers study cost analysis of the potential for systemic transition. [START_REF] Schimmer | Disrupting the subscription journals' business model for the necessary large-scale transformation to OA. A Max Planck Digital Library OA White Paper[END_REF] developed an approach of transitioning traditional journals from subscriptions to OA using offsetting for the OA2020 initiative. As of December 2017, 95 institutions had signed an Expression of Interest to pursue this approach. The Mellon Foundation (2016) Pay it Forward project, similarly assuming transition of existing publishers, found that for the most research-intensive North American research institutions, the total cost to publish in a full APC market would exceed existing library budgets. My [START_REF] Morrison | Economics of scholarly communication in transition[END_REF] analysis of the potential for a global flip to OA journal publishing provides evidence that there is more than sufficient funding from existing spend by academic libraries, and significant cost savings would be possible, but that this requires additional transition such as support for new OA publishers and/or support for small not-for-profit journals.

The objectives of this study are to determine the average and variability of global APC in 2017, and to compare OA journal publishers in 2014 and 2017 to assess what impact, if any, the UK, OA2020, and other initiatives to support APC payment have had on the market to date.

Method

A full description of the 2016 version of the main dataset, henceforth referred to as OA Main used in this project is described in full in Data [START_REF] Morrison | OA APCs (OA APC) Longitudinal Study 2016 Dataset[END_REF]. This remixed dataset includes our team's collection of data from publisher websites, extensive metadata from DOAJ, and the entire datasets for 2010 from [START_REF] Solomon | A study of OA journals using APCs[END_REF] and for 2015 and 2016 from [START_REF] Crawford | Gold OA journals 2011-2016[END_REF]. Versions of the dataset itself are available for download from the project's dataverse [START_REF] Morrison | OA APC dataverse[END_REF] where information on publisher's website clearly indicates that there is no fee, "No" is indicated in the DOAJ 2017 column "Journal article processing charges (APCs)", or Crawford has indicated that the journal is free. Publication fee confirmed means that there is a publication fee listed on the publisher's website (types of fees and amounts are covered below), or that "Yes" in indicated in the DOAJ 2017 column "Journal article processing charges (APCs)". "No information on publication fee" means that no information indicating whether or not there is a publication fee could be found on the publisher's website, or the DOAJ 2017 column "Journal article processing charges (APCs)" indicates "No information". Journals that are ceased are clearly indicated as no longer published on the publisher's website. "Title not found" might a ceased publication, technical error, change in publisher, etc. Only 1 journal was found to have changed from open access to subscription status; this is indicated as a percentage of 0% due to rounding error. The table above presents the 2017 APC (per-article) and APPC (per-page) in USD by frequency in thousands, excluding APC/APPC of 0 (free for now journals). Both APC and APPC exhibit a skew towards the low end of the price range. For example, 1,895 journals have APCs of 1,000 USD or less, while only 6 have APCs above 4,000.

Number of journals by type of publication fee model

Frequency of 2017 APC in USD by amount 13 The above chart illustrates the skew in pricing toward the low end of the range. There are many more journals with prices below 1,000 USD than there are at the high end of the price range.

Publisher Trends

No publication fee: publisher type 16 A rough analysis of the 7,428 journals with "no publication fee" was conducted as follows.

First, journals with a society or institutional association were found using a search/ eliminate/search approach. 2,705 journals were found to have an entry in DOAJ 2017 for "society or institution". An additional 204 journals had a "society or institution" entry in DOAJ 2018 but not DOAJ 2017. 146 journals were identified as having a not-for-profit society, university, or government partnership or full partner through the work of our team. Of the remaining titles, 1,169 publisher names begin with some variation of "university". 103 titles begin with some variation of "society". The remaining titles were searched for words or partial words drawn from the sample relating to university (universid, university, college, colégio, college, department, escola, escula, faculda, faculty); society (socied, societ, sociét, association, asociación, associação), government (government, minist) or words that might fit more than one category (academy, institut). A total of 7,367 titles were found to have a not-for-profit society, university, or government publisher involved, approximately 99% of the sample of 7,428 "no publication fee" journals. A word search of the full list of no publication fee titles for universid and universit found a total of 3,452 titles. That is, about 46% of the no publication fee journals have a fairly clear university publishing model; this percentage is likely understated as words suggesting a sub-university publisher (faculty, school, department) were not included. 17 A complete set of DOAJ metadata from 2014 (9,665 journals) and active titles in OA main 2017 (combining DOAJ metadata with publisher website data) were used for this comparison. Pivot table reports were developed for the list of publisher names. These reports were then examined and further collated manually as publishers are not always automatically collated, primarily due to small variations in publisher names and separate listings by imprint (e.g. Springer, BioMedCentral, and Nature).

The very long tail 18 As illustrated in the above chart, the vast majority of open access publishers studied are very small. Only 2% publish 10 or more OA journals; 16% publish 2-9 journals, and 82% publish only one journal. The distribution is almost identical for 2014, except that the percentage of publishers with just one journal rounds up to 84% (without changing the other percentages due to rounding errors).

Discussion

The global average APC for 2017 was 974 USD, almost identical to the global average of 964 USD reported from our 2014 survey [START_REF] Morrison | Open Access Article Processing Charges: DOAJ Survey May 2014[END_REF] and not much higher than the 2010 906 USD average reported by [START_REF] Solomon | A study of OA journals using APCs[END_REF] (2017).

There is a wide range in pricing and considerable variability. The direction of change in pricing for APCs from 2016 to 2017 also varies, showing prices that are the same, have decreased or increased. Pricing on publisher websites has tended to remain the same or increase, while pricing based on DOAJ shows a greater tendency to decrease prices. This data suggests that the volatility of this emerging market that as first described in 2014

Global OA APCs (APC) 2010-2017: Major Trends ELPUB 2018 [START_REF] Morrison | Open Access Article Processing Charges: DOAJ Survey May 2014[END_REF] is still prevalent. New publishers and journals are entering the market. Initial pricing may be experimental in nature, or artificially low in the case of new journals in order to attract content.

There has been noticeable growth in the OA journal portfolios of large traditional publishers. One factor in this growth is acquisitions. The Springer-BioMedCentral, Wolters Kluwer-Medknow, and De Gruyter-Versita acquisitions all predate 2014. In 2016, Springer acquired Nature. In 2017, Taylor & Francis acquired Co-Action and Sage acquired Libertas Academica. Another factor is partnerships with societies and/or universities; this approach is evident in the OA title lists of De Gruyter, Elsevier, and Wolters Kluwer Medknow. As a result, many of their OA titles do not have APCs.

This slight tendency toward market concentration in the hands of the largest publishers is outshadowed by the very long tail of small publishers and the extensive involvement of university and society publishers as demonstrated by a very rough analysis suggesting that approximately 99% of the 7,428 journals that do not have publication fees have publisher names that include some variation of words closely related to university (e.g. university, universidad) or society (e.g. society, sociedad). This data suggests that the sponsorship model, with costs paid for by the sponsoring university or society, may be more prevalent than APC. This merits further study.

Limitations: the number of fully OA journals being published today is not known and would be very difficult to ascertain in the short term due to rapid growth. Publishers that have never been included in DOAJ are not reflected in this study; this will include publishers who have not met the criteria for DOAJ, and publishers who have not applied for inclusion in DOAJ. In order to track pricing trends over time, the full lists of journals by large publishers are included while the lists of smaller publishers are limited to titles in DOAJ. The data for this study are drawn from several sources using slightly different methodology.

Conclusion

The evidence to date is inconclusive, which suggests that those who pay for scholarly publishing (universities, libraries, funding agencies) have some ability to influence the outcome. Block payment for APCs in the UK appears to support pricing more than four times what is needed for professional UK-based scholarly OA journal publishing.

The very long tail of many very small OA journal publishers, many produced by universities, societies, and independent academics, suggests that a sponsorship model may be more prevalent than APCs and this approach merits further research. Many notfor-profit journals do not charge APCs. Providing modest support for such journals might be the most efficient way to achieve cost savings in the transition to open access, and at the same time avoid perceptions of low quality OA journal publishing associated with commercial APC that are not listed in DOAJ.

BIBLIOGRAPHY

commercial scholarly publishers are entering the OA market: the largest OA journal publishers' portfolios in 2017 were Springer, De Gruyter, Elsevier, and Wolters Kluwer Medknow. However, these are a small portion of OA journal publishing which is still marked by a very long tail and extensive involvement by very small, often university or society publishers. APC pricing shows a wide range and variability. The APC market can be described as volatile.

INDEX

Keywords: OA, APCs, economics

  Not all publication fees are APCs; there are many different sub-models. In this study, fees are treated differently if they are charged per article, per page, or per word (new in 2017).The pay what you want model was used by Cogent in 2017 and is not listed in 2018. The category of page charges has been added in 2018 and is used where the journal only charges a per-page fee clearly related to the print version of the journal. This category may be underestimated because many journals are published in print as well as electronically; hybrid fee structures (APC + print-based charges such as colour and image charges) are not unusual. Submission fees and other types of sub-models such as differential pricing by article type, length, origin of author, etc., are not included.The following tables analyze 3,231 journals for which there is an amount for APC other than 0 (free-for-now journals) and 81 journals with an amount for APPC other than 0. Excluded are a few journals using different models (e.g. charge per word, page charges clearly exclusively print-based, 15 Cogent journals were using a "pay what you want" approach in 2017), and 61 titles that have a cost, but the amount is not specified on the publisher's website.

				Global OA APCs (APC) 2010-2017: Major Trends
	Page charges (new 2018; per-page fee clearly linked exclusively to print)	3
	Publication fees confirmed total		3,795
	APC amount	# journals APPC amount # journals
	0-1,000	1,895	0-100	71
	1,000-2,000	1,011	100-200	7
	2,000-3,000	222	200-300	1
	3,000-4,000	97	300-400	1
	4,000-5,000	6	>400	1
	Total # journals 3,231		81
	Publication fee model			# journals
	APC (per-article fee) with amount including 0	3,625
	APPC (per-page fee)			81
	Cost not specified (website refers to publication fee, no amount given)	61
	Pay what you want (Cogent; not used in 2018)	15
	Charge per word				6
					ELPUB 2018

Conflicting information (e.g different amounts given on different webpages) 4 2017 APC (per article) and APPC (per page) in USD

  The table above illustrates that the overall direction of price changes (same, decrease or increase) varies with the source of data used for the 2017 APC. When data is gathered directly from the publisher's website, 49% of journals show a price increase from 2016 to 2017; from DOAJ, the percentage is 33%. The difference is most marked for price decrease, with only 6% of journal prices on publisher websites showing a decrease but 63% of prices listed in DOAJ. Note that the list of journals included with pricing from the publisher's website includes titles that were not in DOAJ as of 2017 (deleted or not yet added). Both sets of data are included separately to illustrate that the overall direction of price changes is dependent on the sample of journals included. 61 APPC journals for which data is available for 2016 and 2017 (all derived from publishers' websites), show a similar trend, 5 (8%) of journals have decreased in price, 33 (54%) show no change and 23 (38%) have increased in price.

	APC: direction of change 2017-2016
		2017 data from publisher's	2017 data from DOAJ
		website		2017
	Price decrease 133	6%	415	63%
	No change	1,091	46%	31	5%
	Price increase 1,160	49%	215	33%
	Total	2,384	100%	661	100%
	15
		APC APPC
	Average	974 77
	Mode	1,780 86
	Median	750 79
	Standard Deviation 832 62

2017 APC (per article) and APPC (per page) in USD: range, central tendencies and standard deviation

  The above table presents a breakdown of the very long tail. More than 80% of OA journal publishers publish only one journal; 98% publish fewer than 10 journals, and only 2% publish 10 or more journals. These percentages are almost identical for 2014 and 2017. This table also illustrates that there is a net total of about 1,000 new publishers added to DOAJ since 2014.The table on the previous page presents the top 25 publishers for the 2017 dataset by number of journals included, the ranking and the number of journals included in 2017 OA main and the 2014 DOAJ. This illustrates the growth of the OA journal portfolios of some traditional publishers in the last 3 years. In 2014, DOAJ included 2 De Gruyter titles; today according to the De Gruyter Open website this publisher lists over 400. DOAJ listed 8 Elsevier titles in 2014; the Elsevier website in 2017 listed 415 fully OA journals. 5 of the largest publishers are no longer listed in DOAJ (Canadian Center of Science and Education, Internet Scientific Publications, LLC, Macrothink Institute, SCIENCEDOMAIN International, and Scientific Research Publishing; Bentham Open is listed in DOAJ in 2017, but not 2018). 4 of the largest publishers are universities.

	16 17 18 19 20 In contrast with the number of publishers by publisher size, there is a relative decrease in SCIENCEDOMAIN International 50 15 Internet Scientific Publications, LLC 47 47 Ubiquity Press 45 10 19 Oxford University Press 44 11
	the number of journals published by smaller publishers in 2017 (47% of journals were
	one-off in 2014, 37% in 2017). This finding may be an anomaly reflecting the different 20 Baishideng Publishing Group Co. Limited 43 14
	sampling methods in 2014 and 2017. 20 Canadian Center of Science and Education		43	37
	25 top ranked publishers in 2017 by number of journals 21 Universitas Udayana	40	N/A
	Rank Publisher			# 2017	journals	# of journals DOAJ 2014
	1	Springer (222) + BioMedCentral (306) + Nature (86)	614	341
	2	De Gruyter Open			454	2
	3	Elsevier			415	8
	4	Wolters Kluwer Medknow			378	97
	5	Hindawi Publishing Corporation		294	444
	6	Scientific Research Publishing			246	125
	7	MDPI AG			186	104
	8	SAGE Publications			156	10
	9	Taylor & Francis Group			152	2
	10	Dove Medical Press			129	96
	11	Wiley			86	13
	Publishers by number of OA journals DOAJ 2014 12 Universitas Negeri Semarang	OA Main 66	change # change% 3
				2017
	13	Bentham Open			65	104
	Total		5,326	6,329		1,003	19%
	14	Copernicus Publications			55	37
	1 journal #	4,497	5,216		719	16%
	14	Frontiers Media S.A.			55	30
	1 journal%	84%	82%
	15	Macrothink Institute			52	8
	< 10 journals #	5,228	6,197		969	19%
	15	PAGEPress Publications			52	48
	< 10%		98%	98%
	15	Universidade de São Paulo			52	36
	10 or more %	2%	2%

Number of publishers by # of OA journals 2014-2017

  . These findings contrast with the findings of Universities UK of a 16% increase in approximately the same time frame. The global average is less than half the reported average of £1,640 (approximately 2,300 USD) paid for APCs reported by Universities UK (2017) and the €1,936 reported by OpenAPC participants (approximately 2,400 USD). Factors that may account for this are the difference in value of currency between countries; APCs of developing world publishers are relatively low when translated into USD, and the UK's approach of providing block grants specifically to support APCs has probably had an impact on publishers of UK research. However, the case UK-based Ubiquity Press (n.d.), founded by University College London in 2012, demonstrates the potential for cost-savings. Ubiquity's base APC of £400, covering professional publishing services, is 24% of the average UK APC 2016 spend of £1,640 for fully-OA journals as reported by Universities UK

This table demonstrates considerable variation in pricing. The range is wide; APC ranges from 1-5,000 USD, APPC from 4-400 USD. Differences between the 3 measures of central tendency are particularly marked for APC. The median or mid-point of 750 USD is 23% lower than the average, that is, more than half of APC charging journals have fees substantially below the average, while the mode or most common APC of 1,780 USD is close to double the average. For both APC and APPC the standard deviation, a measure of variability, is high, not much lower than the average.

This study is one of the sub-projects of the multi-year Sustaining the Knowledge Commons study on the economics of transition to OA scholarship, funded by Canada's Social Sciences and Humanities Research Council, through an Insight Grant.

ABSTRACTS

The open access (OA) article processing charges (APC) project is a longitudinal study of the


Sergey Parinov
email: sparinov@gmail.com

INDEX Victoria Antonova
email: v_antonova@mail.ru

Global Scholarly Collaboration: from Traditional Citation Practice to Direct Communication

Keywords: Citations as interactive elements, scholarly communication, cooperation, collaboration, shared mental models

Introduction

Current achievements of scholarly digital publishing and citation content analysis create new ways for the better support of the Knowledge Commons. In this paper we discuss the integration of some tools from two ongoing projects. One offers a method of transforming citation data into "interactive elements", another promises to transform the interactive elements into a communication instrument between citing and cited authors.

Both projects are based on the principles of the Open Scholarly Infrastructure [START_REF] Bilder | Principles for Open Scholarly Infrastructures[END_REF]. This guarantees that even after completing the projects, their outputs will be available as a part of a sustainable infrastructure. It means that if there is a demand for the projects' outputs, they can be freely re-used and developed by anyone.

To discuss how current scholarly communication, based on publishing and citing papers, can be replaced by a collaboration between researchers based on direct communication, we should start with a clarification of the relationships between scholarly communication, cooperation, and collaboration.

The main tool of scholarly communication for researchers with the research community is that of publishing their research. References in such publications serve as observable evidence of scholarly cooperation in the research community. Scholarly cooperation, as a kind of socio-economic cooperation (Smith et al., 1995, Axelrod and[START_REF] Axelrod | The evolution of cooperation[END_REF] means that some scholars use the outputs of other scholars and by this, they realize the collective development of scientific knowledge.

Citation network analysis allows us to determine whose results the scholar used, i.e. with whom he had a cooperation, and the position of the scholar in this network. For the research community as a whole, there is no other common method to indicate what and how outputs were used by particular scholars in their research.

6

The forms of cooperation used to organize collective activity may vary depending on the number of participants in this activity and other conditions [START_REF] Smith | Intra-and interorganizational cooperation: Toward a research agenda[END_REF]. Processes of scholarly cooperation based on publishing and citing papers have the form of "horizontal cooperation" [START_REF] Smith | Intra-and interorganizational cooperation: Toward a research agenda[END_REF] among the research community.

7

Scholarly cooperation on a community-wide scale is observable and measurable because: a. current rules and regulations, which oblige scholars to specify their use of previously published research outputs in a prescribed manner;

b. tools and services for research papers preparation and publishing;

c. means for processing the full text of publications and visualizing citation data, relationships and statistics.

8

As a result, the research community has well-developed technology to produce and share publications with citations as an instrument of cooperation. There are also formal/ informal rules and social institutions that regulate the application of this cooperation instrument.

9

Let us compare: scholarly cooperation based on the exchange of publications and citations with another well-known form of collective activity based on direct communication between members of a small group like a research laboratory or a project team.

In the first case, the "cooperation is accomplished by the division of labor among participants as an activity where each person is responsible for solving a portion of the problem" [START_REF] Power | Collaboration vs. Cooperation. There Is a Difference[END_REF]). If we look at how a small group works, as in the second case, we see a collaboration, which "is a coordinated, synchronous activity that is the result of a continued attempt to construct and maintain a shared conception of a problem" [START_REF] Power | Collaboration vs. Cooperation. There Is a Difference[END_REF].

Such comparison shows that publications as a communication and cooperation tool offer participants significantly less effective cooperation. In particular, the authors of research publications do not know about all the facts when someone uses their published research. As a rule, they do not have accurate and complete information on who and when used (cited) their publications, and what exactly was used (cited), and for what purposes. There are no common ways for authors to publicly respond to how other researchers used (cited) their publications. The research community does not have a complete picture of how the publication was used to create new scientific knowledge. Similarly for the authors: it is not known exactly which of their outputs were used, by whom and how exactly.

If we consider citations as a reflection of scholarly cooperative links, then in real academic life the citations bear a lot of information, not all of the same weight. These aspects, including scholars' lines of behavior associated with citations, and the actual content of citations are studied by the sociology of citations [START_REF] Adler | Citation statistics: a report from the International Mathematical Union (IMU) in cooperation with the International Council of Industrial and Applied Mathematics (ICIAM) and the Institute of Mathematical Statistics (IMS)[END_REF]. As the main type, the "grateful" citations [START_REF] Adler | Citation statistics: a report from the International Mathematical Union (IMU) in cooperation with the International Council of Industrial and Applied Mathematics (ICIAM) and the Institute of Mathematical Statistics (IMS)[END_REF] are pointed out, considered as an acknowledgment of the intellectual debt in relation to the cited publication. Such citations directly indicate the scholarly cooperation between citing and cited authors.

Some researchers, however, consider [START_REF] Cozzens | What do citations count? The rhetoric-first model[END_REF]) that for modern research publications the "rhetorical" citations [START_REF] Adler | Citation statistics: a report from the International Mathematical Union (IMU) in cooperation with the International Council of Industrial and Applied Mathematics (ICIAM) and the Institute of Mathematical Statistics (IMS)[END_REF] are more common. They work as the means of conducting scientific discussion, serve as illustrations, and also perform certain "ritual" functions, not directly related to the process of collective creation of scientific knowledge and scholarly cooperation.

This situation is further aggravated by the use of citation indexes to assess research performance. Measuring the success of scholars by the number of citations of their publications affects the essence of the citation process, because in many cases this indicator becomes the goal of scientific activity. Consequently, all the characteristics of the citation process cease to be trustworthy [START_REF] Neylon | Citation metrics are making headlines, but what does citation really mean?[END_REF].

Despite this, the publication of research results and the practice of citation are mandatory in the research community. This allows us to suggest that the data on citation networks extracted from research publications carry information about a substantial part of the existing global network of scholarly cooperation. The processing of these data makes it possible to visualize this network and presumably identify collaborative scholars.

Identifying pairs of scholars, citing and cited, one can suppose that they are related by scholarly cooperation. If the contact information of both is available, it is possible to organize direct scholarly communication between them. When such communications becomes possible between all pairs of cooperative scholars, it promises them better research performance.

The development of a technology for scholarly cooperation between citing and cited authors creates the conditions when researchers can identify the "suppliers" of the research results required by them, and the "consumers" of their own results. Hence, scholars are able to simultaneously coordinate their research in two directions with the "suppliers" of the research results required by them, and with the "consumers" of their own research.

The next step is the creation of the conditions for the emergence of full-fledged collaboration between citing and cited scholars, which normally arises only in small groups.

The second section of the paper considers some research information systems (RIS), the combination of which allows the citations found in research publications to be turned into interactive elements. Such innovation, in its turn, allows RIS to initiate direct communication between cited and citing authors.

In the third section, we discuss how the small-group mechanism of collaboration works and what RIS functionality is required in order to create conditions for the operation of such mechanism on the scale of the entire research community.

In conclusion, the possible consequences of cooperative mechanism implementation for the scientific community as a whole are briefly discussed.

From citing of papers to direct scholarly communication

There is a clear motivation to create a technology which allows direct scholarly communication between researchers who currently can only cite each other's papers. As expected, such an opportunity for scholarly cooperation can greatly increase the research performance of these scholars.

This technology is a combination of existing and newly created tools. One of them is a parsing of citation data from research papers, which also gives us the citation contents around the in-text citations. Within a RIS, the citation content can be used to initiate direct scholarly communication between citing and cited authors. A citation content analysis also helps to use such communications to develop research cooperation.

Parsing of citation data from research papers

Citations in research papers are an important source of data about cooperation between researchers. To analyze this information one has to first extract citation data from research paper content. The approach used by CyrCitEc for citation data parsing was presented in [START_REF] Parinov | Semantic Attributes for Citation Relationships: Creation and Visualization[END_REF]. All citation data extracted by CyrCitEc project are publicly available at http:// peren.openlib.org/. Regularly updated CyrCitEc statistics about parsing results are available at http://citru.repec.org/stats.html.

Only 69% of the papers have full text PDFs available for the citation data parsing and only 51% of the papers have a list of references in more or less standard form.

Based on the set of papers with references we parsed in total 801,318 references, that is on average 18 references per paper. In this set, about 5% of references are duplicated, because different papers can cite the same publications and have the same references.

For 26,467 of the parsed references we were able to create citation relationships between citing and cited papers, since we found cited papers' metadata within RePEc and Socionet information systems.

Using the same set of papers and approach, we parsed 750,607 in-text citations. They mention 1,072,175 parsed references. This is 270,857 references more than total number of parsed references, since some references are mentioned more than once. On average, there are 1.3 mentions per reference.

Non-mentioned references were also counted: 110,340 references (14%) have no in-text citations at all. About 37% of papers with references have at least one non-mentioned reference.

In-text citations

Among different types of citation data available in research papers, in-text citations may keep the data about the character of cooperation between citing and cited authors.

Parsed by CytEcCyr the in-text citation data include the following attributes (see also an example of a data record below):

1. a text string of the style of in-text citation, e.g. a number or an author name in square or round brackets (the tag <Exact> in the example below); An example of parsed data about one in-text citation:

Source: https://goo.gl/Eo1FgG

The in-text citation from the example above has a link with a reference having the number 20 in a paper. CyrCitEc parsed for this reference following data:

Source: https://goo.gl/Eo1FgG

All CyrCitEc data with in-text citations and related references are input for the next tool, which is a part of the Socionet RIS.

Socionet tools

Socionet services, as described in [START_REF] Parinov | Semantic Attributes for Citation Relationships: Creation and Visualization[END_REF], use the in-text citations and references data to produce computer-generated annotations to the content of PDF papers. Fig. 1 shows what these annotations look like using in-text citation and reference data from the examples above. One of the Socionet features is the multiple semantic relationships between information entities [START_REF] Parinov | Towards a Semantic Segment of a Research e-Infrastructure: necessary information objects, tools and services[END_REF]. It allows the linking of citation data with other types of information. A fragment of the semantic linkage network is presented at Fig. 2.

Using these linkages, we can associate additional data with the citation data, e.g. the contact and affiliation data of the authors for the cited and citing papers, metadata of cited and citing papers, etc.

As we expect, in 2019 CyrCitEc will processes all available publications from RePEc and Socionet. As a result, the parsed citation data will be automatically linked with about 70,000 author profiles (https://socionet.ru/collection.xml?h=repec:per:pers&l=en). These author profiles are linked with papers, and with about 15,000 profiles of organizations ( https://socionet.ru/collection.xml?h=repec:edi:inst&l=en) that also have links with other author profiles from their staff.

The system, using the linkages, also can recognizes types of relationships between signedin users and information objects:

1. a user is the author of the browsed object (paper, citation, etc.);

2. a user is a co-author of the selected author;

3. a user is a citing or cited author;

4. a user is just a reader, he/she has no relation with the browsed object.

This information allows the system to initiate different scenarios of direct communications [START_REF] Kogalovsky | Scholarly communication in a semantically enrichable research information system with embedded taxonomy of scientific relationships[END_REF] between cited and citing authors. The system can notify an author about new citations of his/her papers, including its context. Well-known RIS ResearchGate, Academia.edu and others already do it. The system can also provide the author with links to PDFs, which cite his/her papers, where the new citations are highlighted/annotated and work as interactive elements or as a communication instrument.

If the system identified a user as the author of the cited paper and this user clicks the intext citation pointed to his cited paper, the system allows this user to express publically or privately his reaction on how the citing author used/cited his research. According to the citation content, this reaction can be simple as "agree/disagree", or can provide explanations of the cited author what was wrong with using his outputs, or how it could be used properly, etc. If the cited paper has several co-authors the system allows them to express their "agree/disagree" with a reaction of one of them.

The system itself also can initiate some direct communications between citing and cited authors using the sense of the citation content, such as citation polarity or citation function.

Citation content analysis

Citation content analysis, for which CyrCitEc already provides about 750,000 records of the right and left contexts for each in-text citation, has a lot of attention of researchers. [START_REF] Waltman | A review of the literature on citation impact indicators[END_REF] in his review of the traditional citation impact indicators proposed different ways to improve the indicators, including taking into account "the context in which a publication is referenced (i.e., the sentences in a citing publication around the reference to a cited publication)" (Waltman 2016 p. 43).

In recent years, methods for analyzing the content of citations have been actively developed. Some studies [START_REF] Zhang | Citation content analysis (cca): A framework for syntactic and semantic analysis of citation content[END_REF][START_REF] Ding | Content-based citation analysis: The next generation of citation analysis[END_REF] present concepts of contentbased citation analysis (CCA), which addresses a citation's value.

Practical experiments with the analysis of in-text citations (they are also called as the intext references) on various sets of full text papers are also known. One of them identified verbs in citation contexts [START_REF] Bertin | A study of lexical distribution in citation contexts through the IMRaD standard[END_REF] and later they characterized the different sections of articles in terms of the verbs that appear in citation contexts [START_REF] Bertin | Factorial Correspondence Analysis Applied to Citation Contexts[END_REF]. Another aspect of CCA is how references are distributed along the structure of articles, and the age of these cited references [START_REF] Bertin | The invariant distribution of references in scientific articles[END_REF]. Some authors analyzed in-text citations as functions of time, textual progression, and scientific field. They built characteristics of in-text citations in over five million full text articles [START_REF] Boyack | Characterizing in-text citations in scientific articles: A large-scale analysis[END_REF].

Hernández-Alvarez and Gómez (2016) in their survey of CCA provided information about tasks, techniques, and resources, including such tasks as the citation polarity and function classifications.

The analysis of citation polarity/function has the potential to draw conclusions about the motives of authors in citing papers. Such analysis can also produce suggestions: what exactly and was used from the cited papers and why. In some cases, this information may be critically important to the authors of the cited papers and may help to initiate direct communication between them and the citing authors.

If CCA recognizes criticism and the system notifies the author of the criticized paper, it gives him an opportunity to correct mistakes and further develop his research.

If CCA informs the author about a positive impact of his/her paper, then the author can conclude how to develop his research to strengthen research results of other scholars who cited them.

In the both cases, cited authors will benefit if they inform citing authors about their progress with the cited research.

As a result, citation networks will become true communication networks. When implemented, such a system should theoretically allow researchers to directly collaborate with each other without the mediation of the current publishing infrastructure.

Such and many other possible types of direct communications between a pair of researchers, where one is the cited and the citing, are the driving force of research communication and cooperation development.

However, it is not just pairs of communicating researchers. It is an act of, at least, the triple direct communications. Because, if we observe a citing author, he can have direct communications with authors who cited him.

We should address the situation when researchers cooperate and coordinate their activity in a group that includes three parties:

1. themselves ("producers")

2. authors whom they cite ("suppliers")

3. authors who cite them ("consumers").

It means cooperation where "suppliers" and "consumers" also have direct communication and can directly affect each others' activity. Since the group is "a collection of people committed to work jointly toward at least one group goal" [START_REF] Randrup | Philosophy of Collaboration[END_REF], the goal of this group is obviously the creation of new scientific knowledge.

Towards a global scholarly collaboration system

By providing direct scholarly communications for the participants of scholarly cooperation, who have traditionally collaborated via publication exchange and citation, it becomes theoretically possible to create more favorable conditions for their collaborative creativity and the development of new scientific knowledge.

Let us consider a joint activity of scholars in small groups (i.e. laboratories, project teams, etc.), which are strongly based on direct communication between group members.

A group, and specifically a small group, is "a distinguishable set of two or more people who interact, dynamically, interdependently, and adaptively toward a common and valued goal/objective/mission, who have each been assigned specific roles or functions to perform" (Mathieu et al., 2000, p. 274). A key feature of small groups is a harmonization of activities on the principle of "all with everyone."

Another important feature of small groups is the high variability of their environment and, as a consequence, the need for group members to quickly adapt to changing conditions. As Mathieu et al. underlined, "… in order to adapt effectively, team members must predict what their teammates are going to do and what they are going to need in order to do it" (Mathieu et al., 2000, p. 274).

Cooperation is generally defined as a "joint effort toward a group goal" [START_REF] Randrup | Philosophy of Collaboration[END_REF] and as a "concerted collaboration", which is a collaboration with "no identifiable individual deliverables; only group deliverables, toward which members must contribute simultaneous efforts" [START_REF] Randrup | Philosophy of Collaboration[END_REF].

Cooperation as a collective activity of people becomes concerted, if the participants can create and constantly update the collective model of their activity and habitat. They need this model to "play" (simulate) and analyze the various possible options for cooperation. Such a collective model arises if the group members can share with the group their personal mental models and hence create a collective (team) mental model.

The basic idea of mental models is that humans by their mental reflection construct internal working models of the world. "When interacting with the environment, with others, and with the artifacts of technology, people develop internal mental models of themselves and the things with which they are interacting. These models provide predictive and explanatory power for understanding these interactions" (Badke-Schaub et.al., 2007, p. 7).

The concept of a shared or collective mental model is defined as "knowledge structures held by members of a team that enable them to form accurate explanations and expectations for the task, and, in turn, coordinate their actions and adapt their behavior to demands of the task and other team members" [START_REF] Jonker | Shared mental models. A conceptual analysis[END_REF].

The basis of the collaboration mechanism, which works for a small group, is that of shared mental models. A background in this area includes research on the development of public institutions [START_REF] Denzau | Shared mental models: ideologies and institutions[END_REF], increase in the effectiveness of joint activities of people in a group [START_REF] Mathieu | The influence of shared mental models on team process and performance[END_REF], interaction of people with software agents [START_REF] Fan | Realistic cognitive load modeling for enhancing shared mental models in human-agent collaboration[END_REF], environmental protection [START_REF] Jones | Mental models: an interdisciplinary synthesis of theory and methods[END_REF], political activities [START_REF] Richards | Coordination and shared mental models[END_REF], etc.

The sharing of group members' mental models means that members inform each other about their intentions and possibilities regarding options of their joint activity. An aggregation of such information, received from all members, forms a choice area, which is available for analysis to each individual member.

"Shared or team mental models are characterized as knowledge or belief structures that are shared by members of a team, which enable them to form accurate explanations and expectations about the task, and to coordinate their actions and adapt their behaviors to the demands of the task and other team members" (Badke-Schaub et al., 2007 p. 8).

In [START_REF] Parinov | Toward a Theory and Agent-Based Model of the Networked Economy[END_REF] we proposed a conceptualization of how a collaboration mechanism based on shared mental models works.

An aggregation of members' shared mental models creates a collective mental model of the team. Team members interact with the collective mental model by taking information from it, playing with it (sorting out different ways of their cooperation), and by changing it. They can change in the model their personal information image. They can also propose new configurations of the group's cooperation.

In Fig. 3 we illustrate these interactions by the example of forming a collective mental model (CMM) for a group of 4 members. Each member, by continuously exchanging information with others, forms and actualizes his/her own mental model of group cooperation and alienates it into collective model for decision making about the future group's activity.

Fig. 3. Collective mental model

A source of this illustration was published in [START_REF] Parinov | Toward a Theory and Agent-Based Model of the Networked Economy[END_REF] For more explanations for Fig. 3 and its notations see in [START_REF] Parinov | Toward a Theory and Agent-Based Model of the Networked Economy[END_REF].

If group members have fixed in CMM a mutually acceptable configuration of their cooperation, then this configuration passes to the stage of practical implementation. The CMM, formed and set at this stage, is used by the members for the actual coordination of their practical activities.

There is a lot of literature on collaboration research, such as the Six Patterns of Collaboration [START_REF] Briggs | A Six Layer Model of Collaboration[END_REF], which suggests a conceptualization of collaboration as the following processes: generate, reduce, clarify, organize, evaluate, and build commitment. The same authors also provide the Six-Layer Model of Collaboration [START_REF] Briggs | A Six Layer Model of Collaboration[END_REF], which includes collaboration goals, group work products, group activities, group procedures, collaboration tools, and collaborative behaviors. Such research claims an intellectual foundation [START_REF] Randrup | Philosophy of Collaboration[END_REF] for discussing computer-supported collaboration, collaboration support systems [START_REF] Briggs | Facilitator-in-a-Box: Process Support Applications to Help Practitioners Realize the Potential of Collaboration Technology[END_REF], integrated collaboration environment [START_REF] Vindasius | The Integrated Collaboration Environment as a Platform for New Ways of Working: Lesson Learned from Recent Projects[END_REF]) and many others.

However, they do not address the basic collaboration instrument, that is, shared mental models. Without it, it is impossible to respond to the obvious research question: how can the mechanism of scholarly collaboration, which traditionally serves only members of small groups, work for the entire research community?

In this paper, we do not claim to give an exhaustive explanation of the question posed.

Below we discuss what main tasks should be solved to make CMM a part of the social and technical research infrastructure. One of possible options is to implement CMM in RIS, like RePEc or Socionet. Based on services of these RIS we can implement CMM to develop tools for direct communication between citing and cited authors. Since these RIS for economics have about 70,000 identified authors linked with their papers, the proposed mechanism of collaboration will serve a significant part of this research community.

A note: CMM within a RIS already is not a "mental" model. In that case, it would be better to call it a collective information model (CIM).

On a way to having CIM as a part of social and technical research infrastructure we suggest the following main tasks:

1. A synchronization of the individual mental models of the members of the group with their information images in CIM. This function can be realized with the help of an information system that collects and accumulates various data about the activities, intentions and capabilities of cooperative researchers. Tools need to be developed that allow a person to share his mental model with the information system, and also to ensure its continuous realization.

The parameters of the implementation of this function are: the number of group members reflected in the CIM; the accuracy and completeness of the representations of their behavior, intentions and possibilities; and the speed and accuracy of updating changes in these data.

2. Representation in CIM of the environment in which the group works, and a reflection of the changes taking place in this environment.

An information system can also perform this function by collecting information about the environment where the group members cooperate. It is possible that in the near future this function will be implemented even more effectively in connection with the development of the "internet of things". The parameters of the implementation of this function are: the size of the fragment of the environment reflected in the CIM; the accuracy and completeness of the representation of the corresponding fragment of the environment; and the level of actualization of changes in the environment.

3. Playing (making simulations) in the CIM of possible variants of group members' cooperation.

Various computer simulation models can be useful to implement this function, allowing a computer analysis of the best scenarios.

4. Choosing the best variant for cooperation from many possible. With equal relations between group members (no subordination), the implementation of this function means that the members must negotiate. This requires a mechanism of a collective decision-making.

5. Realization of the chosen variant of cooperation in practice, including management functions over the joint activities of the group members. This requires a mechanism for collective management of joint activities.

Summing up listed above, we can conclude that the implementation of the first three tasks are greatly influenced by a power of information technology, while the last two tasks also depend on social norms and rules, i.e. on institutions of cooperation.

Conclusion

If the small-group mechanism of collaboration is used on a larger scale, a cooperation in the research community may works in more effective mode. Cooperative scholars can faster coordinate their activities by direct communication that should give them better research performance.

83 Another consequence is that traditional publications and academic publishing infrastructure lose their monopoly as an instrument of global scholarly communication. This will create some challenges for sustainability of global research community.

84 Another serious challenge is the rapid increase of communication among cooperative researchers resulting in a danger of information overloading for them. As Randrup et al. wrote: "Core insight with a significant negative impact on the performance of collaboration is which have been unveiled by research is cognitive overload and inertia. Individuals have limited attention resources" [START_REF] Randrup | Philosophy of Collaboration[END_REF]. It is a threat, but current research and development in areas like software agents, computer bots and artificial intelligence help humans to cope with an increasing intensity of information flows and give optimistic perspectives for surviving in a coming digital era.

BIBLIOGRAPHY

  2. a link to a reference, mentioned in this in-text citation (the tag <Reference> below); 3. text coordinates of the in-text citation, i.e. a serial number of the first and the last in-text citation symbols counting from the beginning of the paper's content (tags <Start> and <End>); 4. citation contexts located on the left and on the right of the in-text citation; these include at least 200 symbols expanded for taking a whole sentence (tags <Prefix> and <Suffix>).

Fig. 1 .

 1 Fig. 1. An in-text citation as an interactive element

Fig. 2 .

 2 Fig. 2. Semantic linkage network, a fragment

  The project CyrCitEc (https://github.com/citeccyr) is developing tool for the parsing of citation data, including a context for in-text citation from research papers full-text in PDF[START_REF] Parinov | Semantic Attributes for Citation Relationships: Creation and Visualization[END_REF]). The project is funded by the Russian Presidential Academy of National Economy and Public Administration (RANEPA, http://www.ranepa.

ru/eng/). It takes input data from RIS RePEc (http://repec.org/) and Socionet (https://socionet.ru/). In late March 2018, CyrCitEc processed 203 collections of papers with 89,342 publications in total. The largest part of this set are 157 Russian academic journals covering different academic disciplines and provided by NEICON (https://socionet.ru/collection.xml? h=spz:neicon&l=en). There are also research paper series in Russian and English provided by Russian universities, including the Higher School of Economics (https://socionet.ru/ collection.xml?h=repec:hig&l=en), RANEPA (https://socionet.ru/collection.xml? h=repec:rnp&l=en).

Global Scholarly Collaboration: from Traditional Citation Practice to Direct ... ELPUB 2018

ABSTRACTS

The development of recent research information systems allows a transformation of citations in the full text of research papers into interactive elements. Such interactivity in some cases works as an instrument of direct scholarly communications between citing and cited authors. We discuss this challenge for research e-infrastructure development including opportunities for improvements in research cooperation and in collaboration mechanisms for the global research community.


Jan Pokorný

Automatic Subject Indexing and Classification Using Text Recognition and Computer-Based Analysis of Tables of Contents

Book titles for the natural and technical sciences do not include information about all topics a book contains. For example, for a book entitled XML Technology: Principles and Applications in Practice, it is unclear whether a chapter on language XQuery is included or not. Even bibliographic records with subject headings cannot solve such problems because catalogers often do not have sufficient knowledge of particular scientific disciplines. Unlike titles, book tables of contents (ToCs) in the natural and technical sciences often have highly precise descriptions of topics covered in chapters and subchapters. This means it is possible to successfully harvest keywords from ToCs with high relevancy. Such keywords can then become reliable input data for subject indexing and subject classification in library catalogs and other search engines, giving users the ability to search all important topics covered anywhere in a book.

Library collections of print books are traditionally processed for library catalogs in the form of bibliographic records consisting of fields with descriptive data (author name, number of pages, language of publication, name of publisher) and subject data (keywords, subject headings, classification terms). Selected fields are indexed and can serve as access points or filters/facets in a catalog.

Users are usually looking for either a specific book in a catalog (e.g., a user looks for a book entitled Nanotechnology in biology and medicine: methods, devices, and applications by Tauna Vo-Dinh, 2007) or is looking for books on a certain topic (e.g., a user wants some books in the field of nanotechnology in medicine) [START_REF] Lown | How Users Search the Library from a Single Search Box[END_REF]. These are two completely different search strategies. In this article, we will look at a technology that addresses the second strategy, a search based on book subject.

Subject description in bibliographic records for scientific books

Although scientific book titles attempt to express a general topic or focus (what the book is about), they are unable to cover all topics and subtopics contained in a work. For example, the book title Selected Chapters in Nuclear Physics suggests that the main theme of the book is nuclear physics but we do not know what specific topics are included in the book. In this case, a user might refer to subject access data if a bibliographic record for the book is available.

Subject access data is traditionally created by a librarian-cataloger with a book in hand. A cataloger discovers what topics the book covers and performs so-called content analysis. Consequently, the cataloger must define clear keywords expressing the subject of the book as expected by a potential user. Finally, the cataloger has to find the appropriate terms from the existing classification systems supported by the library (most commonly, the Library of Congress Classification, the Dewey Decimal Classification, or the Universal Decimal Classification).

Content analysis performed by a universal cataloger can be problematic. First of all, there are economic aspects, because human labor is expensive. Another disadvantage is time delay: a cataloger is able to accurately describe about 3-4 books per hour [START_REF] Read | Cataloguing Without Tears: Managing Knowledge in the Information Society[END_REF]. If the library buys many books at one time, it can take an unbearably long time for the books to be processed. In libraries with large numbers of books acquired, the delay may even be several weeks. This issue can be partially solved by sharing records between libraries, meaning previously-created records can be copied by other libraries. Records can also contain subject descriptions in many national languages which require translation by libraries. This, too, consumes time.

Another-and perhaps the most serious problem with subject description performed by catalogers-is the limited ability to understand and describe a subject. The quality of description depends on the intellectual assumptions of a cataloger and is always affected by some amount of subjectivity [START_REF] Cloete | Training cataloguing students using a mix of media and technologies[END_REF][START_REF] Romero | An Analysis of Entry-Level Cataloging Errors: Implications for Instruction and Training[END_REF]]. When processing scientific books, a cataloger who is not an expert in a given discipline is not able to correctly and precisely understand and describe the topics contained in the book. This leads not only to inaccuracy of description but also often leads to completely wrong subject classification, with a cataloger putting a book into a different subject classification than an expert would choose [START_REF] Kgosiemang | Education and training for cataloguing at the University of Botswana Library: an overview[END_REF][START_REF] Bowman | Education and training for cataloguing and classification in the British Isles[END_REF][START_REF] Romero | An Analysis of Entry-Level Cataloging Errors: Implications for Instruction and Training[END_REF]. Moreover, catalogers often do not have enough time to study each book in detail. As a result, end users are unable to find books that objectively match their search queries. Let's demonstrate the issue using an example.

A user searches for a book about how to work with a file system in the Python programming language. If the user searches for "python AND file system" in a title or subject index, they will not probably find any matching records. The reason for this is simple: a cataloger probably recognized that the book is about the Python programming language but not did not recognize that some chapter talks about the file system at a certain level of significance. As a result, the bibliographic record with subject access created by this fictional cataloger does not describe the book's topics in enough depth and was not able to recognize nor identify specific topics.

As a result, searching by title or subject for scientific books likely leads to high error rates and a library catalog user probably does not find all the books relevant to specific topical interests. There are several ways libraries can solve this problem.

One way-unfortunately the most frequent solution in many libraries-is to ignore the problem. Universal catalogers create subject descriptions for library collections and the inaccuracy of description is simply tolerated.

Another way to address this problem would be to hire disciplinary specialists who are experts in a particular field. An expert in biology could likely produce fairly accurate descriptions of books from the biological sciences. Unfortunately, this solution is only possible in narrowly specialized professional libraries where the subject range of holdings is so small that the library can employ an appropriate number of catalogers who are also disciplinary experts. However, many general libraries such as national, regional, or large academic libraries build collections across so many scientific disciplines that they cannot afford to employ specially-oriented catalogers for all fields.

Another option is to use the folksonomy method, where end users enrich metadata with custom tags. However, this method requires a relatively high minimum number of users who are actively working with a system. This is a kind of crowd processing, with all related advantages and disadvantages [START_REF] Porter | Folksonomies in the Library: their impact on user experience, and their implications for the work of librarians[END_REF].

Another alternative involves creating relevant subject descriptions without the involvement of expert catalogers. This is possible by implementing automatic recognition of book ToCs and extracting relevant keywords from them.

Keywords extracted from book tables of contents

Non-fiction books, in most cases, come equipped with rich information tools that allow users to quickly navigate to specific chapters or pages-namely, the alphabetical index and the ToC.

While the alphabetical index contains highly atomized and isolated terms that are too context-dependent to be automated harvesting, the ToC is ideal for outlining what each chapter in a book is about. The ToC consists of headings and subheadings for textual content (typically chapters) in the order in which they appear in the book and also marking the page where each part begins. Chapter headings are created by authors who know the topic and text perfectly and therefore should be able to accurately capture key topics for each chapter. In a scientific text, chapter headings consist of keywords carefully chosen by an author, normalized to nominative case with an emphasis on conciseness and simplicity. In sum, we can say that chapter headings represent chapter content. This applies to non-fiction books only-fiction, poetry, and other artistic books include chapter names created with a different intent rather than strictly summarizing content.

ToCs for scientific books thus become ideal data sources for extracting keywords that can be used to enrich subject access descriptions of books. This might seem similar to mining keywords from full-texts but is not actually the case. The basic advantages of using ToCs as data sources when compared to extracting keywords from full-texts can be summarized as follows:

1. Full-text of a book is not required; only a few ToC pages are necessary, 2. ToC items are presented in basic grammar forms, 3. Context for each item is clearly apparent due to the hierarchical relationships of the items (title of the work → section name → chapter name → subchapter name and so on), 4. ToCs contain links to page numbers where chapters begin and these can be used to determine keywords scaled according to how many pages is written about each.

The output of this method can be a set of keywords with a parameter that expresses the space an author devoted to each topic in the book. This parameter can be used for sorting search results by relevance.

Method

The following illustrative example provides detail about the method of extracting keywords from ToCs. Suppose there is a book we only have in print. The process can be split into following steps:

Scanning book pages contained in tables of contents

At our library, we scan all pages where a ToC is present in a book. This depends on how detailed a ToC is and if it is spread over one or more pages. We often see that irrelevant text or some graphic objects are present on ToC pages. Such irrelevant elements will be removed with the following steps. When scanning ToCs, one must be aware that the primary purpose is to retrieve text using OCR. Therefore, it is necessary to check all input errors. Problems can be caused by a missing page, a bent corner, too solid bending, crooked text lines or a book scanned askew. Careful work reduces error rates in the subsequent steps. The result of scan is a bitmap object in the form of a graphic file such as TIFF or JPEG.

OCR with text block detection

Software converting images into text objects must be able to detect the blocks that contain text on a page. Since ToCs have a very diverse structures and layouts, different ways of splitting topics into chapters and subchapters, and different typographical and graphical designs, the software may identify some blocks incorrectly. Therefore, the software must have a capacity for human intervention and should be able to learn from new situations to work better and better.

Irrelevant text block elimination

Pages with ToCs often contain various irrelevant texts and graphic objects which need to be distinguished and removed from processing. For the next steps, we need to work only with text blocks that contain ToC items.

Resolution of word and numeric blocks, removal of stop words

ToCs usually list chapters with the name of each chapter and the page number where each chapter begins. In addition, the page number for the next chapter determines the range of pages that can be used to calculate a relevance scale or to display the importance of a chapter in thematic clouds. Therefore, the software must retrieve the name of each chapter and its location (pages) for each ToC. This can be complicated because of diverse layouts for ToCs on a page.

ToC item names often contain words that indicate sections and chapters only formally and do not contain any information about the content itself. Examples are "Chapter 2," "Book first," "Index," or formal numbering such as "2.1.3." These formal markers can help in the recognition of a ToC hierarchical tree structure but must be distinguished and removed for final processing.

Text analysis with focus on context of TOC items

This step is the most demanding in the whole process and puts a high demand on software. Scientific books typically use a multilevel structure for chapters in which subchapters are embedded into parent chapters, inheriting their context. For example, the name of a subchapter entitled "Paths and their description" can be interpreted in many ways. Its meaning is different for tourist travel books than for books on programming. However, when we put this subchapter in context with a parent chapter "Using file system," we can interpret the meaning of the word "paths" more preciselypaths in a computer file system. If we extend this using another context, resulting from a book title Programming in Python, we can determine the meaning of the word "paths" exactly.

Software must be able to handle ToC items not only in an exact order but must also be able to distinguish item positions in ToC hierarchical trees in order to determine parent and child items as well as the extent of their embedding. Automatic detection of these relations is usually based on the layout of items on a page (embedded items are often indented) or by using typographic characteristics (embedded items often have smaller or thinner fonts than their parent items). The meaning of child items needs to be extended by utilizing context from all parent items in order to create definite and significant keywords.

Keyword extraction

Keywords harvested from ToC items can be optimized and transformed according to the requirements of particular cataloging policies, excluding duplicate items, and so on. If books written in more than one language are processed, automatic translations can also be performed at this point. The system can also remove keywords from chapters which are considered to be marginal (e.g., if a chapter is under 2 pages, it can be assumed that such a topic is presented marginally or inadequately).

Subject classification assignment

Finally, the system suggests terms for selected subject classification systems that best match each book. This functionality leverages a learning mechanism that tracks what keyword combinations have been applied to which classification terms. The system currently supports Universal Decimal Classification, Conspectus, and PSH. Others can be added.

Usage

The result of this process is a list of keywords that can serve as output for information systems, typically library systems or discovery systems. The list can be imported directly into selected bibliographic record fields subsequently indexed for searching or harvested for indexing in another system. Another interesting option is to store keyword lists in a shared repository so that other libraries can use them. Keywords can then be downloaded from the shared storage space using a unique identifier such as ISBN.

In conjunction with bibliographic records, keywords from ToCs can help in the identification of scientific and technical topics that occur most frequently for a certain time period. This can be used for a number of summary views; for example, to display a timeline where a user can clearly see how often a topic occurs in the literature, to show how a given keyword occurs over time in a variety of disciplines, or to trace the intersection of topics between disciplines. Another potential use is for the display of rankings for popular topics which be an attractive alternative to classical book newsletters.

BIBLIOGRAPHY

ABSTRACTS

This paper will describe a method for machine-based creation of high quality subject indexing and classification for both electronic and print documents using tables of contents (ToCs). The technology described here is primarily focused on electronic and print documents for which, because of technical or licensing reasons, it is not possible to index full text. However, the technology would also be useful for full text documents, because it could significantly enhance the accuracy and relevance of subject description by analyzing the structure of ToCs.

INDEX

Keywords: text mining, computer-generated subject headings, computer-generated keywords, machine learning system, library automatization AUTHOR JAN POKORNÝ National Library of Technology, Prague, Czechia jan.pokorny@techlib.cz (corresponding author)